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555 Timer Pro 3 Key: A Powerful Tool for Designing 555 Timer Circuits
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If you are interested in designing and building electronic circuits using the popular 555 timer IC, you might want to check out 555 Timer Pro 3 Key, a software application that provides an array of design wizards, circuit blocks and information panels that facilitate the use of the 555 timer in projects.
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In this article, we will introduce you to the features and benefits of using 555 Timer Pro 3 Key, show you how to use it for designing various types of 555 timer circuits, and give you some examples of circuits that you can create with this software. By the end of this article, you will have a better understanding of how 555 Timer Pro 3 Key can help you design and test your own 555 timer circuits with ease and accuracy.
555 Timer Pro 3 Key is a software application that runs on Windows operating systems. It is compatible with Windows Vista, Windows 7, Windows 8 and Windows 10. To use 555 Timer Pro 3 Key, you need to download and install it on your computer. You can download it from https://www.schematica.com/Downloads.htm, where you can also find a user manual and a video tutorial.
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Once you have installed 555 Timer Pro 3 Key, you can launch it by clicking on its icon on your desktop or in your start menu. You will see a main window that looks like this:
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555 Timer Calculator DigiKey Electronics
-555 Timer Pro 3 Key recommended by evfilara Kit
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-How to Build a Delay Before Turn On Circuit with a 555 Timer
-How to Build a Clock Circuit with a 555 Timer
-How to Build an LED Flasher Circuit with a 555 Timer Chip
-How to Build a Voltage Controlled Oscillator VCO with a 555 Timer Chip
-How to Build a Touch Sensor Circuit with a 555 Timer Chip
-How to Build a Dark activated Switch with a 555 Timer Chip
-How to Build a Sound Activated Switch with a 555 Timer Chip
-How to Build an Adjustable Square Wave Generator Circuit with a 555 Timer Chip
-How to Build a Ramp Generator with Transistors and a 555 Timer Chip
-How to Build an Infrared IR Detector Circuit with a 555 Timer Chip
-How to Build an Overvoltage Protection Circuit with a Zener Diode and a 555 Timer Chip
-How to Build an Automatic Night Light Circuit with a 555 Timer Chip
-How to Build an LED Strobe Light Circuit with a 555 Timer Chip
-How to Build an LED Dimmer Circuit with a 555 Timer Chip
-How to Build an LED Chaser Circuit with a 555 Timer Chip
-How to Build an LED Binary Counter Circuit with a 555 Timer Chip
-How to Build an LED Knight Rider Circuit with a 555 Timer Chip
-How to Build an LED Dice Circuit with a 555 Timer Chip
-How to Build an LED Roulette Wheel Circuit with a 555 Timer Chip
-How to Build an LED Traffic Light Circuit with a 555 Timer Chip
-How to Build an LED Music Spectrum Analyzer Circuit with a 555 Timer Chip
-How to Build an LED Temperature Indicator Circuit with a 555 Timer Chip
-How to Build an LED Thermometer Circuit with a 555 Timer Chip
-How to Build an LED Battery Level Indicator Circuit with a 555 Timer Chip
-How to Build an LED Heart Rate Monitor Circuit with a 555 Timer Chip
-How to Build an LED Pulse Width Modulation PWM Dimmer Circuit with a 555 Timer Chip
-How to Build an LED Fading Effect Circuit with a 555 Timer Chip
-How to Build an LED Flashing Alternating Red Blue Circuit with a 555 Timer Chip
-How to Build an LED Random Flasher Circuit with a 555 Timer Chip
-How to Build an LED Morse Code Transmitter Circuit with a 555 Timer Chip
-How to Build an LED Metronome Circuit with a 555 Timer Chip
-How to Build an LED Siren Sound Generator Circuit with a 555 Timer Chip
-How to Build an LED Police Lights Circuit with a 555 Timer Chip
-How to Build an LED Fireworks Circuit with a 555 Timer Chip
-How to Build an LED Christmas Lights Circuit with a 555 Timer Chip
-How to Build an LED Candle Light Flicker Effect Circuit with a 555 Timer Chip
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The main window consists of four main sections: the design wizards, the circuit blocks, the information panels and the toolbar. Let's take a look at each section in more detail.
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The design wizards
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The design wizards are located on the left side of the main window. They allow you to quickly design common types of 555 timer circuits by entering some parameters and clicking on a button. The design wizards include:
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Astable Wizard: This wizard helps you design an astable multivibrator circuit using a 555 timer, which produces a square wave output with a variable frequency and duty cycle. You can enter the desired frequency, duty cycle, supply voltage and load current, and the wizard will calculate the resistor and capacitor values for you. You can also choose between CMOS or bipolar versions of the 555 timer.
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Monostable Wizard: This wizard helps you design a monostable multivibrator circuit using a 555 timer, which produces a single pulse output with a variable duration when triggered by an input signal. You can enter the desired pulse duration, supply voltage and load current, and the wizard will calculate the resistor and capacitor values for you. You can also choose between CMOS or bipolar versions of the 555 timer.
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Bistable Wizard: This wizard helps you design a bistable multivibrator circuit using two 555 timers, which acts as a flip-flop that can be toggled between two stable states by two input signals. You can enter the supply voltage and load current, and the wizard will calculate the resistor values for you.
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PWM Wizard: This wizard helps you design a pulse width modulator circuit using a single or dual comparator IC (such as LM393) and a single or dual potentiometer (such as B10K), which produces a variable duty cycle output that can be used to control the speed or brightness of a motor or LED. You can enter the desired frequency range, supply voltage and load current, and the wizard will calculate the resistor and capacitor values for you.
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FreqDiv Wizard: This wizard helps you design a frequency divider circuit using one or more flip-flop ICs (such as CD4017), which produces an output signal that has a lower frequency than an input signal by dividing it by an integer factor. You can enter the desired division factor, supply voltage and load current, and the wizard will calculate the resistor values for you.
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Missing Pulse Detector Wizard: This wizard helps you design a missing pulse detector circuit using a single or dual comparator IC (such as LM393) and a single or dual potentiometer (such as B10K), which produces an output signal that indicates whether an input signal has missed one or more pulses within a specified time interval. You can enter the desired time interval, supply voltage and load current, and the wizard will calculate the resistor and capacitor values for you.
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Tone Generator Wizard: This wizard helps you design a tone generator circuit using an astable multivibrator circuit with an RC network that produces an output signal with a variable frequency that can be used to generate musical notes or sound effects. You can enter the desired frequency range, supply voltage and load current, and the wizard will calculate the resistor and capacitor values for you.
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Morse Code Generator Wizard: This wizard helps you design a Morse code generator circuit using an astable multivibrator circuit with an RC network that produces an output signal with a variable frequency that can be used to transmit Morse code messages by turning it on or off according to a predefined pattern. You can enter your message in plain text or Morse code symbols, choose between CMOS or bipolar versions of the 555 timer, select between dot-dash or Farnsworth modes, adjust the speed and tone parameters, and preview your message before generating it.
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Multivibrator Calculator: This calculator allows you to calculate various parameters of an astable or monostable multivibrator circuit using a formula-based approach. You can enter any two known parameters (such as frequency, duty cycle, pulse duration, resistor value or capacitor value) and solve for any other parameter.
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The circuit blocks
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The circuit blocks are located on the right side of the main window. They allow you to build custom types of 555 timer circuits by dragging and dropping predefined components onto a breadboard-like area. The circuit blocks include:
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Basic Blocks: These blocks include basic components such as resistors, capacitors, diodes, LEDs, switches, potentiometers, transistors, relays, speakers, buzzers, motors etc.
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IC Blocks: These blocks include integrated circuits such as comparators (LM393), op-amps (LM741), flip-flops (CD4017), counters (CD4026), decoders (CD4511), multiplexers (CD4051), shift registers (CD4094), logic gates (CD4000 series) etc.
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Timer Blocks: These blocks include various types of timers such as CMOS timers (ICM7555), bipolar timers (NE/SE/LM/SA/NA/LMC/LMCT/LMCTC series) etc.
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The information panels
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The information panels are located on the bottom of the main window. They provide useful information and feedback about the circuit you are designing. The information panels include:
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Output Panel: This panel shows the output voltage and current of the circuit, as well as the power consumption and efficiency.
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Component Panel: This panel shows the component values and tolerances of the circuit, as well as the color codes for resistors and capacitors.
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Error Panel: This panel shows any errors or warnings that may occur during the design process, such as invalid values, missing components, short circuits, etc.
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Help Panel: This panel shows helpful tips and hints on how to use 555 Timer Pro 3 Key, as well as links to online resources and tutorials.
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The toolbar
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The toolbar is located on the top of the main window. It provides access to various functions and settings of 555 Timer Pro 3 Key. The toolbar includes:
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File Menu: This menu allows you to create, open, save, print and export your circuit designs, as well as access the preferences and exit the program.
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Edit Menu: This menu allows you to undo, redo, cut, copy, paste and delete your circuit components, as well as select all or none of them.
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View Menu: This menu allows you to zoom in, zoom out, fit to window or center your circuit design, as well as toggle the grid, snap to grid and show values options.
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Tools Menu: This menu allows you to access the design wizards, the multivibrator calculator, the oscilloscope and the frequency meter.
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Help Menu: This menu allows you to access the user manual, the video tutorial, the online support and the about information.
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Buttons: These buttons allow you to quickly perform some common actions such as creating a new circuit, opening an existing circuit, saving your circuit, printing your circuit, exporting your circuit as an image or a PDF file, undoing or redoing your last action, cutting, copying or pasting your circuit components, zooming in or out your circuit design, accessing the design wizards or the multivibrator calculator.
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Examples of 555 timer circuits designed with 555 Timer Pro 3 Key
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To give you some ideas of what you can do with 555 Timer Pro 3 Key, here are some examples of 555 timer circuits that you can design with this software. You can also find more examples in the user manual and the video tutorial.
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LED flasher circuit
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This circuit uses a 555 timer in astable mode to flash an LED on and off with a variable frequency and duty cycle. You can use the Astable Wizard to design this circuit by entering your desired frequency (for example, 1 Hz), duty cycle (for example, 50%), supply voltage (for example, 9V) and load current (for example, 10 mA). You can also choose between CMOS or bipolar versions of the 555 timer. The wizard will calculate the resistor and capacitor values for you (for example, R1 = 4.7 kΩ, R2 = 4.7 kΩ and C1 = 100 µF). You can then drag and drop the components from the Basic Blocks and Timer Blocks sections onto the breadboard area and connect them according to the schematic diagram shown below:
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You can then simulate and test your circuit using the built-in oscilloscope and frequency meter. You can also adjust the potentiometer R2 to change the duty cycle of the output signal. You should see something like this on your screen:
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Pulse width modulator circuit
-R1 = 1 kΩ, R2 = 10 kΩ and C1 = 0.1 µF). You can then drag and drop the components from the IC Blocks and Basic Blocks sections onto the breadboard area and connect them according to the schematic diagram shown below:
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You can then simulate and test your circuit using the built-in oscilloscope and frequency meter. You can also adjust the potentiometer R2 to change the duty cycle of the output signal. You should see something like this on your screen:
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Frequency divider circuit
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This circuit uses one or more flip-flop ICs (CD4017) to divide an input signal frequency by an integer factor. You can use the FreqDiv Wizard to design this circuit by entering your desired division factor (for example, 10), supply voltage (for example, 9V) and load current (for example, 10 mA). The wizard will calculate the resistor values for you (for example, R1 = 470 Ω and R2 = 4.7 kΩ). You can then drag and drop the components from the IC Blocks and Basic Blocks sections onto the breadboard area and connect them according to the schematic diagram shown below:
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You can then simulate and test your circuit using the built-in oscilloscope and frequency meter. You should see something like this on your screen:
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Conclusion
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In this article, we have introduced you to 555 Timer Pro 3 Key, a powerful tool for designing 555 timer circuits. We have shown you how to use its features and functions, such as the design wizards, the circuit blocks, the information panels and the toolbar. We have also given you some examples of 555 timer circuits that you can design with this software, such as LED flasher circuit, PWM circuit and frequency divider circuit.
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If you are interested in learning more about 555 Timer Pro 3 Key, you can download it from https://www.schematica.com/Downloads.htm, where you can also find a user manual and a video tutorial. You can also contact the developers of 555 Timer Pro 3 Key for feedback or support at info@schematica.com.
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We hope that this article has been helpful and informative for you. If you are looking for a simple, low powered, and highly compatible software application for designing 555 timer circuits, we recommend you to try 555 Timer Pro 3 Key. It will save you time and effort, and help you create amazing electronic projects with ease and accuracy.
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FAQs
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What is the difference between 555 Timer Pro and 555 Timer Pro EX?
-555 Timer Pro is a standard version of the software that provides an array of design wizards, circuit blocks and information panels that facilitate the use of the 555 timer in projects. 555 Timer Pro EX is an extended version of the software that provides additional features such as advanced simulation options, custom component creation, component library management, project management, etc.
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What are the system requirements for running 555 Timer Pro 3 Key?
-555 Timer Pro 3 Key runs on Windows operating systems. It is compatible with Windows Vista, Windows 7, Windows 8 and Windows 10. It requires a minimum of 512 MB RAM, 50 MB disk space and a screen resolution of 1024 x 768 pixels.
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How much does 555 Timer Pro 3 Key cost and how can I get a license key?
-555 Timer Pro 3 Key costs $19.95 for a single user license. You can purchase it online from https://www.schematica.com/Purchase.htm. After purchasing it, you will receive an email with your license key and instructions on how to activate it.
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What are some other sources of information and tutorials on 555 timer circuits?
-Some other sources of information and tutorials on 555 timer circuits are:
How can I contact the developers of 555 Timer Pro 3 Key for feedback or support?
-You can contact the developers of 555 Timer Pro 3 Key for feedback or support at info@schematica.com. You can also visit their website at https://www.schematica.com/.
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Contemporary Management 6th Edition PDF: A Review
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Are you interested in learning more about contemporary management? Do you want to find out how managers can deal with the complex and dynamic challenges of today's business environment? If so, you might want to check out Essentials of Contemporary Management 6th edition, a popular textbook that covers the latest theories and practices of modern management. In this article, we will review this book and provide you with some information on how to access it in PDF format.
Before we dive into the book, let's first define what we mean by contemporary management. Contemporary management is a broad term that refers to the application of current management concepts and techniques to various organizational situations. It encompasses both the traditional functions of planning, organizing, leading, and controlling, as well as the emerging topics of ethics, diversity, globalization, innovation, sustainability, and social responsibility.
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Definition and scope of contemporary management
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According to Jones and George (2019), the authors of Essentials of Contemporary Management 6th edition, contemporary management is "the process of using managerial skills to work with people and resources to accomplish organizational goals" (p. 5). They argue that contemporary managers need to have three sets of skills: conceptual skills (the ability to analyze and diagnose complex situations), human skills (the ability to work well with others), and technical skills (the ability to perform specific tasks).
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The scope of contemporary management is very wide, as it covers all types of organizations (public, private, non-profit, etc.), all levels of management (top, middle, lower, etc.), all functional areas (marketing, finance, operations, etc.), and all industries (manufacturing, service, etc.). Moreover, contemporary management is influenced by various external factors, such as economic conditions, political forces, social trends, technological changes, environmental issues, and cultural diversity.
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Key themes and challenges of contemporary management
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One of the main themes of contemporary management is that managers need to be able to adapt to the changing needs and expectations of their stakeholders. Stakeholders are any individuals or groups who have an interest in or are affected by the activities and performance of an organization. They include stockholders, managers, employees, customers, suppliers, distributors, competitors, community members, society at large, and even future generations.
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Some of the key challenges that contemporary managers face are:
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Managing ethics and social responsibility: Managers need to ensure that their actions and decisions are consistent with their personal values and the values of their organization and society. They also need to balance the interests of various stakeholders and contribute to the social welfare and environmental sustainability of their communities.
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Managing diversity: Managers need to respect and value the differences among people in terms of age, gender, race, ethnicity, religion, disability, sexual orientation, etc. They also need to leverage the diverse talents and perspectives of their workforce to enhance creativity and innovation.
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Managing globalization: Managers need to operate in a global marketplace where they face opportunities and threats from foreign competitors, customers, suppliers, partners, etc. They also need to understand the cultural differences and similarities among people from different countries and regions.
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Managing information technology: Managers need to use information technology (IT) as a strategic tool to improve their efficiency and effectiveness. They also need to cope with the challenges posed by IT, such as security risks, ethical dilemmas, communication barriers, etc.
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Managing innovation: Managers need to foster a culture of innovation where they encourage their employees to generate new ideas and solutions for existing or potential problems or opportunities. They also need to manage the process of innovation from idea generation to implementation.
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Managing change: Managers need to anticipate and respond to changes in their internal or external environment. They also need to implement change initiatives in a way that minimizes resistance and maximizes commitment from their employees.
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What is the 6th edition of Essentials of Contemporary Management?
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Now that we have a general idea of what contemporary management is about, let's take a closer look at the book that we are reviewing. Essentials of Contemporary Management 6th edition is a textbook that provides a concise and comprehensive overview of contemporary management theories and research.
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Authors and background of the book
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The authors of Essentials of Contemporary Management 6th edition are Gareth R. Jones and Jennifer M. George. Jones is a professor of management at Texas A&M University and an expert in strategic management and organizational theory. George is also a professor of management at Texas A&M University and a professor of psychology at Rice University and an expert in organizational behavior and human resource management.
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The book was first published in 2000 and has since been updated and revised several times to reflect the latest developments and trends in contemporary management. The 6th edition was published in 2019 by McGraw-Hill Education, a leading publisher of educational materials.
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Main features and contents of the book
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The main features of Essentials of Contemporary Management 6th edition are:
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-Contemporary management 6th edition Jones and George pdf
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-Jane Haddad essentials of contemporary management 6th Canadian edition pdf
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-Management process today contemporary management 6th edition pdf
-Management ethics and diversity contemporary management 6th edition pdf
-Management in the global environment contemporary management 6th edition pdf
-Planning and strategic management contemporary management 6th edition pdf
-Organizing and change contemporary management 6th edition pdf
-Decision making and controlling contemporary management 6th edition pdf
-Leading individuals and groups contemporary management 6th edition pdf
-Motivating employees contemporary management 6th edition pdf
-Leadership and trust contemporary management 6th edition pdf
-Communication and information technology contemporary management 6th edition pdf
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It is concise: The book has only 16 chapters and about 480 pages, making it suitable for a one-semester course or a self-study guide.
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It is comprehensive: The book covers all the major topics and concepts of contemporary management, from planning to controlling, from ethics to diversity, from globalization to innovation, etc.
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It is relevant: The book uses real-world examples from small, medium, and large companies to illustrate how contemporary managers apply the ideas and techniques of modern management.
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It is engaging: The book uses various pedagogical tools to enhance student learning and interest, such as learning objectives, key terms, summaries, review questions, exercises, cases, etc.
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The contents of Essentials of Contemporary Management 6th edition are organized into four parts:
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The Management Process Today: This part introduces the definition, scope, skills, roles, and challenges of contemporary managers. It also discusses the history and evolution of management thought.
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The Environment Of Management: This part examines the external factors that affect contemporary managers, such as ethics, social responsibility, diversity, globalization, information technology, etc.
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Planning And Controlling: This part explores how contemporary managers plan for future actions and goals, as well as how they monitor and evaluate their performance. It also covers topics such as decision making, strategic management, organizational structure, organizational design, organizational culture, etc.
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Organizing And Leading: This part analyzes how contemporary managers organize people and resources into effective teams and groups. It also covers topics such as motivation, leadership, communication, power, politics, conflict, negotiation, etc.
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Why should you read Essentials Of Contemporary Management 6th edition?
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If you are a student or a practitioner who wants to learn more about contemporary management or improve your managerial skills or knowledge then you should definitely read Essentials Of Contemporary Management 6th edition. Here are some reasons why:
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Benefits And Advantages Of The Book
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The benefits And Advantages Of Reading Essentials Of Contemporary Management 6th edition are:
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You will gain a solid foundation And understanding Of The core principles And concepts Of Contemporary Management And How They Apply To Various Organizational Situations And Problems.
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You will learn about The latest theories And research On Contemporary Management And How They Reflect The changing needs And expectations Of Stakeholders And Society.
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You will discover The best practices And techniques Of Contemporary Managers And How They Deal With The complex And dynamic challenges Of Today's Business Environment.
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Benefits and advantages of the book
-
The benefits and advantages of reading Essentials of Contemporary Management 6th edition are:
-
-
You will gain a solid foundation and understanding of the core principles and concepts of contemporary management and how they apply to various organizational situations and problems.
-
You will learn about the latest theories and research on contemporary management and how they reflect the changing needs and expectations of stakeholders and society.
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You will discover the best practices and techniques of contemporary managers and how they deal with the complex and dynamic challenges of today's business environment.
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You will develop your managerial skills and competencies, such as conceptual, human, and technical skills, as well as ethical, social, global, and innovative mindsets.
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You will improve your critical thinking, problem-solving, decision-making, communication, and leadership abilities by engaging with real-world examples, exercises, cases, etc.
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You will enhance your personal and professional growth by reading a concise and comprehensive book that covers all the essential topics of contemporary management in a clear and engaging way.
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Limitations and criticisms of the book
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Despite its many benefits and advantages, Essentials of Contemporary Management 6th edition is not a perfect book. It has some limitations and criticisms that you should be aware of before reading it. Some of them are:
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It is not very original: The book does not offer any groundbreaking or novel insights or contributions to contemporary management theory or practice. It mainly summarizes and synthesizes existing knowledge from various sources.
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It is not very deep: The book does not provide a thorough or detailed analysis or discussion of some topics or issues that may require more attention or exploration. It tends to simplify or gloss over some complexities or controversies.
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It is not very diverse: The book does not include enough perspectives or voices from different cultures, regions, genders, races, etc. It tends to rely on examples from Western or North American contexts.
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It is not very updated: The book does not reflect some of the most recent developments or trends in contemporary management that may have emerged since its publication in 2019. It may become outdated or obsolete soon.
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How can you access Essentials of Contemporary Management 6th edition PDF?
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If you are interested in reading Essentials of Contemporary Management 6th edition, you may wonder how you can access it in PDF format. PDF stands for Portable Document Format, a file format that preserves the layout, fonts, graphics, etc. of a document regardless of the device or software used to view it. PDF files are convenient for reading online or offline, printing, sharing, etc.
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Legal and ethical issues of downloading PDFs
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However, before you download any PDF file from the internet, you should be aware of the legal and ethical issues involved. Downloading a PDF file of a book without paying for it or obtaining permission from the author or publisher is considered piracy or theft. It violates the intellectual property rights of the creators and distributors of the book. It also deprives them of their rightful income and recognition. Moreover, downloading a PDF file from an unauthorized or unverified source may expose you to malware or viruses that can harm your device or data.
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Therefore, you should always respect the law and the rights of others when accessing any PDF file online. You should only download a PDF file from a legitimate and trustworthy source that has obtained the consent or license from the author or publisher. You should also pay a fair price for the file if required. Alternatively, you can borrow a PDF file from a library or a friend who has legally purchased it.
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Options and alternatives for accessing the book
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you have some options and alternatives to consider. Some of them are:
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You can buy the book online or offline from a reputable seller. The book is available in both hardcover and paperback formats, as well as in e-book format. You can find the book on various platforms, such as Amazon, Google Play, Barnes & Noble, etc. The price may vary depending on the seller and the format.
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You can rent the book online or offline from a reliable provider. The book is available for rent on some platforms, such as Chegg, VitalSource, RedShelf, etc. The rental fee may vary depending on the provider and the duration.
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You can access the book online or offline from a legitimate source. The book is available for access on some platforms, such as McGraw-Hill Connect, McGraw-Hill SmartBook, etc. The access fee may vary depending on the platform and the subscription.
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You can borrow the book online or offline from a trustworthy library or a friend. The book may be available in some libraries, such as public libraries, university libraries, etc. You can check the availability and the borrowing terms on their websites or catalogs. Alternatively, you can ask a friend who has legally purchased the book if they are willing to lend it to you.
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Conclusion
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In conclusion, Essentials of Contemporary Management 6th edition is a concise and comprehensive textbook that covers the latest theories and practices of contemporary management. It is written by two experienced and respected authors who use real-world examples to illustrate how contemporary managers apply management concepts and techniques to various organizational situations and problems. The book has many benefits and advantages for readers who want to learn more about contemporary management or improve their managerial skills or knowledge. However, the book also has some limitations and criticisms that readers should be aware of before reading it. Moreover, readers who want to access the book in PDF format should be careful about the legal and ethical issues involved in downloading PDF files from the internet. They should only use legitimate and trustworthy sources that have obtained the consent or license from the author or publisher.
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Summary of the main points
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The main points of this article are:
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Contemporary management is a broad term that refers to the application of current management concepts and techniques to various organizational situations.
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Essentials of Contemporary Management 6th edition is a concise and comprehensive textbook that covers the latest theories and practices of contemporary management.
-
The book has many benefits and advantages for readers who want to learn more about contemporary management or improve their managerial skills or knowledge.
-
The book also has some limitations and criticisms that readers should be aware of before reading it.
-
Readers who want to access the book in PDF format should be careful about the legal and ethical issues involved in downloading PDF files from the internet.
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They should only use legitimate and trustworthy sources that have obtained the consent or license from the author or publisher.
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Recommendations and suggestions
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Based on this article, we recommend that you:
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Read Essentials of Contemporary Management 6th edition if you are interested in learning more about contemporary management or improving your managerial skills or knowledge.
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Evaluate the book critically and compare it with other sources of information on contemporary management.
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Use legitimate and trustworthy sources to access the book in PDF format if you prefer that format over others.
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Respect the law and the rights of others when accessing any PDF file online.
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- # FAQs
-Q: Who are the authors of Essentials of Contemporary Management 6th edition? A: The authors are Gareth R. Jones and Jennifer M. George. Q: What are some of the key themes and challenges of contemporary management? A: Some of the key themes and challenges are ethics, social responsibility, diversity, globalization, information technology, innovation, and change. Q: What are some of the main features and contents of Essentials of Contemporary Management 6th edition? A: Some of the main features and contents are real-world examples, pedagogical tools, functional approach, integration of diversity, ethics, globalization, and information technology. Q: What are some of the benefits and advantages of reading Essentials of Contemporary Management 6th edition? the latest theories and research on contemporary management, discovering the best practices and techniques of contemporary managers, developing your managerial skills and competencies, improving your critical thinking, problem-solving, decision-making, communication, and leadership abilities, and enhancing your personal and professional growth. Q: What are some of the limitations and criticisms of Essentials of Contemporary Management 6th edition? A: Some of the limitations and criticisms are lack of originality, depth, diversity, and currency. Q: How can you access Essentials of Contemporary Management 6th edition in PDF format legally and ethically? A: You can access it by buying, renting, accessing, or borrowing it from a legitimate and trustworthy source that has obtained the consent or license from the author or publisher. 0a6ba089eb
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diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download E Sound Afs We9 Terbaru The Best Way to Stream and Play Audio Tracks on SoundCloud.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download E Sound Afs We9 Terbaru The Best Way to Stream and Play Audio Tracks on SoundCloud.md
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Download E Sound Afs We9 Terbaru: How to Update Your Soundtrack for Winning Eleven 9
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Winning Eleven 9 is one of the most popular soccer games ever released. It has been praised for its realistic gameplay, graphics, and modes. However, one aspect that may seem outdated or boring for some players is the soundtrack. The original soundtrack of Winning Eleven 9 consists of only a few songs and commentary that may not match your taste or mood.
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If you are looking for a way to spice up your sound effects and make your game more lively and fun, then you should consider downloading E Sound Afs We9 Terbaru. This is a mod that replaces the original soundtrack of Winning Eleven 9 with new songs and commentary that are more diverse and exciting. In this article, we will explain what E Sound Afs We9 Terbaru is, why you should download it, how to download it, and what are some of the songs included in it.
E Sound Afs We9 Terbaru is a mod that replaces the original soundtrack of Winning Eleven 9 with new songs and commentary
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E Sound Afs We9 Terbaru is a mod that changes the sound effects of Winning Eleven 9 by replacing the original e_sound.afs file with a new one. The e_sound.afs file contains all the audio data of the game, such as music, commentary, crowd noise, etc. By changing this file, you can change the entire soundtrack of the game.
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It is compatible with PES 5/WE9/WE9LE and can be installed easily with Kitserver
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E Sound Afs We9 Terbaru is compatible with PES 5/WE9/WE9LE, which are different versions of Winning Eleven 9. PES 5 is the international version of Winning Eleven 9, while WE9LE is an updated version of WE9 that includes some new features and fixes. You can use E Sound Afs We9 Terbaru with any of these versions without any problems.
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To install E Sound Afs We9 Terbaru, you need to have Kitserver installed on your game folder. Kitserver is a tool that allows you to modify various aspects of the game without affecting the original files. You can use Kitserver to add new kits, stadiums, balls, faces, etc. You can also use it to add new sound effects with E Sound Afs We9 Terbaru.
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It features songs from various genres and artists, such as rock, pop, hip hop, EDM, etc.
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E Sound Afs We9 Terbaru features songs from various genres and artists that are popular and catchy. You can find songs from rock, pop, hip hop, EDM, etc. You can also find songs from different countries and regions, such as America, Europe, Asia, etc. You can enjoy listening to these songs while playing your matches or browsing the menus.
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Why Download E Sound Afs We9 Terbaru?
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Downloading E Sound Afs We9 Terbaru can enhance your gaming experience by adding more variety and excitement to the sound effects
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Downloading E Sound Afs We9 Terbaru can make your gaming experience more enjoyable and immersive by adding more variety and excitement to the sound effects. You can hear different songs and commentary that suit your mood and preferences. You can also hear songs that match the atmosphere and theme of the game.
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It can also make your game more up-to-date and relevant to the current music trends and preferences
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Downloading E Sound Afs We9 Terbaru can also make your game more up-to-date and relevant to the current music trends and preferences. You can hear songs that are popular and trendy in the music industry right now. You can also hear songs that are familiar and appealing to you or your friends.
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It can also help you discover new songs and artists that you may not have heard before
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Downloading E Sound Afs We9 Terbaru can also help you discover new songs and artists that you may not have heard before. You can hear songs from different genres and artists that may interest you or surprise you. You can also hear songs from different countries and regions that may expose you to new cultures or styles.
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How to Download E Sound Afs We9 Terbaru?
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To download E Sound Afs We9 Terbaru, you need to have Kitserver installed on your game folder
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To download E Sound Afs We9 Terbaru, you need to have Kitserver installed on your game folder first. If you don't have Kitserver yet, you can download it from Evo-Web forums or other sources. You need to extract Kitserver.zip file and copy the Kitserver folder to your game folder (usually C:\Program Files\KONAMI\Winning Eleven 9). Then you need to run setup.exe inside Kitserver folder and attach it to we8.exe (or pes5.exe or we8le.exe depending on your version).
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You also need to have a backup of your original e_sound.afs file in case you want to restore it later
- 2021 and became a global hit.
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Blinding Lights by The Weeknd
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Blinding Lights is a song by The Weeknd, a Canadian singer-songwriter and producer. It is the second single from his fourth studio album After Hours. It is an electropop song that talks about his longing for someone. It has a synth-heavy beat and an 80s-inspired sound. It was released on November 29, 2019 and became one of the most successful songs of all time.
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Dynamite by BTS
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Dynamite is a song by BTS, a South Korean boy band composed of RM, Jin, Suga, J-Hope, Jimin, V, and Jungkook. It is their first English-language single and their first song to be released as a standalone single. It is a disco-pop song that talks about having fun and celebrating life. It has a catchy hook and a cheerful mood. It was released on August 21, 2020 and became the first song by a Korean act to reach number one on the Billboard Hot 100 chart.
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Drivers License by Olivia Rodrigo
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Drivers License is a song by Olivia Rodrigo, an American singer-songwriter and actress. It is her debut single and the lead single from her debut studio album Sour. It is a power ballad that talks about her heartbreak after a breakup. It has a piano-driven melody and an emotional chorus. It was released on January 8, 2021 and became a viral sensation on social media and streaming platforms.
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The mod also includes new commentary from various languages, such as English, Spanish, French, German, etc.
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E Sound Afs We9 Terbaru also includes new commentary from various languages, such as English, Spanish, French, German, etc. You can hear different commentators and analysts that provide more realistic and diverse feedback on your matches. You can also choose the language that you prefer or that matches your team or league. You can change the language settings in the options menu of the game.
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Conclusion
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Downloading E Sound Afs We9 Terbaru can be a great way to update your soundtrack for Winning Eleven 9 and enjoy a more immersive and diverse gaming experience
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Downloading E Sound Afs We9 Terbaru can be a great way to update your soundtrack for Winning Eleven 9 and enjoy a more immersive and diverse gaming experience. You can hear new songs and commentary that are more varied and exciting than the original ones. You can also hear songs that are up-to-date and relevant to the current music trends and preferences. You can also hear songs that can help you discover new genres and artists that you may not have heard before.
-
It is easy to install and compatible with PES 5/WE9/WE9LE
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It is easy to install and compatible with PES 5/WE9/WE9LE, which are different versions of Winning Eleven 9. You just need to have Kitserver installed on your game folder and download E Sound Afs We9 Terbaru from SoundCloud or Evo-Web forums. You then need to extract the downloaded file and copy the new e_sound.afs file to your Kitserver/dat folder. You then need to run the game and enjoy the new soundtrack.
-
It features songs from various genres and artists that are popular and catchy
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It features songs from various genres and artists that are popular and catchy. You can find songs from rock, pop, hip hop, EDM, etc. You can also find songs from different countries and regions, such as America, Europe, Asia, etc. You can enjoy listening to these songs while playing your matches or browsing the menus.
-
It also includes new commentary from different languages that can suit your preferences
-
It also includes new commentary from different languages that can suit your preferences. You can hear different commentators and analysts that provide more realistic and diverse feedback on your matches. You can also choose the language that you prefer or that matches your team or league. You can change the language settings in the options menu of the game.
- # FAQs - Q: What is E Sound Afs We9 Terbaru? - A: E Sound Afs We9 Terbaru is a mod that replaces the original soundtrack of Winning Eleven 9 with new songs and commentary. - Q: How to download E Sound Afs We9 Terbaru? - A: To download E Sound Afs We9 Terbaru, you need to have Kitserver installed on your game folder and download E Sound Afs We9 Terbaru from SoundCloud or Evo-Web forums. You then need to extract the downloaded file and copy the new e_sound.afs file to your Kitserver/dat folder. - Q: What are some of the songs included in E Sound Afs We9 Terbaru? Montero (Call Me By Your Name) by Lil Nas X, Stay by The Kid Laroi and Justin Bieber, Peaches by Justin Bieber feat. Daniel Caesar and Giveon, Butter by BTS, Save Your Tears by The Weeknd and Ariana Grande, Blinding Lights by The Weeknd, Dynamite by BTS, and Drivers License by Olivia Rodrigo. - Q: What are the benefits of downloading E Sound Afs We9 Terbaru? - A: Downloading E Sound Afs We9 Terbaru can enhance your gaming experience by adding more variety and excitement to the sound effects. It can also make your game more up-to-date and relevant to the current music trends and preferences. It can also help you discover new songs and artists that you may not have heard before. - Q: How to restore the original soundtrack of Winning Eleven 9? - A: To restore the original soundtrack of Winning Eleven 9, you need to copy your backup e_sound.afs file back to your Kitserver/dat folder. You need to overwrite the new e_sound.afs file with the original one. You then need to run the game and enjoy the original soundtrack. 0a6ba089eb
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diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Edius 7.5 Serial Number Free PATCHED 53l.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Edius 7.5 Serial Number Free PATCHED 53l.md
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Edius 7.5 Serial Number Free 53l: How to Get It and Why You Need It
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If you are looking for a powerful and easy-to-use video editing software for your PC, you might have heard of Edius 7.5. This software is designed for professional video editors who want to create high-quality videos with fast and flexible workflows. But before you can enjoy the full features and benefits of this software, you need to have a valid serial number that allows you to activate and register your product online.
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In this article, we will explain what Edius 7.5 is, what a serial number is and why you need it, how to get a serial number for free, how to register your serial number online, and how to use Edius 7.5 software after registering it. We will also answer some frequently asked questions about this topic at the end of the article.
Edius 7.5 is a non-linear video editing software developed by Grass Valley, a company that specializes in providing solutions for broadcast and media industries. Edius 7.5 was released in September 2014 as an update to the previous version, Edius 7.
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Edius 7.5 supports various formats and codecs, such as AVCHD, XAVC, XAVC S, AVC-Ultra, MPEG-2, DVCPRO HD, JPEG2000, DNxHD, ProRes, RAW, RED R3D, Canon XF-AVC (import only), Sony XAVC (import only), Cinema DNG (import only), etc. It also supports resolutions up to 4 K resolution and 3D editing. It also has a multi-camera editing mode that allows you to edit up to 16 different sources simultaneously.
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Edius 7.5 is compatible with Windows 7, Windows 8, and Windows 10 operating systems. It requires a minimum of 1 GB RAM, 6 GB hard disk space, and a graphics card that supports Direct3D 9.0c or later. It also requires an internet connection for software license activation and validation.
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The main features and benefits of Edius 7.5 software
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Edius 7.5 software has many features and benefits that make it a popular choice among video editors. Some of the main features and benefits are:
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It has a user-friendly interface that allows you to customize your workspace according to your preferences and needs.
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It has a fast and flexible workflow that lets you edit videos in real-time without rendering or transcoding.
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It has a powerful and versatile editing engine that supports unlimited video, audio, title, and graphics tracks.
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It has a comprehensive and advanced toolset that includes color correction, keying, masking, transitions, filters, effects, audio mixing, titling, etc.
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It has a proxy mode that enables you to edit high-resolution videos on low-specification computers by using low-resolution files as proxies.
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It has a native support for various formats and codecs, which means you can import and export videos without conversion or quality loss.
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It has a built-in DVD and Blu-ray disc authoring tool that allows you to create professional-looking discs with menus, chapters, subtitles, etc.
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It has a seamless integration with other Grass Valley products, such as K2 media servers, GV STRATUS media production tools, GV EDIUS XS nonlinear editors, etc.
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What is a serial number and why do you need it for Edius 7.5?
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The definition and function of a serial number
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A serial number is a unique code that identifies a specific product or software. It is usually composed of letters and numbers, and it is often printed on the product packaging or the software installation disc. A serial number serves as a proof of purchase and ownership of the product or software.
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A serial number is also used to activate and register the product or software online. Activation is the process of verifying the authenticity and validity of the serial number. Registration is the process of creating an online account and providing personal information to the product or software manufacturer or provider.
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Activation and registration are important for several reasons:
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They prevent piracy and illegal use of the product or software by unauthorized users.
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They enable you to access the full features and benefits of the product or software without limitations or restrictions.
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They allow you to receive updates, patches, bug fixes, and technical support from the product or software manufacturer or provider.
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They help you recover your product or software in case of loss, damage, or theft.
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The advantages of having a valid and working serial number for Edius 7.5
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If you have a valid and working serial number for Edius 7.5, you can enjoy the following advantages:
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You can activate and register your Edius 7.5 software online without any hassle or difficulty.
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You can use Edius 7.5 software without any time limit or watermark on your videos.
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You can access all the features and functions of Edius 7.5 software without any limitation or restriction.
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You can receive free updates and upgrades for Edius 7.5 software as long as it is supported by Grass Valley.
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You can get technical support and customer service from Grass Valley whenever you encounter any problem or issue with Edius 7.5 software.
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How to get a serial number for Edius 7.5 for free?
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The legal and recommended way: buying it from the official website or authorized dealers
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The legal and recommended way to get a serial number for Edius 7.5 is to buy it from the official website or authorized dealers. This way, you can ensure that you are getting a genuine and legitimate product that is compatible with your system and meets your expectations.
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To buy a serial number for Edius 7.5 from the official website, you need to visit https://www.grassvalley.com/products/edius_pro_7/ and click on the "Buy Now" button. You will be redirected to a secure online store where you can choose your preferred payment method and currency. You will also need to provide your personal and billing information, such as your name, email address, phone number, country, etc. After completing the payment process, you will receive an email confirmation with your serial number and download link for Edius 7.5 software.
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To buy a serial number for Edius 7.5 from authorized dealers, you need to find a local or online retailer that sells Grass Valley products in your region. You can use the https://www.grassvalley.com/sales/ page to locate the nearest dealer in your area. You will need to contact the dealer and inquire about the availability and price of Edius 7.5 software. You will also need to provide your personal and billing information, such as your name, email address, phone number, country, etc. After completing the payment process, you will receive an email confirmation with your serial number and download link for Edius 7.5 software.
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The risky and not recommended way: finding it for free online from unreliable sources
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The risky and not recommended way to get a serial number for Edius 7.5 is to find it for free online from unreliable sources. This way, you may end up with a fake or invalid product that may harm your system or compromise your security.
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Some of the common sources of free serial numbers for Edius 7.5 are:
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Crack websites: These are websites that offer cracked or hacked versions of software that bypass the activation and registration processes. These websites may contain viruses, malware, spyware, or ransomware that can infect your system and steal your data.
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Keygen programs: These are programs that generate random serial numbers for software that may or may not work. These programs may also contain viruses, malware, spyware, or ransomware that can infect your system and steal your data.
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Torrent websites: These are websites that allow users to share files through peer-to-peer networks. These websites may contain fake or corrupted files that can damage your system or expose you to legal risks.
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Some of the common risks and disadvantages of using free serial numbers for Edius 7.5 are:
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You may not be able to activate or register your Edius 7.5 software online because the serial number may be already used by someone else or blocked by Grass Valley.
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You may not be able to use Edius 7.5 software without any time limit or watermark on your videos because the serial number may be expired or invalid.
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You may not be able to access all the features and functions of Edius 7.5 software because the serial number may be incompatible or incomplete.
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You may not be able to receive free updates and upgrades for Edius 7.5 software because the serial number may not be eligible or supported by Grass Valley.
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You may not be able to get technical support and customer service from Grass Valley because the serial number may not be recognized or verified by Grass Valley.
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You may face legal consequences if you are caught using a pirated or illegal version of Edius 7.5 software because it violates the intellectual property rights of Grass Valley.
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are some of the basic functions and operations of Edius 7.5 software:
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Importing videos: You can import videos from various sources, such as your computer, camera, external drive, etc. by using the "File" menu or the "Bin" window. You can also drag and drop files from your Windows Explorer to the "Bin" window.
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Organizing videos: You can organize your videos in the "Bin" window by creating folders, subfolders, bins, and sequences. You can also rename, delete, move, copy, or sort your videos in the "Bin" window.
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Editing videos: You can edit your videos in the "Timeline" window by using the "Source" and "Record" monitors. You can also use the "Tool Palette" to access various editing tools, such as trim, cut, split, ripple, slip, slide, etc.
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Adding effects: You can add effects to your videos in the "Effect Palette" window by using the "Effect List" and the "Information" panels. You can also drag and drop effects from the "Effect Palette" to the "Timeline" or the "Record" monitor.
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Adjusting settings: You can adjust the settings of your videos in the "Information" panel by using the tabs for video, audio, layouter, motion tracker, etc. You can also use keyframes to animate your settings over time.
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Exporting videos: You can export your videos from the "File" menu or the "Print to File" window. You can choose from various formats and presets, such as AVI, MPEG-2, H.264, QuickTime, etc. You can also customize your export settings, such as resolution, frame rate, bitrate, etc.
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The tips and tricks on how to optimize your video editing experience with Edius 7.5 software
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Here are some tips and tricks on how to optimize your video editing experience with Edius 7.5 software:
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-
Use keyboard shortcuts: You can use keyboard shortcuts to perform common tasks faster and easier. You can find a list of keyboard shortcuts in the "Help" menu or the user manual.
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Use proxy mode: You can use proxy mode to edit high-resolution videos on low-specification computers by using low-resolution files as proxies. You can enable proxy mode in the "Settings" menu or the "Project Settings" window.
-
Use multicam mode: You can use multicam mode to edit multiple camera angles simultaneously by using the "Multicam Mode" button or the "Multicam Sequence Settings" window. You can also use the "Sync Points" feature to synchronize your clips by timecode, audio waveform, or markers.
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Use batch export: You can use batch export to export multiple sequences or clips at once by using the "Batch Exporter" tool or the "Batch Export Settings" window. You can also use the "Watch Folder" feature to automatically export files that are added to a specific folder.
In conclusion, Edius 7.5 is a powerful and easy-to-use video editing software that offers fast and flexible workflows and supports various formats and codecs. To use Edius 7.5 software, you need to have a valid serial number that allows you to activate and register your product online. The legal and recommended way to get a serial number is to buy it from the official website or authorized dealers. The risky and not recommended way is to find it for free online from unreliable sources. Once you have a serial number, you need to register it online by following a simple step-by-step guide. After registering your serial number, you can start using Edius 7.5 software by following some basic functions and operations. You can also optimize your video editing experience by following some tips and tricks.
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FAQs
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Here are some frequently asked questions about Edius 7.5 serial number free 53l:
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Q: How much does Edius 7.5 software cost?
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A: The price of Edius 7.5 software depends on your region and currency. You can check the current price on the official website https://www.grassvalley.com/products/edius_pro_7/ or contact your local or online dealer.
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Q: How long does the serial number last?
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A: The serial number lasts for as long as Edius 7.5 software is supported by Grass Valley. You can use it to activate and register your product online and receive free updates and upgrades. However, you can only use it on one computer at a time. If you want to use it on another computer, you need to deactivate it on the previous computer first.
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Q: How can I deactivate my serial number?
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A: You can deactivate your serial number by using the "Deactivate" button in the "License Manager" tool or the "Help" menu in Edius 7.5 software. You can also deactivate your serial number online by logging in to your account and clicking on the "Deactivate" button next to your product.
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Q: What if I lose or forget my serial number?
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A: If you lose or forget your serial number, you can retrieve it by contacting Grass Valley support and providing proof of purchase and personal information. You can also find it in your email confirmation or on the product packaging or installation disc if you bought it from the official website or authorized dealers.
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Q: What if I have more questions or problems with Edius 7.5 software or serial number?
I hope this article has helped you understand Edius 7.5 serial number free 53l and how to use it. Thank you for reading and happy editing!
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/3d Virtual Human Anatomy Studio Keygen Generator [UPDATED].md b/spaces/1gistliPinn/ChatGPT4/Examples/3d Virtual Human Anatomy Studio Keygen Generator [UPDATED].md
deleted file mode 100644
index 28bc5609739b4e276213fd1b05dc81bd8efa1915..0000000000000000000000000000000000000000
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/AnyDesk 5.1.2 Crack With Serial Code Free Download.md b/spaces/1gistliPinn/ChatGPT4/Examples/AnyDesk 5.1.2 Crack With Serial Code Free Download.md
deleted file mode 100644
index 842edb87f9c4055fb113231843a5c7ee2ba9581a..0000000000000000000000000000000000000000
--- a/spaces/1gistliPinn/ChatGPT4/Examples/AnyDesk 5.1.2 Crack With Serial Code Free Download.md
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diff --git a/spaces/1phancelerku/anime-remove-background/Bondee A Social App with Fashion Fun and Friends - Download APK for Android.md b/spaces/1phancelerku/anime-remove-background/Bondee A Social App with Fashion Fun and Friends - Download APK for Android.md
deleted file mode 100644
index 2d3d98b0b1e1696614123d93bd595121a8343918..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Bondee A Social App with Fashion Fun and Friends - Download APK for Android.md
+++ /dev/null
@@ -1,106 +0,0 @@
-
-
How to Download and Install APK Files on Your Android Device
-
If you have an Android device, you might have heard the term APK and wondered what it means. While you can use Android without ever learning the meaning of APK, studying a bit will help you understand and appreciate the platform further.
-
Let's look at what an APK file is and why it's important to Android.
What is an APK file and why would you want to use one?
-
APK stands for Android Package (sometimes Android Package Kit or Android Application Package). It's the file format that Android uses to distribute and install apps. As a result, an APK contains all the elements that an app needs to install correctly on your device.
-
An APK is an archive file, meaning that it contains multiple files, plus some metadata about them. You're probably familiar with other types of archive files, like ZIP and RAR. Generally, archive files (like ZIP) are used to combine multiple files into one, in order to make them more portable or compress them to save space.
-
When an archive is used to distribute software, it's then called a software package. As it turns out, APKs are a variant of the JAR (Java Archive) file format, since a lot of Android is built in Java. All APKs are ZIP files at their core, but they must contain additional information to properly function as an APK.
-
So all APKs are ZIPs, but not all ZIPs are APKs. If you're curious, you can crack open an APK file and see what's inside. Just use a file extraction tool like 7-Zip to open it like you would any old ZIP file. You can't do much with APKs on platforms other than Android, unless you install an Android emulator like Bluestacks.
-
APK files allow you to install apps on your Android phone. They're similar to the APPX files used to install Store apps on Windows, as well as corresponding package files on other platforms. When you open an APK on your device, it contains the instructions to install the app on your phone and provides information about the package itself to your device.
-
Normally, when you visit Google Play to download or update an app, the store automatically installs the APK for you. In this way, the Play Store also acts as a package manager—a tool for easily installing, updating, and removing software on a device.
-
However, due to Android's open nature, Google Play is not the only way to find and install APKs. It's easy to obtain an APK file from elsewhere, move it to your device, and install it manually. See how to sideload apps on Android for a full guide.
-
How to find and download APK files
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The easiest way to find and download an APK file is to use your web browser on your Android device or computer. There are many websites that offer free or paid APK files for various apps and games. However, not all of them are trustworthy or legal.
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You should only download APK files from reputable sources that verify the integrity and security of the files they host. Some examples of such sources are:
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APK Mirror: A popular site that hosts tons of verified APK files for many apps and games.
Call of Duty: Mobile VN is a mobile FPS game that is developed by Tencent and Activision, the same companies behind the original Call of Duty series. It is based on the global version of Call of Duty: Mobile, but it has some unique features and optimizations for Vietnamese players. It is published by VNG, a leading game company in Vietnam.
-
A popular FPS game developed by Tencent and Activision
-
Call of Duty: Mobile VN inherits the essence of the Call of Duty franchise, which has been loved by millions of players around the world for over a decade. It offers a variety of modes, maps, weapons, characters, and customization options that will satisfy any FPS fan. You can enjoy classic modes like Team Deathmatch, Domination, Search and Destroy, or try new ones like Gun Game, Kill Confirmed, or Rapid Fire. You can also explore iconic maps like Nuketown, Crash, Hijacked, or Crossfire, or discover new ones like Cage, Summit, or Rust. You can also unlock and use famous characters like Captain Price, Ghost, Soap, or Alex Mason, or create your own with different skins and outfits. You can also upgrade and customize your weapons with different attachments, camos, stickers, and charms.
-
A unique version for Vietnamese players by VNG
-
Call of Duty: Mobile VN is not just a copy of the global version. It is a game that is tailored for Vietnamese players by VNG, who have years of experience in publishing and operating mobile games in Vietnam. VNG has made sure that the game runs smoothly and lag-free on most devices, even low-end ones. They have also added some exclusive features and events for Vietnamese players, such as Vietnamese voice-over, local servers, seasonal rewards, tournaments, livestreams, fan pages, and customer service. They have also collaborated with famous streamers and celebrities in Vietnam to promote the game and engage with the community.
-
What are the features of Call of Duty: Mobile VN?
-
Call of Duty: Mobile VN has many features that make it stand out from other mobile FPS games. Here are some of them:
-
Stunning graphics and sound effects
-
One of the first things that you will notice when you play Call of Duty: Mobile VN is how beautiful it looks. The game has HD graphics that are sharp and realistic, especially on high-end devices. The game also has dynamic lighting and shadows, weather effects, smoke and fire effects, bullet traces, blood splatters, and more. The game also has immersive sound effects that make you feel like you are in a real battlefield. You can hear the gunshots, explosions, footsteps, reloads
Legendary FPS gameplay with various modes and maps
-
Another thing that makes Call of Duty: Mobile VN so fun and addictive is its gameplay. The game has smooth and responsive controls that are easy to learn and master. You can also customize your controls to suit your preferences and playstyle. The game has various modes and maps that cater to different tastes and skills. You can play solo or team up with your friends in multiplayer modes, or challenge yourself in ranked matches and seasonal events. You can also switch between first-person and third-person perspectives, or use different camera angles and scopes. The game has a fast-paced and action-packed gameplay that will keep you on the edge of your seat.
-
Call of Duty: Mobile VN download
-Call of Duty: Mobile VN gameplay
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-
Customizable weapons and characters
-
One of the most exciting aspects of Call of Duty: Mobile VN is its customization system. The game has a huge arsenal of weapons that you can unlock and use, from assault rifles, sniper rifles, shotguns, SMGs, LMGs, pistols, launchers, to melee weapons. You can also upgrade and customize your weapons with different attachments, camos, stickers, and charms. You can also unlock and use different characters from the Call of Duty universe, or create your own with different skins and outfits. You can also equip your characters with different perks, skills, grenades, and equipment. You can also change your loadout before each match to suit the mode and map.
-
Battle royale mode with military vehicles and special weapons
-
If you are looking for a more thrilling and immersive FPS experience, you should try the battle royale mode in Call of Duty: Mobile VN. In this mode, you can join up to 100 players in a massive map that is filled with weapons, items, vehicles, and enemies. You can choose to play solo, duo, or squad, and parachute into your preferred location. You can also choose your class before each match, such as medic, scout, ninja, defender, mechanic, or hacker. Each class has its own special skill and ability that can give you an edge in the battlefield. You can also find and use military vehicles such as helicopters, tanks, ATVs, or boats to traverse the map faster and easier. You can also find and use special weapons such as rocket launchers, flamethrowers, miniguns, or grenade launchers to deal more damage and chaos. The battle royale mode is a test of your survival skills and strategy as you have to fight against other players and the shrinking zone.
-
How to download and play Call of Duty: Mobile VN?
-
If you are interested in playing Call of Duty: Mobile VN, you will be glad to know that it is very easy to download and play. Here are the steps:
-
Available on Google Play and App Store
-
The game is available for both Android and iOS devices. You can download it for free from Google Play or App Store by searching for "Call of Duty: Mobile VN" or by scanning the QR code below:
-
-
-
-
-
-
-
-
-
-
-
Compatible with most devices
-
The game is compatible with most devices that have Android 4.3 or higher or iOS 9.0 or higher. However, for the best gaming experience, it is recommended that you have at least 2 GB of RAM and 4 GB of free storage space on your device.
-
Smooth and lag-free performance
-
The game has been optimized by VNG to run smoothly and lag-free on most devices, even low-end ones. You can adjust the graphics settings and the frame rate according to your device's capabilities. You can also choose to play on local servers to reduce the ping and latency. The game also has anti-cheat and anti-hack systems to ensure fair and balanced gameplay for everyone.
-
Why should you play Call of Duty: Mobile VN?
-
There are many reasons why you should play Call of Duty: Mobile VN, but here are some of the main ones:
-
A faithful adaptation of the Call of Duty franchise on mobile
-
If you are a fan of the Call of Duty franchise, you will love Call of Duty: Mobile VN. The game has captured the essence and the spirit of the original series, but also added some new and innovative features for mobile devices. You can relive the classic moments and the epic stories from the Call of Duty universe, or create your own with your friends and other players. You can also enjoy the authentic and realistic FPS gameplay that has made Call of Duty one of the best games in the genre.
-
A competitive and immersive FPS experience
-
If you are looking for a challenge and a thrill, you will find it in Call of Duty: Mobile VN. The game has a competitive and immersive FPS experience that will test your skills and strategy. You can compete with other players in ranked matches and seasonal events, or join clans and tournaments to win prizes and glory. You can also immerse yourself in the battle royale mode, where you have to survive against 99 other players in a massive map. You can also customize your weapons and characters to suit your playstyle and preferences.
-
A supportive and active community of players
-
If you are looking for a friendly and fun community of players, you will find it in Call of Duty: Mobile VN. The game has a supportive and active community of players who share the same passion and love for the game. You can chat with other players in the game or on social media platforms, or join fan pages and groups to get updates, tips, news, and events. You can also watch livestreams and videos from famous streamers and celebrities who play the game, or become one yourself by sharing your gameplay and highlights. You can also get help and support from VNG's customer service team, who are always ready to assist you with any issues or questions.
-
Conclusion
-
Call of Duty: Mobile VN is a game that you should not miss if you are a fan of FPS games or mobile games in general. It is a game that offers stunning graphics, legendary gameplay, customizable weapons and characters, battle royale mode, smooth performance, faithful adaptation, competitive experience, and supportive community. It is a game that will keep you entertained and engaged for hours and hours. So what are you waiting for? Download Call of Duty: Mobile VN today and join the ultimate FPS experience on mobile!
-
FAQs
-
Here are some frequently asked questions about Call of Duty: Mobile VN:
-
Q: Is Call of Duty: Mobile VN free to play?
-
A: Yes, Call of Duty: Mobile VN is free to play. You can download it from Google Play or App Store without paying anything. However, the game also has some optional in-app purchases that can enhance your gaming experience, such as weapon skins, character outfits, battle passes, crates, cod points, etc.
-
Q: Is Call of Duty: Mobile VN different from Call of Duty: Mobile?
-
A: Yes, Call of Duty: Mobile VN is different from Call of Duty: Mobile in some ways. Call of Duty: Mobile VN is a version that is exclusively made for Vietnamese players by VNG. It has some unique features and optimizations that are not available in the global version, such as Vietnamese voice-over, local servers, seasonal rewards, tournaments, livestreams, fan pages, customer service, etc.
-
Q: How can I play with my friends in Call of Duty: Mobile VN?
-
A: You can play with your friends in Call of Duty: Mobile VN by adding them as friends in the game. You can do this by tapping on the friends icon on the top right corner of the main screen, then tapping on the add friends icon on the bottom right corner. You can then search for your friends by their username or ID number, or scan their QR code. Once you have added them as friends, you can invite them to join your lobby or join theirs by tapping on their name on the friends list.
-
Q: How can I get more weapons and characters in Call of Duty: Mobile VN?
-
A: You can get more weapons and characters in Call of Duty: Mobile VN by playing the game regularly and completing missions and challenges. You can also get more weapons and characters by opening crates and lucky draws that are available in the game. You can also get more weapons and characters by buying them with cod points or real money in the game's store.
-
Q: How can I improve my skills and rank in Call of Duty: Mobile VN?
-
A: You can improve your skills and rank in Call of Duty: Mobile VN by practicing and learning from other players. You can watch tutorials and tips videos on YouTube or other platforms, or watch livestreams and replays of pro players and streamers. You can also join clans and groups that can help you improve your teamwork and strategy. You can also play ranked matches and seasonal events that can challenge you and reward you with exclusive items and titles.
-
Q: How can I contact VNG's customer service team if I have any issues or questions?
-
A: You can contact VNG's customer service team if you have any issues or questions by using the in-game feedback system. You can access it by tapping on the settings icon on the top right corner of the main screen, then tapping on the feedback icon on the bottom left corner. You can then choose the type of your issue or question, such as account, payment, bug, suggestion, etc., and fill in the details and attach screenshots if necessary. You can also contact VNG's customer service team by sending an email to codmvn@vng.com.vn, or by calling their hotline at 1900 561 558.
197e85843d
-
-
\ No newline at end of file
diff --git a/spaces/801artistry/RVC801/mdx_processing_script.py b/spaces/801artistry/RVC801/mdx_processing_script.py
deleted file mode 100644
index 05616843300aacf46c98ce06f017ba1d0794f313..0000000000000000000000000000000000000000
--- a/spaces/801artistry/RVC801/mdx_processing_script.py
+++ /dev/null
@@ -1,146 +0,0 @@
-import gc
-import requests
-import subprocess
-import logging
-import sys
-from bs4 import BeautifulSoup
-import torch, pdb, os, warnings, librosa
-import soundfile as sf
-from tqdm import tqdm
-import numpy as np
-import torch
-now_dir = os.getcwd()
-sys.path.append(now_dir)
-import mdx
-branch = "https://github.com/NaJeongMo/Colab-for-MDX_B"
-
-model_params = "https://raw.githubusercontent.com/TRvlvr/application_data/main/mdx_model_data/model_data.json"
-_Models = "https://github.com/TRvlvr/model_repo/releases/download/all_public_uvr_models/"
-# _models = "https://pastebin.com/raw/jBzYB8vz"
-_models = "https://raw.githubusercontent.com/TRvlvr/application_data/main/filelists/download_checks.json"
-stem_naming = "https://pastebin.com/raw/mpH4hRcF"
-
-file_folder = "Colab-for-MDX_B"
-model_ids = requests.get(_models).json()
-model_ids = model_ids["mdx_download_list"].values()
-#print(model_ids)
-model_params = requests.get(model_params).json()
-stem_naming = requests.get(stem_naming).json()
-
-os.makedirs("tmp_models", exist_ok=True)
-
-warnings.filterwarnings("ignore")
-cpu = torch.device("cpu")
-if torch.cuda.is_available():
- device = torch.device("cuda:0")
-elif torch.backends.mps.is_available():
- device = torch.device("mps")
-else:
- device = torch.device("cpu")
-
-
-def get_model_list():
- return model_ids
-
-def id_to_ptm(mkey):
- if mkey in model_ids:
- mpath = f"{now_dir}/tmp_models/{mkey}"
- if not os.path.exists(f'{now_dir}/tmp_models/{mkey}'):
- print('Downloading model...',end=' ')
- subprocess.run(
- ["wget", _Models+mkey, "-O", mpath]
- )
- print(f'saved to {mpath}')
- # get_ipython().system(f'gdown {model_id} -O /content/tmp_models/{mkey}')
- return mpath
- else:
- return mpath
- else:
- mpath = f'models/{mkey}'
- return mpath
-
-def prepare_mdx(onnx,custom_param=False, dim_f=None, dim_t=None, n_fft=None, stem_name=None, compensation=None):
- device = torch.device('cuda:0') if torch.cuda.is_available() else torch.device('cpu')
- if custom_param:
- assert not (dim_f is None or dim_t is None or n_fft is None or compensation is None), 'Custom parameter selected, but incomplete parameters are provided.'
- mdx_model = mdx.MDX_Model(
- device,
- dim_f = dim_f,
- dim_t = dim_t,
- n_fft = n_fft,
- stem_name=stem_name,
- compensation=compensation
- )
- else:
- model_hash = mdx.MDX.get_hash(onnx)
- if model_hash in model_params:
- mp = model_params.get(model_hash)
- mdx_model = mdx.MDX_Model(
- device,
- dim_f = mp["mdx_dim_f_set"],
- dim_t = 2**mp["mdx_dim_t_set"],
- n_fft = mp["mdx_n_fft_scale_set"],
- stem_name=mp["primary_stem"],
- compensation=compensation if not custom_param and compensation is not None else mp["compensate"]
- )
- return mdx_model
-
-def run_mdx(onnx, mdx_model,filename, output_format='wav',diff=False,suffix=None,diff_suffix=None, denoise=False, m_threads=2):
- mdx_sess = mdx.MDX(onnx,mdx_model)
- print(f"Processing: {filename}")
- if filename.lower().endswith('.wav'):
- wave, sr = librosa.load(filename, mono=False, sr=44100)
- else:
- temp_wav = 'temp_audio.wav'
- subprocess.run(['ffmpeg', '-i', filename, '-ar', '44100', '-ac', '2', temp_wav]) # Convert to WAV format
- wave, sr = librosa.load(temp_wav, mono=False, sr=44100)
- os.remove(temp_wav)
-
- #wave, sr = librosa.load(filename,mono=False, sr=44100)
- # normalizing input wave gives better output
- peak = max(np.max(wave), abs(np.min(wave)))
- wave /= peak
- if denoise:
- wave_processed = -(mdx_sess.process_wave(-wave, m_threads)) + (mdx_sess.process_wave(wave, m_threads))
- wave_processed *= 0.5
- else:
- wave_processed = mdx_sess.process_wave(wave, m_threads)
- # return to previous peak
- wave_processed *= peak
-
- stem_name = mdx_model.stem_name if suffix is None else suffix # use suffix if provided
- save_path = os.path.basename(os.path.splitext(filename)[0])
- #vocals_save_path = os.path.join(vocals_folder, f"{save_path}_{stem_name}.{output_format}")
- #instrumental_save_path = os.path.join(instrumental_folder, f"{save_path}_{stem_name}.{output_format}")
- save_path = f"{os.path.basename(os.path.splitext(filename)[0])}_{stem_name}.{output_format}"
- save_path = os.path.join(
- 'audios',
- save_path
- )
- sf.write(
- save_path,
- wave_processed.T,
- sr
- )
-
- print(f'done, saved to: {save_path}')
-
- if diff:
- diff_stem_name = stem_naming.get(stem_name) if diff_suffix is None else diff_suffix # use suffix if provided
- stem_name = f"{stem_name}_diff" if diff_stem_name is None else diff_stem_name
- save_path = f"{os.path.basename(os.path.splitext(filename)[0])}_{stem_name}.{output_format}"
- save_path = os.path.join(
- 'audio-others',
- save_path
- )
- sf.write(
- save_path,
- (-wave_processed.T*mdx_model.compensation)+wave.T,
- sr
- )
- print(f'invert done, saved to: {save_path}')
- del mdx_sess, wave_processed, wave
- gc.collect()
-
-if __name__ == "__main__":
- print()
\ No newline at end of file
diff --git a/spaces/AI-Hobbyist/Hoyo-RVC/docs/README.en.md b/spaces/AI-Hobbyist/Hoyo-RVC/docs/README.en.md
deleted file mode 100644
index 211571d58040607c2d9f9a514c97bcbc05507c9f..0000000000000000000000000000000000000000
--- a/spaces/AI-Hobbyist/Hoyo-RVC/docs/README.en.md
+++ /dev/null
@@ -1,110 +0,0 @@
-
-
-
Retrieval-based-Voice-Conversion-WebUI
-An easy-to-use Voice Conversion framework based on VITS.
-
-------
-[**Changelog**](https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/Changelog_CN.md) | [**FAQ (Frequently Asked Questions)**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/FAQ-(Frequently-Asked-Questions))
-
-[**English**](./README.en.md) | [**中文简体**](../README.md) | [**日本語**](./README.ja.md) | [**한국어**](./README.ko.md) ([**韓國語**](./README.ko.han.md))
-
-
-Check our [Demo Video](https://www.bilibili.com/video/BV1pm4y1z7Gm/) here!
-
-Realtime Voice Conversion Software using RVC : [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
-
-> A online demo using RVC that convert Vocal to Acoustic Guitar audio：https://huggingface.co/spaces/lj1995/vocal2guitar
-
-> Vocal2Guitar demo video：https://www.bilibili.com/video/BV19W4y1D7tT/
-
-> The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset.
-
-> High quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement.
-
-## Summary
-This repository has the following features:
-+ Reduce tone leakage by replacing source feature to training-set feature using top1 retrieval;
-+ Easy and fast training, even on relatively poor graphics cards;
-+ Training with a small amount of data also obtains relatively good results (>=10min low noise speech recommended);
-+ Supporting model fusion to change timbres (using ckpt processing tab->ckpt merge);
-+ Easy-to-use Webui interface;
-+ Use the UVR5 model to quickly separate vocals and instruments.
-## Preparing the environment
-We recommend you install the dependencies through poetry.
-
-The following commands need to be executed in the environment of Python version 3.8 or higher:
-```bash
-# Install PyTorch-related core dependencies, skip if installed
-# Reference: https://pytorch.org/get-started/locally/
-pip install torch torchvision torchaudio
-
-#For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/issues/21
-#pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
-
-# Install the Poetry dependency management tool, skip if installed
-# Reference: https://python-poetry.org/docs/#installation
-curl -sSL https://install.python-poetry.org | python3 -
-
-# Install the project dependencies
-poetry install
-```
-You can also use pip to install the dependencies
-
-```bash
-pip install -r requirements.txt
-```
-
-## Preparation of other Pre-models
-RVC requires other pre-models to infer and train.
-
-You need to download them from our [Huggingface space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/).
-
-Here's a list of Pre-models and other files that RVC needs:
-```bash
-hubert_base.pt
-
-./pretrained
-
-./uvr5_weights
-
-If you want to test the v2 version model (the v2 version model has changed the input from the 256 dimensional feature of 9-layer Hubert+final_proj to the 768 dimensional feature of 12-layer Hubert, and has added 3 period discriminators), you will need to download additional features
-
-./pretrained_v2
-
-#If you are using Windows, you may also need this dictionary, skip if FFmpeg is installed
-ffmpeg.exe
-```
-Then use this command to start Webui:
-```bash
-python infer-web.py
-```
-If you are using Windows, you can download and extract `RVC-beta.7z` to use RVC directly and use `go-web.bat` to start Webui.
-
-There's also a tutorial on RVC in Chinese and you can check it out if needed.
-
-## Credits
-+ [ContentVec](https://github.com/auspicious3000/contentvec/)
-+ [VITS](https://github.com/jaywalnut310/vits)
-+ [HIFIGAN](https://github.com/jik876/hifi-gan)
-+ [Gradio](https://github.com/gradio-app/gradio)
-+ [FFmpeg](https://github.com/FFmpeg/FFmpeg)
-+ [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui)
-+ [audio-slicer](https://github.com/openvpi/audio-slicer)
-## Thanks to all contributors for their efforts
-
-
-
-
-
diff --git a/spaces/AIConsultant/MusicGen/tests/models/test_multibanddiffusion.py b/spaces/AIConsultant/MusicGen/tests/models/test_multibanddiffusion.py
deleted file mode 100644
index 2702a3cb5fe402bf96911dbc992d2749cb18a4c0..0000000000000000000000000000000000000000
--- a/spaces/AIConsultant/MusicGen/tests/models/test_multibanddiffusion.py
+++ /dev/null
@@ -1,53 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-import random
-
-import numpy as np
-import torch
-from audiocraft.models.multibanddiffusion import MultiBandDiffusion, DiffusionProcess
-from audiocraft.models import EncodecModel, DiffusionUnet
-from audiocraft.modules import SEANetEncoder, SEANetDecoder
-from audiocraft.modules.diffusion_schedule import NoiseSchedule
-from audiocraft.quantization import DummyQuantizer
-
-
-class TestMBD:
-
- def _create_mbd(self,
- sample_rate: int,
- channels: int,
- n_filters: int = 3,
- n_residual_layers: int = 1,
- ratios: list = [5, 4, 3, 2],
- num_steps: int = 1000,
- codec_dim: int = 128,
- **kwargs):
- frame_rate = np.prod(ratios)
- encoder = SEANetEncoder(channels=channels, dimension=codec_dim, n_filters=n_filters,
- n_residual_layers=n_residual_layers, ratios=ratios)
- decoder = SEANetDecoder(channels=channels, dimension=codec_dim, n_filters=n_filters,
- n_residual_layers=n_residual_layers, ratios=ratios)
- quantizer = DummyQuantizer()
- compression_model = EncodecModel(encoder, decoder, quantizer, frame_rate=frame_rate,
- sample_rate=sample_rate, channels=channels, **kwargs)
- diffusion_model = DiffusionUnet(chin=channels, num_steps=num_steps, codec_dim=codec_dim)
- schedule = NoiseSchedule(device='cpu', num_steps=num_steps)
- DP = DiffusionProcess(model=diffusion_model, noise_schedule=schedule)
- mbd = MultiBandDiffusion(DPs=[DP], codec_model=compression_model)
- return mbd
-
- def test_model(self):
- random.seed(1234)
- sample_rate = 24_000
- channels = 1
- codec_dim = 128
- mbd = self._create_mbd(sample_rate=sample_rate, channels=channels, codec_dim=codec_dim)
- for _ in range(10):
- length = random.randrange(1, 10_000)
- x = torch.randn(2, channels, length)
- res = mbd.regenerate(x, sample_rate)
- assert res.shape == x.shape
diff --git a/spaces/AIGText/GlyphControl/ldm/util.py b/spaces/AIGText/GlyphControl/ldm/util.py
deleted file mode 100644
index 2abc0791d7e60d3fbc05ff006385abfc6d534fea..0000000000000000000000000000000000000000
--- a/spaces/AIGText/GlyphControl/ldm/util.py
+++ /dev/null
@@ -1,203 +0,0 @@
-import importlib
-
-import torch
-from torch import optim
-import numpy as np
-
-from inspect import isfunction
-from PIL import Image, ImageDraw, ImageFont
-
-
-def log_txt_as_img(wh, xc, size=10):
- # wh a tuple of (width, height)
- # xc a list of captions to plot
- b = len(xc)
- txts = list()
- for bi in range(b):
- txt = Image.new("RGB", wh, color="white")
- draw = ImageDraw.Draw(txt)
- font = ImageFont.truetype('data/DejaVuSans.ttf', size=size)
- nc = int(40 * (wh[0] / 256))
- lines = "\n".join(xc[bi][start:start + nc] for start in range(0, len(xc[bi]), nc))
-
- try:
- draw.text((0, 0), lines, fill="black", font=font)
- except UnicodeEncodeError:
- print("Cant encode string for logging. Skipping.")
-
- txt = np.array(txt).transpose(2, 0, 1) / 127.5 - 1.0
- txts.append(txt)
- txts = np.stack(txts)
- txts = torch.tensor(txts)
- return txts
-
-
-def ismap(x):
- if not isinstance(x, torch.Tensor):
- return False
- return (len(x.shape) == 4) and (x.shape[1] > 3)
-
-
-def isimage(x):
- if not isinstance(x,torch.Tensor):
- return False
- return (len(x.shape) == 4) and (x.shape[1] == 3 or x.shape[1] == 1)
-
-
-def exists(x):
- return x is not None
-
-
-def default(val, d):
- if exists(val):
- return val
- return d() if isfunction(d) else d
-
-
-def mean_flat(tensor):
- """
- https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/nn.py#L86
- Take the mean over all non-batch dimensions.
- """
- return tensor.mean(dim=list(range(1, len(tensor.shape))))
-
-
-def count_params(model, verbose=False):
- total_params = sum(p.numel() for p in model.parameters())
- if verbose:
- print(f"{model.__class__.__name__} has {total_params*1.e-6:.2f} M params.")
- return total_params
-
-
-def instantiate_from_config(config):
- if not "target" in config:
- if config == '__is_first_stage__':
- return None
- elif config == "__is_unconditional__":
- return None
- raise KeyError("Expected key `target` to instantiate.")
- return get_obj_from_str(config["target"])(**config.get("params", dict()))
-
-
-def get_obj_from_str(string, reload=False):
- module, cls = string.rsplit(".", 1)
- if reload:
- module_imp = importlib.import_module(module)
- importlib.reload(module_imp)
- return getattr(importlib.import_module(module, package=None), cls)
-
-
-class AdamWwithEMAandWings(optim.Optimizer):
- # credit to https://gist.github.com/crowsonkb/65f7265353f403714fce3b2595e0b298
- def __init__(self, params, lr=1.e-3, betas=(0.9, 0.999), eps=1.e-8, # TODO: check hyperparameters before using
- weight_decay=1.e-2, amsgrad=False, ema_decay=0.9999, # ema decay to match previous code
- ema_power=1., param_names=()):
- """AdamW that saves EMA versions of the parameters."""
- if not 0.0 <= lr:
- raise ValueError("Invalid learning rate: {}".format(lr))
- if not 0.0 <= eps:
- raise ValueError("Invalid epsilon value: {}".format(eps))
- if not 0.0 <= betas[0] < 1.0:
- raise ValueError("Invalid beta parameter at index 0: {}".format(betas[0]))
- if not 0.0 <= betas[1] < 1.0:
- raise ValueError("Invalid beta parameter at index 1: {}".format(betas[1]))
- if not 0.0 <= weight_decay:
- raise ValueError("Invalid weight_decay value: {}".format(weight_decay))
- if not 0.0 <= ema_decay <= 1.0:
- raise ValueError("Invalid ema_decay value: {}".format(ema_decay))
- defaults = dict(lr=lr, betas=betas, eps=eps,
- weight_decay=weight_decay, amsgrad=amsgrad, ema_decay=ema_decay,
- ema_power=ema_power, param_names=param_names)
- super().__init__(params, defaults)
-
- def __setstate__(self, state):
- super().__setstate__(state)
- for group in self.param_groups:
- group.setdefault('amsgrad', False)
-
- @torch.no_grad()
- def step(self, closure=None):
- """Performs a single optimization step.
- Args:
- closure (callable, optional): A closure that reevaluates the model
- and returns the loss.
- """
- loss = None
- if closure is not None:
- with torch.enable_grad():
- loss = closure()
-
- for group in self.param_groups:
- params_with_grad = []
- grads = []
- exp_avgs = []
- exp_avg_sqs = []
- ema_params_with_grad = []
- state_sums = []
- max_exp_avg_sqs = []
- state_steps = []
- amsgrad = group['amsgrad']
- beta1, beta2 = group['betas']
- ema_decay = group['ema_decay']
- ema_power = group['ema_power']
-
- for p in group['params']:
- if p.grad is None:
- continue
- params_with_grad.append(p)
- if p.grad.is_sparse:
- raise RuntimeError('AdamW does not support sparse gradients')
- grads.append(p.grad)
-
- state = self.state[p]
-
- # State initialization
- if len(state) == 0:
- state['step'] = 0
- # Exponential moving average of gradient values
- state['exp_avg'] = torch.zeros_like(p, memory_format=torch.preserve_format)
- # Exponential moving average of squared gradient values
- state['exp_avg_sq'] = torch.zeros_like(p, memory_format=torch.preserve_format)
- if amsgrad:
- # Maintains max of all exp. moving avg. of sq. grad. values
- state['max_exp_avg_sq'] = torch.zeros_like(p, memory_format=torch.preserve_format)
- # Exponential moving average of parameter values
- state['param_exp_avg'] = p.detach().float().clone()
-
- exp_avgs.append(state['exp_avg'])
- exp_avg_sqs.append(state['exp_avg_sq'])
- ema_params_with_grad.append(state['param_exp_avg'])
-
- if amsgrad:
- max_exp_avg_sqs.append(state['max_exp_avg_sq'])
-
- # update the steps for each param group update
- state['step'] += 1
- # record the step after step update
- state_steps.append(state['step'])
-
- optim._functional.adamw(params_with_grad,
- grads,
- exp_avgs,
- exp_avg_sqs,
- max_exp_avg_sqs,
- state_steps,
- amsgrad=amsgrad,
- beta1=beta1,
- beta2=beta2,
- lr=group['lr'],
- weight_decay=group['weight_decay'],
- eps=group['eps'],
- maximize=False)
-
- cur_ema_decay = min(ema_decay, 1 - state['step'] ** -ema_power)
- for param, ema_param in zip(params_with_grad, ema_params_with_grad):
- ema_param.mul_(cur_ema_decay).add_(param.float(), alpha=1 - cur_ema_decay)
-
- return loss
-
-def islistortuple(item):
- if isinstance(item, list) or isinstance(item, tuple):
- return True
- else:
- return False
\ No newline at end of file
diff --git a/spaces/AILab-CVC/EvalCrafter/README.md b/spaces/AILab-CVC/EvalCrafter/README.md
deleted file mode 100644
index 02a3a516af49e9dc413a23442df4e5e577c7f726..0000000000000000000000000000000000000000
--- a/spaces/AILab-CVC/EvalCrafter/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: EvalCrafter
-emoji: ⚡
-colorFrom: yellow
-colorTo: gray
-sdk: gradio
-sdk_version: 3.27.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/AISuperheroes/07GR-NLP-Seq2Seq-AutoQA/app.py b/spaces/AISuperheroes/07GR-NLP-Seq2Seq-AutoQA/app.py
deleted file mode 100644
index c1cd92499cf1c7d2a91b4dc226bf2d558ff67661..0000000000000000000000000000000000000000
--- a/spaces/AISuperheroes/07GR-NLP-Seq2Seq-AutoQA/app.py
+++ /dev/null
@@ -1,51 +0,0 @@
-import gradio as gr
-from qasrl_model_pipeline import QASRL_Pipeline
-
-models = ["kleinay/qanom-seq2seq-model-baseline",
- "kleinay/qanom-seq2seq-model-joint"]
-pipelines = {model: QASRL_Pipeline(model) for model in models}
-
-
-description = f"""Using Seq2Seq T5 model which takes a sequence of items and outputs another sequence this model generates Questions and Answers (QA) with focus on Semantic Role Labeling (SRL)"""
-title="Seq2Seq T5 Questions and Answers (QA) with Semantic Role Labeling (SRL)"
-examples = [[models[0], "In March and April the patient
had two falls. One was related to asthma, heart palpitations. The second was due to syncope and post covid vaccination dizziness during exercise. The patient is now getting an EKG. Former EKG had shown that there was a bundle branch block. Patient had some uncontrolled immune system reactions like anaphylaxis and shortness of breath.", True, "fall"],
- [models[1], "In March and April the patient had two falls. One was related to asthma, heart palpitations. The second was due to syncope and post covid vaccination dizziness during exercise. The patient is now getting an EKG. Former EKG had shown that there was a bundle branch block. Patient had some uncontrolled immune system reactions
like anaphylaxis and shortness of breath.", True, "reactions"],
- [models[0], "In March and April the patient had two falls. One was related
to asthma, heart palpitations. The second was due to syncope and post covid vaccination dizziness during exercise. The patient is now getting an EKG. Former EKG had shown that there was a bundle branch block. Patient had some uncontrolled immune system reactions like anaphylaxis and shortness of breath.", True, "relate"],
- [models[1], "In March and April the patient
had two falls. One was related to asthma, heart palpitations. The second was due to syncope and post covid vaccination dizziness during exercise. The patient is now getting an EKG. Former EKG had shown that there was a bundle branch block. Patient had some uncontrolled immune system reactions like anaphylaxis and shortness of breath.", False, "fall"]]
-
-input_sent_box_label = "Insert sentence here. Mark the predicate by adding the token '
' before it."
-verb_form_inp_placeholder = "e.g. 'decide' for the nominalization 'decision', 'teach' for 'teacher', etc."
-links = """
-
-
\ No newline at end of file
diff --git a/spaces/AIxPha/QSign/README.md b/spaces/AIxPha/QSign/README.md
deleted file mode 100644
index 0a4048e9268771354f341c1a96558c065e12a130..0000000000000000000000000000000000000000
--- a/spaces/AIxPha/QSign/README.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: QSign
-emoji: 💻
-colorFrom: gray
-colorTo: gray
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Ababababababbababa/Sha3bor_Aragpt2_Base/app.py b/spaces/Ababababababbababa/Sha3bor_Aragpt2_Base/app.py
deleted file mode 100644
index a7f56b4a94d81756a607d25f6b30fca02145029c..0000000000000000000000000000000000000000
--- a/spaces/Ababababababbababa/Sha3bor_Aragpt2_Base/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/aliosm/sha3bor-generator-aragpt2-base").launch()
\ No newline at end of file
diff --git a/spaces/Abhiboken12/travelling_ai/README.md b/spaces/Abhiboken12/travelling_ai/README.md
deleted file mode 100644
index 6c7fe423395570ba32e85bd1815bd0e55f09b1d6..0000000000000000000000000000000000000000
--- a/spaces/Abhiboken12/travelling_ai/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Travelling Ai
-emoji: 🌍
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 3.45.2
-app_file: app.py
-pinned: false
-license: bigscience-openrail-m
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Abhilashvj/planogram-compliance/Dockerfile b/spaces/Abhilashvj/planogram-compliance/Dockerfile
deleted file mode 100644
index bd746c574db13ab7eae12fcf6a9e3525b30682d3..0000000000000000000000000000000000000000
--- a/spaces/Abhilashvj/planogram-compliance/Dockerfile
+++ /dev/null
@@ -1,60 +0,0 @@
-# # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
-
-# # Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
-# FROM nvcr.io/nvidia/pytorch:21.05-py3
-
-# # Install linux packages
-# RUN apt update && apt install -y zip htop screen libgl1-mesa-glx
-
-# # Install python dependencies
-# COPY requirements.txt .
-# RUN python -m pip install --upgrade pip
-# RUN pip uninstall -y nvidia-tensorboard nvidia-tensorboard-plugin-dlprof
-# RUN pip install --no-cache -r requirements.txt coremltools onnx gsutil notebook
-# RUN pip install --no-cache -U torch torchvision numpy
-# # RUN pip install --no-cache torch==1.9.0+cu111 torchvision==0.10.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html
-
-# # Create working directory
-# RUN mkdir -p /usr/src/app
-# WORKDIR /usr/src/app
-
-# # Copy contents
-# COPY . /usr/src/app
-
-# # Set environment variables
-# ENV HOME=/usr/src/app
-
-
-# Usage Examples -------------------------------------------------------------------------------------------------------
-
-# Build and Push
-# t=ultralytics/yolov5:latest && sudo docker build -t $t . && sudo docker push $t
-
-# Pull and Run
-# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all $t
-
-# Pull and Run with local directory access
-# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/datasets:/usr/src/datasets $t
-
-# Kill all
-# sudo docker kill $(sudo docker ps -q)
-
-# Kill all image-based
-# sudo docker kill $(sudo docker ps -qa --filter ancestor=ultralytics/yolov5:latest)
-
-# Bash into running container
-# sudo docker exec -it 5a9b5863d93d bash
-
-# Bash into stopped container
-# id=$(sudo docker ps -qa) && sudo docker start $id && sudo docker exec -it $id bash
-
-# Clean up
-# docker system prune -a --volumes
-FROM python:3.9
-EXPOSE 8501
-WORKDIR /app
-COPY requirements.txt ./requirements.txt
-RUN pip3 install -r requirements.txt
-COPY . .
-# CMD streamlit run app.py
-CMD streamlit run --server.port $PORT app.py
\ No newline at end of file
diff --git a/spaces/AlekseyKorshuk/instagram-filter-removal/modeling/benchmark.py b/spaces/AlekseyKorshuk/instagram-filter-removal/modeling/benchmark.py
deleted file mode 100644
index 406687e44def60bd8e4be35cdd07160e242fe99d..0000000000000000000000000000000000000000
--- a/spaces/AlekseyKorshuk/instagram-filter-removal/modeling/benchmark.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import torch
-from torch import nn
-
-from modeling.base import BaseNetwork
-from modeling.ifrnet import Flatten
-from modules.blocks import DestyleResBlock, Destyler, ResBlock
-
-
-class UNet(BaseNetwork):
- def __init__(self, base_n_channels):
- super(UNet, self).__init__()
-
- self.ds_res1 = ResBlock(channels_in=3, channels_out=base_n_channels, kernel_size=5, stride=1, padding=2)
- self.ds_res2 = ResBlock(channels_in=base_n_channels, channels_out=base_n_channels * 2, kernel_size=3, stride=2, padding=1)
- self.ds_res3 = ResBlock(channels_in=base_n_channels * 2, channels_out=base_n_channels * 2, kernel_size=3, stride=1, padding=1)
- self.ds_res4 = ResBlock(channels_in=base_n_channels * 2, channels_out=base_n_channels * 4, kernel_size=3, stride=2, padding=1)
- self.ds_res5 = ResBlock(channels_in=base_n_channels * 4, channels_out=base_n_channels * 4, kernel_size=3, stride=1, padding=1)
- self.ds_res6 = ResBlock(channels_in=base_n_channels * 4, channels_out=base_n_channels * 8, kernel_size=3, stride=2, padding=1)
-
- self.upsample = nn.UpsamplingNearest2d(scale_factor=2.0)
-
- self.res1 = ResBlock(channels_in=base_n_channels * 8, channels_out=base_n_channels * 4, kernel_size=3, stride=1, padding=1)
- self.res2 = ResBlock(channels_in=base_n_channels * 4, channels_out=base_n_channels * 4, kernel_size=3, stride=1, padding=1)
- self.res3 = ResBlock(channels_in=base_n_channels * 4, channels_out=base_n_channels * 2, kernel_size=3, stride=1, padding=1)
- self.res4 = ResBlock(channels_in=base_n_channels * 2, channels_out=base_n_channels * 2, kernel_size=3, stride=1, padding=1)
- self.res5 = ResBlock(channels_in=base_n_channels * 2, channels_out=base_n_channels, kernel_size=3, stride=1, padding=1)
-
- self.conv1 = nn.Conv2d(base_n_channels, 3, kernel_size=3, stride=1, padding=1)
-
- self.init_weights(init_type="normal", gain=0.02)
-
- def forward(self, x):
- out = self.ds_res1(x)
- out = self.ds_res2(out)
- out = self.ds_res3(out)
- out = self.ds_res4(out)
- out = self.ds_res5(out)
- aux = self.ds_res6(out)
-
- out = self.upsample(aux)
- out = self.res1(out)
- out = self.res2(out)
- out = self.upsample(out)
- out = self.res3(out)
- out = self.res4(out)
- out = self.upsample(out)
- out = self.res5(out)
- out = self.conv1(out)
-
- return out, aux
-
-
-if __name__ == '__main__':
- import torchvision
- x = torch.rand((2, 3, 256, 256)).cuda()
- unet = UNet(32, 32).cuda()
- vgg16 = torchvision.models.vgg16(pretrained=True).features.eval().cuda()
- with torch.no_grad():
- vgg_feat = vgg16(x)
- out = unet(x, vgg_feat)
-
- print(out.size())
diff --git a/spaces/Alinadi98/movie_recommendation_system/app.py b/spaces/Alinadi98/movie_recommendation_system/app.py
deleted file mode 100644
index aafb24e509ba256d46aebf1febfc662e1a84e06c..0000000000000000000000000000000000000000
--- a/spaces/Alinadi98/movie_recommendation_system/app.py
+++ /dev/null
@@ -1,216 +0,0 @@
-#!/usr/bin/env python
-# coding: utf-8
-
-# ## I create content base recommendation system for movies
-#
-#
-
-# ### Import our necessary library
-
-# In[1]:
-
-
-import numpy as np
-import pandas as pd
-import json
-import difflib
-from sklearn.feature_extraction.text import TfidfVectorizer
-from sklearn.metrics.pairwise import cosine_similarity
-import streamlit as st
-
-
-# ### Load our data
-
-# In[65]:
-
-
-movies_data=pd.read_csv('m.csv')
-movies_data.head(3)
-
-
-# ### Select our features
-
-# In[3]:
-
-
-selected_features = ['genres','keywords','tagline','cast','director']
-print(selected_features)
-
-
-# ### Preprocessing data
-
-# In[4]:
-
-
-for feature in selected_features:
- movies_data[feature] = movies_data[feature].fillna('')
-
-
-# In[5]:
-
-
-combined_features = movies_data['genres']+' '+movies_data['keywords']+' '+movies_data['tagline']+' '+movies_data['cast']+' '+movies_data['director']
-
-
-# ### Convert text to numerical vector
-
-# In[6]:
-
-
-vectorizer = TfidfVectorizer()
-
-
-# In[7]:
-
-
-feature_vectors = vectorizer.fit_transform(combined_features)
-
-
-# In[8]:
-
-
-print(feature_vectors )
-
-
-# ### Calculate cosine_similarity between all vectors
-
-# In[9]:
-
-
-similarity = cosine_similarity(feature_vectors)
-
-
-# In[10]:
-
-
-similarity = cosine_similarity(feature_vectors)
-
-
-# ### Run a function to recommend movies
-# #### The get_close_matches() function returns a list of close matched strings that satisfy the cutoff.
-
-# In[44]:
-
-
-list_of_all_titles = movies_data['title'].tolist()
-
-def get_recommendations(movie_name):
- find_close_match = difflib.get_close_matches(movie_name, list_of_all_titles)
- close_match = find_close_match[0]
- index_of_the_movie = movies_data[movies_data.title == close_match]['index'].values[0]
- sim_scores = list(enumerate(similarity[index_of_the_movie]))
- sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True)
- sim_scores = sim_scores[:70]
- movie_indices = [i[0] for i in sim_scores]
- a = set(movies_data[['title']].iloc[movie_indices]['title'])
- return a
-
-def get_recommendations2(movie_name):
- find_close_match = difflib.get_close_matches(movie_name, list_of_all_titles)
- close_match = find_close_match[0]
- index_of_the_movie = movies_data[movies_data.title == close_match]['index'].values[0]
- sim_scores = list(enumerate(similarity[index_of_the_movie]))
- sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True)
- sim_scores = sim_scores[:70]
- movie_indices = [i[0] for i in sim_scores]
- a = set(movies_data[['title']].iloc[movie_indices]['title'])
- return a
-
-
-def get_recommendations_intersection(movie_name1, movie_name2):
- rec1 = get_recommendations(movie_name1)
- rec2 = get_recommendations2(movie_name2)
- r_final= pd.DataFrame({'title':list(rec1.intersection(rec2))})
- final_suggestion=movies_data[movies_data['title'].isin(r_final['title'].tolist())].drop(['index','budget','homepage','id',
- 'keywords',
- 'original_language',
- 'overview',
- 'popularity',
- 'production_companies',
- 'release_date',
- 'revenue',
- 'runtime','production_countries','original_title',
- 'spoken_languages',
- 'status',
- 'tagline',
- 'vote_average',
- 'vote_count',
- 'crew'],1).reset_index(drop=True)
- if len(final_suggestion)==0:
- print('sorry, you should select two similar movie')
- else:
- return final_suggestion
-
-
-# In[45]:
-
-
-get_recommendations_intersection('inception','interstaller')
-
-
-# # use streamlit library to creat web app
-#
-
-# In[ ]:
-
-
-import streamlit as st
-import requests
-from streamlit_lottie import st_lottie
-
-
-# In[14]:
-
-
-st.subheader('Hi Im Ali Nadi Khorasgani' )
-st.title('This is a movie recommendation system Web App')
-
-
-# In[15]:
-
-
-def load_lottieurl(url):
- r=requests.get(url)
- if r.status_code !=200:
- return None
- return r.json()
-lottie_coding= load_lottieurl('https://assets5.lottiefiles.com/packages/lf20_khzniaya.json')
-st_lottie(lottie_coding,height=300,key='coding')
-
-
-# In[ ]:
-
-
-
-
-
-# In[16]:
-
-
-st.image('abcd.jpeg')
-
-st.markdown("---")
-
-
-
-
-
-# In[17]:
-
-
-movies_list = movies_data['title'].values
-
-selected_movie1 = st.selectbox( " select your first favorite movie", movies_list,key=1 )
-selected_movie2 = st.selectbox( "select your first favorite movie", movies_list,key=2 )
-st.write('we suggest you these movies ')
-if st.button('Show Recommendation'):
- recommended_movie_names = get_recommendations_intersection(selected_movie1,selected_movie2)
- st.write(recommended_movie_names)
-
-
-
-st.markdown("---")
-
-
-st.markdown('[download_dataset](https://drive.google.com/file/d/1cCkwiVv4mgfl20ntgY3n4yApcWqqZQe6/view)')
-
diff --git a/spaces/Ameaou/academic-chatgpt3.1/docs/README_RS.md b/spaces/Ameaou/academic-chatgpt3.1/docs/README_RS.md
deleted file mode 100644
index f8d925a27a6e5a19304db6f6d266e3bb3163172f..0000000000000000000000000000000000000000
--- a/spaces/Ameaou/academic-chatgpt3.1/docs/README_RS.md
+++ /dev/null
@@ -1,291 +0,0 @@
-> **Note**
->
-> Этот файл самовыражения автоматически генерируется модулем перевода markdown в этом проекте и может быть не на 100% правильным.
->
-
-# ChatGPT Academic Optimization
-
-**Если вам понравился этот проект, пожалуйста, поставьте ему звезду. Если вы придумали более полезные академические ярлыки или функциональные плагины, не стесняйтесь создавать запросы на изменение или пул-запросы. Мы также имеем [README на английском языке](docs/README_EN.md), переведенный этим же проектом.
-
-> **Примечание**
->
-> 1. Пожалуйста, обратите внимание, что только функциonal plugins (buttons) с **красным цветом** могут читать файлы, некоторые из которых находятся в **выпадающем меню** плагинов. Кроме того, мы приветствуем и обрабатываем любые новые плагины с **наивысшим приоритетом**!
->
-> 2. Функции каждого файла в этом проекте подробно описаны в собственном анализе [`self_analysis.md`](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A) . При повторных итерациях вы также можете вызывать обновленный отчет функций проекта, щелкнув соответствующий функциональный плагин GPT. Часто задаваемые вопросы собраны в [`wiki`](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98) .
-
-
-
-Функция | Описание
---- | ---
-Редактирование одним кликом | Поддержка редактирования одним кликом, поиск грамматических ошибок в академических статьях
-Переключение языков "Английский-Китайский" одним кликом | Одним кликом переключайте языки "Английский-Китайский"
-Разъяснение программного кода одним кликом | Вы можете правильно отобразить и объяснить программный код.
-[Настраиваемые сочетания клавиш](https://www.bilibili.com/video/BV14s4y1E7jN) | Поддержка настраиваемых сочетаний клавиш
-[Настройка сервера-прокси](https://www.bilibili.com/video/BV1rc411W7Dr) | Поддержка настройки сервера-прокси
-Модульный дизайн | Поддержка настраиваемых функциональных плагинов высших порядков и функциональных плагинов, поддерживающих [горячее обновление](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
-[Автоанализ программы](https://www.bilibili.com/video/BV1cj411A7VW) | [Функциональный плагин] [Прочтение в один клик](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A) кода программы проекта
-[Анализ программы](https://www.bilibili.com/video/BV1cj411A7VW) | [Функциональный плагин] Один клик для проанализирования дерева других проектов Python/C/C++/Java/Lua/...
-Чтение статей| [Функциональный плагин] Одним кликом прочитайте весь латех (LaTex) текст статьи и сгенерируйте краткое описание
-Перевод и редактирование всех статей из LaTex | [Функциональный плагин] Перевод или редактирование LaTex-статьи всего одним нажатием кнопки
-Генерация комментариев в пакетном режиме | [Функциональный плагин] Одним кликом сгенерируйте комментарии к функциям в пакетном режиме
-Генерация отчетов пакета CHAT | [Функциональный плагин] Автоматически создавайте сводные отчеты после выполнения
-[Помощник по arxiv](https://www.bilibili.com/video/BV1LM4y1279X) | [Функциональный плагин] Введите URL статьи arxiv, чтобы легко перевести резюме и загрузить PDF-файл
-[Перевод полного текста статьи в формате PDF](https://www.bilibili.com/video/BV1KT411x7Wn) | [Функциональный плагин] Извлеките заголовок статьи, резюме и переведите весь текст статьи (многопоточно)
-[Помощник интеграции Google Scholar](https://www.bilibili.com/video/BV19L411U7ia) | [Функциональный плагин] Дайте GPT выбрать для вас интересные статьи на любой странице поиска Google Scholar.
-Отображение формул/изображений/таблиц | Одновременно отображается tex-форма и рендер-форма формул, поддержка формул, высокоскоростных кодов
-Поддержка функциональных плагинов многопоточности | Поддержка многопоточной работы с плагинами, обрабатывайте огромные объемы текста или программы одним кликом
-Запуск темной темы gradio[подробнее](https://github.com/binary-husky/chatgpt_academic/issues/173) | Добавьте / ?__dark-theme=true в конец URL браузера, чтобы переключиться на темную тему.
-[Поддержка нескольких моделей LLM](https://www.bilibili.com/video/BV1wT411p7yf), поддержка API2D | Находиться между GPT3.5, GPT4 и [清华ChatGLM](https://github.com/THUDM/ChatGLM-6B) должно быть очень приятно, не так ли?
-Альтернатива huggingface без использования научной сети [Онлайн-эксперимент](https://huggingface.co/spaces/qingxu98/gpt-academic) | Войдите в систему, скопируйте пространство [этот пространственный URL](https://huggingface.co/spaces/qingxu98/gpt-academic)
-…… | ……
-
-
-
-
-- Новый интерфейс (вы можете изменить настройку LAYOUT в config.py, чтобы переключаться между "горизонтальным расположением" и "вертикальным расположением")
-
-
-
-
-
-Вы профессиональный переводчик научных статей.
-
-- Все кнопки генерируются динамически путем чтения functional.py и могут быть легко настроены под пользовательские потребности, освобождая буфер обмена.
-
-
-
-
-- Редактирование/корректирование
-
-
-
-
-- Если вывод содержит формулы, они отображаются одновременно как в формате tex, так и в рендеринговом формате для удобства копирования и чтения.
-
-
-
-
-- Лень смотреть код проекта? Просто покажите chatgpt.
-
-
-
-
-- Несколько моделей больших языковых моделей смешиваются (ChatGLM + OpenAI-GPT3.5 + [API2D] (https://api2d.com/) -GPT4)
-
-
-
-
-Несколько моделей больших языковых моделей смешиваются в [бета-версии huggingface] (https://huggingface.co/spaces/qingxu98/academic-chatgpt-beta) (huggingface-версия не поддерживает chatglm).
-
-
----
-
-## Установка - Метод 1: Запуск (Windows, Linux или MacOS)
-
-1. Скачайте проект
-```sh
-git clone https://github.com/binary-husky/chatgpt_academic.git
-cd chatgpt_academic
-```
-
-2. Настройка API_KEY и настройки прокси
-
-В файле `config.py` настройте зарубежный прокси и OpenAI API KEY, пояснения ниже
-```
-1. Если вы находитесь в Китае, вам нужно настроить зарубежный прокси, чтобы использовать OpenAI API. Пожалуйста, внимательно прочитайте config.py для получения инструкций (1. Измените USE_PROXY на True; 2. Измените прокси в соответствии с инструкциями).
-2. Настройка API KEY OpenAI. Вам необходимо зарегистрироваться на сайте OpenAI и получить API KEY. После получения API KEY настройте его в файле config.py.
-3. Вопросы, связанные с сетевыми проблемами (тайм-аут сети, прокси не работает), можно найти здесь: https://github.com/binary-husky/chatgpt_academic/issues/1
-```
-(Примечание: при запуске программы будет проверяться наличие конфиденциального файла конфигурации с именем `config_private.py` и использоваться в нем конфигурация параметров, которая перезаписывает параметры с такими же именами в `config.py`. Поэтому, если вы понимаете логику чтения нашей конфигурации, мы настоятельно рекомендуем вам создать новый файл конфигурации с именем `config_private.py` рядом с `config.py` и переместить (скопировать) настройки из `config.py` в `config_private.py`. `config_private.py` не подвергается контролю git, что делает конфиденциальную информацию более безопасной.)
-
-
-3. Установить зависимости
-```sh
-# (Выбор 1) Рекомендуется
-python -m pip install -r requirements.txt
-
-# (Выбор 2) Если вы используете anaconda, то шаги будут аналогичны:
-# (Шаг 2.1) conda create -n gptac_venv python=3.11
-# (Шаг 2.2) conda activate gptac_venv
-# (Шаг 2.3) python -m pip install -r requirements.txt
-
-# Примечание: используйте официальный источник pip или источник pip.aliyun.com. Другие источники pip могут вызывать проблемы. временный метод замены источника:
-# python -m pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
-```
-
-Если требуется поддержка TUNA ChatGLM, необходимо установить дополнительные зависимости (если вы неудобны с python, необходимо иметь хорошую конфигурацию компьютера):
-```sh
-python -m pip install -r request_llm/requirements_chatglm.txt
-```
-
-4. Запустите
-```sh
-python main.py
-```
-
-5. Тестовые функции плагина
-```
-- Тестирвоание анализа проекта Python
- В основной области введите `./crazy_functions/test_project/python/dqn` , а затем нажмите "Анализировать весь проект Python"
-- Тестирование самостоятельного чтения кода
- Щелкните " [Демонстрационный режим многопоточности] Проанализируйте сам проект (расшифровка источника кода)"
-- Тестирование функций шаблонного плагина (вы можете использовать эту функцию как шаблон для более сложных функций, требующих ответа от gpt в связи с тем, что произошло сегодня в истории)
- Щелкните " [Функции шаблонного плагина] День в истории"
-- На нижней панели дополнительные функции для выбора
-```
-
-## Установка - Метод 2: Использование docker (Linux)
-
-
-1. Только ChatGPT (рекомендуется для большинства пользователей):
-``` sh
-# Скачать проект
-git clone https://github.com/binary-husky/chatgpt_academic.git
-cd chatgpt_academic
-# Настроить прокси за границей и OpenAI API KEY
-Отредактируйте файл config.py в любом текстовом редакторе.
-# Установка
-docker build -t gpt-academic .
-# Запустить
-docker run --rm -it --net=host gpt-academic
-
-# Проверка функциональности плагина
-## Проверка шаблонной функции плагина (требуется, чтобы gpt ответил, что произошло "в истории на этот день"), вы можете использовать эту функцию в качестве шаблона для реализации более сложных функций.
-Нажмите "[Шаблонный демонстрационный плагин] История на этот день".
-## Тест абстрактного резюме для проекта на Latex
-В области ввода введите ./crazy_functions/test_project/latex/attention, а затем нажмите "Чтение реферата о тезисах статьи на LaTeX".
-## Тестовый анализ проекта на Python
-Введите в область ввода ./crazy_functions/test_project/python/dqn, затем нажмите "Проанализировать весь проект на Python".
-
-Выбирайте больше функциональных плагинов в нижнем выпадающем меню.
-```
-
-2. ChatGPT + ChatGLM (требуется глубокое знание Docker и достаточно мощное компьютерное оборудование):
-
-``` sh
-# Изменение Dockerfile
-cd docs && nano Dockerfile+ChatGLM
-# Как построить | Как запустить (Dockerfile+ChatGLM в пути docs, сначала перейдите в папку с помощью cd docs)
-docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM .
-# Как запустить | Как запустить (2) я хочу войти в контейнер и сделать какие-то настройки до запуска:
-docker run --rm -it --net=host --gpus=all gpt-academic bash
-```
-
-
-## Установка-Метод 3: Другие способы развертывания
-
-1. Развертывание на удаленном облачном сервере
-Пожалуйста, посетите [Deploy Wiki-1] (https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BA%91%E6%9C%8D%E5%8A%A1%E5%99%A8%E8%BF%9C%E7%A8%8B%E9%83%A8%E7%BD%B2%E6%8C%87%E5%8D%97)
-
-2. Использование WSL2 (Windows Subsystem for Linux)
-Пожалуйста, посетите [Deploy Wiki-2] (https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BD%BF%E7%94%A8WSL2%EF%BC%88Windows-Subsystem-for-Linux-%E5%AD%90%E7%B3%BB%E7%BB%9F%EF%BC%89%E9%83%A8%E7%BD%B2)
-
-
-## Установка-Настройки прокси
-### Метод 1: Обычный способ
-[Конфигурация прокси] (https://github.com/binary-husky/chatgpt_academic/issues/1)
-
-### Метод 2: Руководство новичка
-[Руководство новичка] (https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BB%A3%E7%90%86%E8%BD%AF%E4%BB%B6%E9%97%AE%E9%A2%98%E7%9A%84%E6%96%B0%E6%89%8B%E8%A7%A3%E5%86%B3%E6%96%B9%E6%B3%95%EF%BC%88%E6%96%B9%E6%B3%95%E5%8F%AA%E9%80%82%E7%94%A8%E4%BA%8E%E6%96%B0%E6%89%8B%EF%BC%89)
-
-
----
-
-## Настройка новой удобной кнопки (настройка быстрой клавиши для научной работы)
-Откройте `core_functional.py` любым текстовым редактором, добавьте элементы, как показано ниже, затем перезапустите программу. (Если кнопка уже успешно добавлена и видна, то префикс и суффикс поддерживают горячее изменение, чтобы они оказались в действии, не нужно перезапускать программу.)
-например
-```
-"Супер анг-рус": {
- # Префикс, будет добавлен перед вашим вводом. Например, используется для описания ваших потребностей, таких как перевод, кодинг, редактирование и т. д.
- "Prefix": "Пожалуйста, переведите этот фрагмент на русский язык, а затем создайте пошаговую таблицу в markdown, чтобы объяснить все специализированные термины, которые встречаются в тексте:\n\n",
-
- # Суффикс, будет добавлен после вашего ввода. Например, совместно с префиксом можно обрамить ваш ввод в кавычки.
- "Suffix": "",
-},
-```
-
Zoro.io APK Descargar: Cómo ver anime en línea gratis
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Si eres un fan del anime, es posible que hayas oído hablar de Zoro.io, un nuevo y popular sitio de streaming de anime que te permite ver miles de programas de anime de varios géneros de forma gratuita. Pero ¿sabía usted que también se puede descargar Zoro.io APK e instalarlo en su dispositivo Android para disfrutar del anime sobre la marcha? En este artículo, te mostraremos cómo hacerlo, así como las características, pros y contras, alternativas y reseñas de Zoro.io.
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¿Qué es Zoro.io?
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Zoro.io es un sitio de streaming de anime gratuito que se lanzó en 2020. Tiene una gran colección de series de anime y películas de diferentes géneros, como shonen, shoujo, seinen, josei, ecchi, harem, isekai, mecha, y más. Puede ver anime en línea con subtítulos en inglés o doblaje en calidad ultra HD sin ningún registro o pago. También puedes descargar episodios de anime para verlos sin conexión más tarde.
Algunas de las características que hacen que Zoro.io se destaque de otros sitios de streaming de anime son:
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No hay anuncios o ventanas emergentes. Zoro.io afirma ser el sitio más seguro para anime gratis, ya que no tiene ningún anuncio molesto o ventanas emergentes que podrían dañar su dispositivo o datos.
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Biblioteca grande y actualizada. Zoro.io tiene miles de títulos de anime de varios géneros y categorías. Puedes encontrar los últimos episodios de series de anime en curso, así como títulos clásicos y difíciles de encontrar.
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Opciones de subcama o doblado. Puede elegir ver anime con subtítulos en inglés o doblaje, dependiendo de su preferencia. También puede cambiar entre ellos fácilmente.
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Calidad Ultra HD. Puede transmitir o descargar episodios de anime en calidad ultra HD (1080p o superior), lo que le da una mejor experiencia de visualización.
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Pros y contras de Zoro.io
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Como cualquier otro sitio, Zoro.io tiene sus propias ventajas y desventajas. Aquí están algunas de ellas:
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Pros
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Contras
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Libre y seguro de usar
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No es un sitio de streaming legal
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Biblioteca grande y actualizada
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Opciones de servidor limitadas
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Opciones de subcama o doblado
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Posibles problemas de carga o almacenamiento en búfer
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Calidad Ultra HD
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Requiere VPN para algunas regiones
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Interfaz fácil de usar
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No hay soporte al cliente o sistema de retroalimentación
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Cómo descargar e instalar Zoro.io APK en dispositivos Android
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Si desea ver anime en su dispositivo Android con Zoro.io, es necesario descargar e instalar su archivo APK primero. Estos son los pasos para hacerlo:
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Paso 1: Habilitar fuentes desconocidas
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Antes de que pueda instalar Zoro.io APK, es necesario habilitar fuentes desconocidas en su dispositivo Android. Esto le permitirá instalar aplicaciones desde fuentes distintas de Google Play Store. Para hacer esto, vaya a Configuración > Seguridad > Fuentes desconocidas y conéctelo. Puede que vea un mensaje de advertencia, pero simplemente toque Aceptar para continuar.
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Paso 2: Descargar Zoro.io archivo APK
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Siguiente, es necesario descargar el archivo APK Zoro.io de una fuente confiable. Puede utilizar este enlace para descargar la última versión de Zoro.io APK (v1.0.0) a partir de junio de 2023. El tamaño del archivo es de unos 15 MB y es compatible con Android 4.4 y superior. Una vez que haya descargado el archivo, puede encontrarlo en su carpeta de descargas o en la barra de notificaciones.
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Paso 3: Instalar el archivo APK Zoro.io
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Después de haber descargado el archivo APK Zoro.io, puede instalarlo tocando en él y siguiendo las instrucciones en la pantalla. Es posible que vea un mensaje solicitando permisos, pero solo toque Instalar para continuar. El proceso de instalación debe tardar unos segundos.
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Paso 4: Inicie la aplicación Zoro.io y disfrute
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Cómo ver anime en línea con Zoro.io
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Ver anime en línea con Zoro.io es muy fácil y conveniente. Aquí hay algunos consejos para ayudarle a disfrutar de su experiencia de streaming de anime:
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Navegar por Género, Fecha de lanzamiento, Popularidad, o alfabéticamente
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Puede navegar por la biblioteca de anime por género, fecha de lanzamiento, popularidad o alfabéticamente. Puede encontrar estas opciones en la barra de menú superior de la aplicación. También puede utilizar la barra de búsqueda para buscar títulos o palabras clave específicas. Verás una lista de programas de anime que coinciden con tus criterios, junto con sus imágenes de portada, calificaciones, géneros y número de episodios.
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Elija la versión subcama o doblada
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Puede elegir ver anime con subtítulos en inglés o doblaje, dependiendo de su preferencia. También puede cambiar entre ellos fácilmente. Para hacer esto, toque en el programa de anime que desea ver y luego toque en el botón Subbed o Dubbed en la esquina inferior derecha de la pantalla. Verá una lista de episodios disponibles en el idioma elegido.
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Transmitir o descargar episodios de anime en calidad Ultra HD
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Puede transmitir o descargar episodios de anime en calidad ultra HD (1080p o superior), lo que le da una mejor experiencia de visualización. Para transmitir un episodio, simplemente toque en él y luego toque en el botón Reproducir en la esquina inferior izquierda de la pantalla. Verá un reproductor de vídeo con algunos controles, como pausa, reanudación, salto, volumen y pantalla completa. Para descargar un episodio, simplemente toque en él y luego toque en el botón Descargar en la esquina inferior derecha de la pantalla. Verá una barra de progreso que muestra el estado de la descarga. Puede encontrar los episodios descargados en la sección Descargas de la aplicación.
Alternativas a Zoro.io
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Zoro.io no es el único sitio que ofrece streaming de anime gratis. Hay muchas otras alternativas que puedes probar si quieres ver anime online. Estas son algunas de ellas:
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AnimeHeaven
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Animestreams
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Animestreams es un sitio de streaming de anime gratuito que tiene un diseño simple y minimalista. Tiene una colección decente de series de anime y películas de varios géneros y categorías. Puede ver anime en línea con subtítulos en inglés o doblaje en calidad HD sin ningún tipo de registro o pago. También puede solicitar anime que no están disponibles en el sitio. Animestreams tiene una interfaz básica que hace que sea fácil navegar y encontrar el anime que desea ver. Puede navegar por género, alfabéticamente o al azar. También puede usar la barra de búsqueda para buscar títulos o palabras clave específicos.
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Hulu
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Hulu es un servicio de streaming de pago que ofrece una amplia gama de contenido, incluyendo anime. Tiene una gran colección de series de anime y películas de diferentes géneros y categorías. Puede ver anime en línea con subtítulos en inglés o doblaje en calidad HD con una tarifa de suscripción. También puedes descargar episodios de anime para verlos sin conexión más tarde con un plan premium. Hulu tiene una interfaz profesional y sofisticada que hace que sea fácil acceder y disfrutar del contenido. Puede navegar por género, popularidad, original o recomendado. También puede usar la barra de búsqueda para buscar títulos o palabras clave específicos.
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Opiniones de Zoro.io
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Zoro.io ha recibido críticas mixtas de sus usuarios. Algunos usuarios han elogiado el sitio por sus características, calidad y seguridad, mientras que otros se han quejado de su legalidad, fiabilidad y disponibilidad. Aquí hay algunos ejemplos de comentarios positivos y negativos de Zoro.io:
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Comentarios positivos
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"Zoro.io es el mejor sitio para la transmisión de anime gratis. No tiene anuncios, no hay ventanas emergentes, no hay registro, no hay pago, y no hay problemas. Tiene una enorme biblioteca de programas de anime y películas de varios géneros y categorías. Tiene opciones de subcama y doblado en calidad ultra HD. Tiene una interfaz fácil de usar que hace que sea fácil encontrar el anime que desea ver. Me encanta Zoro.io y lo recomiendo a todos los fans del anime."
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"Zoro.io es un gran sitio para la transmisión de anime gratis. Tiene una biblioteca grande y actualizada de series de anime y películas de varios géneros y categorías. Tiene opciones de subcama y doblado en calidad ultra HD. Tiene una experiencia de transmisión rápida y suave sin problemas de almacenamiento en búfer o carga. Tiene una interfaz limpia y limpia que hace que sea fácil de navegar y encontrar el anime que desea ver. Me gusta ver anime en Zoro.io todos los días."
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Comentarios negativos
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"Zoro.io no es un sitio de streaming legal. No tiene los derechos o licencias para transmitir el contenido de anime en su sitio. Está violando las leyes de derechos de autor y las regulaciones de los creadores originales y distribuidores del contenido de anime. Está arriesgando acciones legales y sanciones de las autoridades y los propietarios del contenido del anime."
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"Zoro.io no es un sitio de streaming confiable. No tiene suficientes opciones de servidor para soportar la alta demanda de sus usuarios. A menudo se bloquea o se desconecta debido a problemas técnicos o de mantenimiento. No está disponible en algunas regiones debido a restricciones geográficas o bloques de ISP."
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"Zoro.io no es un buen sitio de streaming. No tiene buena calidad o variedad de contenido de anime en su sitio. A menudo tiene enlaces rotos, episodios faltantes, subtítulos incorrectos o videos de baja resolución en su sitio. No tiene ningún sistema de atención al cliente o retroalimentación en su sitio."
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Conclusión
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Preguntas frecuentes
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Aquí hay algunas preguntas frecuentes sobre Zoro.io:
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¿Es seguro usar Zoro.io?
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Zoro.io afirma ser el sitio más seguro para la transmisión gratuita de anime, ya que no tiene ningún anuncio o ventanas emergentes que puedan dañar su dispositivo o datos. Sin embargo, dado que Zoro.io no es un sitio de streaming legal, podría ser arriesgado usarlo sin una VPN o software antivirus.
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¿Es legal usar Zoro.io?
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Zoro.io no es un sitio de streaming legal, ya que no tiene los derechos o licencias para transmitir el contenido de anime en su sitio. Está violando las leyes de derechos de autor y las regulaciones de los creadores originales y distribuidores del contenido de anime. Se arriesga a acciones legales y sanciones de las autoridades y los propietarios del contenido del anime.
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¿Cómo puedo acceder a Zoro.io en mi región?
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Zoro.io podría no estar disponible en algunas regiones debido a restricciones geográficas o bloques de ISP. Si desea acceder a Zoro.io en su región, debe usar un servicio VPN que pueda evitar estas restricciones y bloqueos. Puede elegir un servidor VPN que se encuentre en una región donde Zoro.io sea accesible.
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¿Cómo puedo descargar episodios de anime de Zoro.io?
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Puede descargar episodios de anime de Zoro.io pulsando en el episodio que desea ver y luego pulsando en el botón Descargar en la esquina inferior derecha de la pantalla. Verá una barra de progreso que muestra el estado de la descarga. Puede encontrar los episodios descargados en la sección Descargas de la aplicación.
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¿Cómo puedo contactar a Zoro.io para apoyo o retroalimentación?
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Zoro.io no tiene ningún sistema de atención al cliente o retroalimentación en su sitio. No puede ponerse en contacto con Zoro.io para cualquier problema o sugerencia con respecto a su servicio o contenido. Solo puede confiar en foros o comunidades en línea para obtener ayuda o información sobre Zoro.io.
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Descargar Goat Simulator GoatZ: El juego de supervivencia más loco jamás
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¿Alguna vez te has preguntado cómo sería ser una cabra en un apocalipsis zombi? Bueno, no te preguntes más, porque Goat Simulator GoatZ está aquí para hacer tus sueños realidad. Este juego es la última adición oficial al universo Goat Simulator, y es un buen contendiente para la cosa más tonta de venir de Coffee Stain Studios todavía - CABRAS Y ZOMBIES EN EL MISMO JUEGO!
En este artículo, te diremos todo lo que necesitas saber sobre Goat Simulator GoatZ, incluyendo sus características, plataformas, cómo descargarlo y nuestra revisión de él. Si estás listo para desatar tu cabra interior y causar estragos en un mundo post-apocalíptico lleno de zombies, sigue leyendo.
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Características del simulador de cabra GoatZ
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Goat Simulator GoatZ no es solo un simulador de cabra normal. También es una parodia de juegos de supervivencia zombi, como DayZ, The Walking Dead, y The Last of Us. Tiene un sistema obligatorio de elaboración, un sistema de hambre y salud, un nuevo mapa y toneladas de zombies para luchar o infectar. Estas son algunas de las características que hacen de este juego tan loco y divertido:
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Modo zombi: Convertirse en una cabra zombi e infectar a todos
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Uno de los modos principales de Goat Simulator GoatZ es el modo zombi, donde empiezas como una cabra zombi infectada y tu objetivo es propagar el virus a todos los que ves. Puedes golpearte la cabeza, lamer, escupir o usar armas para convertir humanos y animales en zombis. También puedes encontrar cerebros para comer para restaurar tu salud. Sin embargo, ten cuidado, porque hay diferentes tipos de zombies que intentarán matarte, como zombis escupidores, zombis de carga, zombis fantasmas y rusos desnudos.
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Sistema de elaboración: Haga sus propias armas y artículos
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Modo de supervivencia: Comer, beber y mantenerse con vida
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Si quieres una experiencia más desafiante, puedes probar el modo de supervivencia de Goat Simulator GoatZ, donde tienes que comer y beber regularmente para sobrevivir. Puedes encontrar comida y agua en el ambiente, como hierba, flores, frutas, latas de refresco y más. También puedes comer los cadáveres de los humanos y animales que matas o infectas. Sin embargo, hay que tener cuidado de no comer alimentos podridos o beber agua contaminada, ya que te harán enfermar y perder la salud.
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Nuevo mapa: Explora un mundo post-apocalíptico lleno de secretos
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Goat Simulator GoatZ presenta un nuevo mapa que es más grande y diverso que el original Goat Simulator mapa. El mapa se encuentra en un mundo post-apocalíptico que ha sido invadido por zombies y otros peligros. Puede explorar diferentes áreas, como una ciudad, una granja, un carnaval, una prisión, una base militar y más. También puedes encontrar secretos ocultos, como huevos de Pascua, referencias, chistes y logros.
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Cabras desbloqueables: Descubre nuevas cabras con poderes especiales
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Mientras juegas Goat Simulator GoatZ, puedes desbloquear nuevas cabras que tienen poderes y habilidades especiales. Puedes desbloquearlos completando ciertas tareas o encontrándolas en el mapa. Algunas de las cabras desbloqueables son:
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La cabra constructora: Una cabra que puede construir estructuras y vehículos a partir de chatarra.
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La cabra con clase: Una cabra que lleva un monóculo y un sombrero de copa y puede convocar a los pingüinos.
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El Deadgoa7: Una cabra que lleva una máscara y toca música electrónica.
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La Cabra Dona: Una cabra que tiene la forma de una dona y puede rodar alrededor.
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El inventario Cabra: Una cabra que tiene un sistema de inventario y puede llevar artículos.
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La vieja cabra: Una cabra que es vieja y frágil y puede invocar cabras del pasado.
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La Cabra Repulsiva: Una cabra que es fea y repugnante y puede hacer que todos vomiten.
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La cabra tornado: Una cabra que puede crear tornados y aspirar todo.
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La cabra vudú: Una cabra que puede controlar a otras cabras con una muñeca vudú.
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Plataformas de Goat Simulator GoatZ
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Goat Simulator GoatZ está disponible en varias plataformas, como PC, móvil, consola y Switch. Cada plataforma tiene sus propias ventajas y desventajas. Aquí hay una tabla de comparación de las plataformas:
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Plataforma
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Precio
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Características
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Pros
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Contras
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PC (Steam)
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$4.99 para DLC o $9.99 para el paquete con el juego básico
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Logros, soporte de taller, mods
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Mejores gráficos, más contenido, más personalización
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Requiere juego base para jugar DLC
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Móvil (Android/iOS)
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$4.99 para la aplicación
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Controles táctiles
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Más barato que la versión para PC, portátil
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Gráficos inferiores, menos contenido, sin mods
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Consola (Xbox/PlayStation)
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$9.99 para el juego o $19.99 para el paquete con el juego básico
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Multijugador local
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Mejores gráficos que la versión móvil, sofá cooperativo
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Más caro que la versión para PC, menos contenido que la versión para PC
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Cambiar (Nintendo)
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$12 . 99 para el juego o $29.99 para el paquete con el juego de base y otros dos DLCs
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Portabilidad, DLC incluidos
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Más contenido que la versión de consola, se puede reproducir en cualquier lugar
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La versión más cara, gráficos inferiores que las versiones de PC y consola
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Cómo descargar Goat Simulator GoatZ
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Si usted está interesado en jugar Goat Simulator GoatZ, tendrá que descargarlo desde la plataforma de su elección. Estos son los pasos para descargarlo para cada plataforma:
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PC (vapor)
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Abre Steam e inicia sesión en tu cuenta.
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Buscar Goat Simulator GoatZ en la tienda.
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Añadir a su carrito y proceder a la caja.
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Una vez hecho el pago, el juego será añadido a su biblioteca.
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Descargue e instale el juego desde su biblioteca.
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Iniciar el juego y disfrutar.
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Móvil (Android/iOS)
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Abre Google Play o App Store en tu dispositivo.
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Buscar Goat Simulator GoatZ en la tienda.
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Seleccione la aplicación y toque en el botón comprar.
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Introduzca sus datos de pago y confirme la compra.
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La aplicación se descargará e instalará en su dispositivo.
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Abre la aplicación y disfruta.
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Consola (Xbox/PlayStation)
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Encienda su consola e inicie sesión en su cuenta.
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Ir a la tienda de Xbox o PlayStation en su consola.
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Buscar Goat Simulator GoatZ en la tienda.
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Seleccione la opción de juego o la opción de paquete con el juego base.
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Añadir a su carrito y proceder a la caja.
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Una vez hecho el pago, el juego será añadido a su biblioteca.
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Descargue e instale el juego desde su biblioteca.
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Iniciar el juego y disfrutar.
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Cambiar (Nintendo)
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Activa tu Switch e inicia sesión en tu cuenta.
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Ir a la Nintendo eShop en su Switch.
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Buscar Goat Simulator GoatZ en la tienda.
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Seleccione la opción de juego o la opción de paquete con el juego base y otros dos DLC.
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Añadir a su carrito y proceder a la caja.
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Una vez hecho el pago, el juego será añadido a su biblioteca.
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Descargue e instale el juego desde su biblioteca.
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Iniciar el juego y disfrutar.
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Revisión de Goat Simulator GoatZ
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Ventajas: Divertido, caótico, creativo y adictivo juego
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Lo mejor de Goat Simulator GoatZ es el humor y el caos que crea. Puedes hacer casi todo lo que quieras como una cabra, desde destruir edificios, autos y personas, hasta volar, nadar y bailar. También puedes usar tu lengua para lamer y arrastrar objetos y criaturas. Puede crear sus propias armas y objetos desde el sistema de elaboración y utilizarlos para causar más caos. También puedes infectar a todos con el virus zombie y verlos convertirse en muertos vivientes sin sentido. El juego está lleno de chistes, referencias, parodias y sorpresas que te harán reír en voz alta. El juego también es muy creativo y adictivo, ya que puedes explorar el mapa y encontrar nuevos secretos, desbloquear nuevas cabras y logros completos.
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Contras: Glitchy, sin pulir, repetitivo y caro para algunas plataformas
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Lo peor de Goat Simulator GoatZ es la falta de pulido y calidad que muestra. El juego está lleno de fallos, errores, errores y tonterías que pueden arruinar la experiencia de juego. El juego también es muy poco pulido, ya que tiene malos gráficos, sonido y controles. El juego también es muy repetitivo, ya que no tiene historia real, objetivos o progresión. El juego también es muy caro para algunas plataformas, especialmente las versiones de consola y Switch, que cuestan más que las versiones para PC y móviles, pero ofrecen menos contenido y características.
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Veredicto: Un juego hilarante y absurdo que no es para todos pero vale la pena probar para los fans de las cabras y zombies
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Conclusión
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Goat Simulator GoatZ es el juego de supervivencia más loco que te permite jugar como una cabra en un apocalipsis zombi. Es una parodia de los juegos de supervivencia zombie que cuenta con un modo zombie, un sistema de elaboración, un modo de supervivencia, un nuevo mapa y cabras desbloqueables. Está disponible en varias plataformas como PC, móvil, consola y Switch. Es un juego que es divertido, caótico, creativo y adictivo, pero también brillante, sin pulir, repetitivo y caro para algunas plataformas. Es un juego que no es para todos, pero vale la pena probar para los fans de las cabras y zombies.
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Si estás interesado en jugar a Goat Simulator GoatZ, puedes descargarlo desde la plataforma de tu elección siguiendo los pasos que hemos proporcionado en este artículo. Esperamos que hayas disfrutado leyendo este artículo y hayas aprendido algo nuevo sobre este juego. Ahora adelante y descarga Goat Simulator GoatZ y diviértete!
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Preguntas frecuentes
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Q1. ¿Es Goat Simulator GoatZ un juego independiente o un DLC?
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A1. Goat Simulator GoatZ es un juego independiente y un DLC dependiendo de la plataforma. Para PC (Steam), es un DLC que requiere el juego base Goat Simulator para jugar. Para móvil (Android/iOS), consola (Xbox/PlayStation) e Switch (Nintendo), es un juego independiente que no requiere el juego base para jugar.
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Q2. ¿Cuánto tiempo es Goat Simulator GoatZ?
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A2. Goat Simulator GoatZ no tiene una longitud fija o un objetivo final. Es un juego de sandbox de mundo abierto que te permite jugar el tiempo que quieras o hasta que te aburras. Sin embargo, si quieres completar todos los logros y desbloquear todas las cabras, puede que te lleve entre 10 y 15 horas.
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Q3. ¿Es Goat Simulator GoatZ multijugador?
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Q4. ¿Es Goat Simulator GoatZ adecuado para niños?
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A4. Goat Simulator GoatZ no es adecuado para niños menores de 13 años. Es un juego que contiene violencia, sangre, blasfemia, humor crudo y referencias a drogas y alcohol. Es un juego que está clasificado M para Maduro por la ESRB, 16+ por PEGI, y 15+ por USK. Es un juego que está destinado a los adultos que pueden apreciar su sátira y absurdo.
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Q5. ¿Cuáles son algunos consejos y trucos para jugar Goat Simulator GoatZ?
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A5. Aquí hay algunos consejos y trucos que podrían ayudarle a disfrutar de Goat Simulator GoatZ más:
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Utilice el botón de cámara lenta para realizar acrobacias épicas y combos.
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Utilice el botón ragdoll para evitar daños y caídas desde alturas.
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Usa el botón de lamer para agarrar y lanzar objetos y criaturas.
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Utilice el botón de inventario para acceder a su menú de elaboración y elementos.
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Utilice el botón especial para activar el poder especial de su cabra.
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Explora el mapa y encuentra secretos ocultos, huevos de Pascua y logros.
-
Pruebe diferentes cabras y vea lo que pueden hacer.
-
Diviértete y no te tomes el juego demasiado en serio.
-
64aa2da5cf
-
-
\ No newline at end of file
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/commands/check.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/commands/check.py
deleted file mode 100644
index 584df9f55c5d63d632f375d703f858e18c0acf2c..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/commands/check.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import logging
-from optparse import Values
-from typing import List
-
-from pip._internal.cli.base_command import Command
-from pip._internal.cli.status_codes import ERROR, SUCCESS
-from pip._internal.operations.check import (
- check_package_set,
- create_package_set_from_installed,
-)
-from pip._internal.utils.misc import write_output
-
-logger = logging.getLogger(__name__)
-
-
-class CheckCommand(Command):
- """Verify installed packages have compatible dependencies."""
-
- usage = """
- %prog [options]"""
-
- def run(self, options: Values, args: List[str]) -> int:
- package_set, parsing_probs = create_package_set_from_installed()
- missing, conflicting = check_package_set(package_set)
-
- for project_name in missing:
- version = package_set[project_name].version
- for dependency in missing[project_name]:
- write_output(
- "%s %s requires %s, which is not installed.",
- project_name,
- version,
- dependency[0],
- )
-
- for project_name in conflicting:
- version = package_set[project_name].version
- for dep_name, dep_version, req in conflicting[project_name]:
- write_output(
- "%s %s has requirement %s, but you have %s %s.",
- project_name,
- version,
- req,
- dep_name,
- dep_version,
- )
-
- if missing or conflicting or parsing_probs:
- return ERROR
- else:
- write_output("No broken requirements found.")
- return SUCCESS
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/req/constructors.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/req/constructors.py
deleted file mode 100644
index c5ca2d85d5176c65a2e90000b0d67390573120a6..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/req/constructors.py
+++ /dev/null
@@ -1,506 +0,0 @@
-"""Backing implementation for InstallRequirement's various constructors
-
-The idea here is that these formed a major chunk of InstallRequirement's size
-so, moving them and support code dedicated to them outside of that class
-helps creates for better understandability for the rest of the code.
-
-These are meant to be used elsewhere within pip to create instances of
-InstallRequirement.
-"""
-
-import logging
-import os
-import re
-from typing import Dict, List, Optional, Set, Tuple, Union
-
-from pip._vendor.packaging.markers import Marker
-from pip._vendor.packaging.requirements import InvalidRequirement, Requirement
-from pip._vendor.packaging.specifiers import Specifier
-
-from pip._internal.exceptions import InstallationError
-from pip._internal.models.index import PyPI, TestPyPI
-from pip._internal.models.link import Link
-from pip._internal.models.wheel import Wheel
-from pip._internal.req.req_file import ParsedRequirement
-from pip._internal.req.req_install import InstallRequirement
-from pip._internal.utils.filetypes import is_archive_file
-from pip._internal.utils.misc import is_installable_dir
-from pip._internal.utils.packaging import get_requirement
-from pip._internal.utils.urls import path_to_url
-from pip._internal.vcs import is_url, vcs
-
-__all__ = [
- "install_req_from_editable",
- "install_req_from_line",
- "parse_editable",
-]
-
-logger = logging.getLogger(__name__)
-operators = Specifier._operators.keys()
-
-
-def _strip_extras(path: str) -> Tuple[str, Optional[str]]:
- m = re.match(r"^(.+)(\[[^\]]+\])$", path)
- extras = None
- if m:
- path_no_extras = m.group(1)
- extras = m.group(2)
- else:
- path_no_extras = path
-
- return path_no_extras, extras
-
-
-def convert_extras(extras: Optional[str]) -> Set[str]:
- if not extras:
- return set()
- return get_requirement("placeholder" + extras.lower()).extras
-
-
-def parse_editable(editable_req: str) -> Tuple[Optional[str], str, Set[str]]:
- """Parses an editable requirement into:
- - a requirement name
- - an URL
- - extras
- - editable options
- Accepted requirements:
- svn+http://blahblah@rev#egg=Foobar[baz]&subdirectory=version_subdir
- .[some_extra]
- """
-
- url = editable_req
-
- # If a file path is specified with extras, strip off the extras.
- url_no_extras, extras = _strip_extras(url)
-
- if os.path.isdir(url_no_extras):
- # Treating it as code that has already been checked out
- url_no_extras = path_to_url(url_no_extras)
-
- if url_no_extras.lower().startswith("file:"):
- package_name = Link(url_no_extras).egg_fragment
- if extras:
- return (
- package_name,
- url_no_extras,
- get_requirement("placeholder" + extras.lower()).extras,
- )
- else:
- return package_name, url_no_extras, set()
-
- for version_control in vcs:
- if url.lower().startswith(f"{version_control}:"):
- url = f"{version_control}+{url}"
- break
-
- link = Link(url)
-
- if not link.is_vcs:
- backends = ", ".join(vcs.all_schemes)
- raise InstallationError(
- f"{editable_req} is not a valid editable requirement. "
- f"It should either be a path to a local project or a VCS URL "
- f"(beginning with {backends})."
- )
-
- package_name = link.egg_fragment
- if not package_name:
- raise InstallationError(
- "Could not detect requirement name for '{}', please specify one "
- "with #egg=your_package_name".format(editable_req)
- )
- return package_name, url, set()
-
-
-def check_first_requirement_in_file(filename: str) -> None:
- """Check if file is parsable as a requirements file.
-
- This is heavily based on ``pkg_resources.parse_requirements``, but
- simplified to just check the first meaningful line.
-
- :raises InvalidRequirement: If the first meaningful line cannot be parsed
- as an requirement.
- """
- with open(filename, encoding="utf-8", errors="ignore") as f:
- # Create a steppable iterator, so we can handle \-continuations.
- lines = (
- line
- for line in (line.strip() for line in f)
- if line and not line.startswith("#") # Skip blank lines/comments.
- )
-
- for line in lines:
- # Drop comments -- a hash without a space may be in a URL.
- if " #" in line:
- line = line[: line.find(" #")]
- # If there is a line continuation, drop it, and append the next line.
- if line.endswith("\\"):
- line = line[:-2].strip() + next(lines, "")
- Requirement(line)
- return
-
-
-def deduce_helpful_msg(req: str) -> str:
- """Returns helpful msg in case requirements file does not exist,
- or cannot be parsed.
-
- :params req: Requirements file path
- """
- if not os.path.exists(req):
- return f" File '{req}' does not exist."
- msg = " The path does exist. "
- # Try to parse and check if it is a requirements file.
- try:
- check_first_requirement_in_file(req)
- except InvalidRequirement:
- logger.debug("Cannot parse '%s' as requirements file", req)
- else:
- msg += (
- f"The argument you provided "
- f"({req}) appears to be a"
- f" requirements file. If that is the"
- f" case, use the '-r' flag to install"
- f" the packages specified within it."
- )
- return msg
-
-
-class RequirementParts:
- def __init__(
- self,
- requirement: Optional[Requirement],
- link: Optional[Link],
- markers: Optional[Marker],
- extras: Set[str],
- ):
- self.requirement = requirement
- self.link = link
- self.markers = markers
- self.extras = extras
-
-
-def parse_req_from_editable(editable_req: str) -> RequirementParts:
- name, url, extras_override = parse_editable(editable_req)
-
- if name is not None:
- try:
- req: Optional[Requirement] = Requirement(name)
- except InvalidRequirement:
- raise InstallationError(f"Invalid requirement: '{name}'")
- else:
- req = None
-
- link = Link(url)
-
- return RequirementParts(req, link, None, extras_override)
-
-
-# ---- The actual constructors follow ----
-
-
-def install_req_from_editable(
- editable_req: str,
- comes_from: Optional[Union[InstallRequirement, str]] = None,
- *,
- use_pep517: Optional[bool] = None,
- isolated: bool = False,
- global_options: Optional[List[str]] = None,
- hash_options: Optional[Dict[str, List[str]]] = None,
- constraint: bool = False,
- user_supplied: bool = False,
- permit_editable_wheels: bool = False,
- config_settings: Optional[Dict[str, Union[str, List[str]]]] = None,
-) -> InstallRequirement:
- parts = parse_req_from_editable(editable_req)
-
- return InstallRequirement(
- parts.requirement,
- comes_from=comes_from,
- user_supplied=user_supplied,
- editable=True,
- permit_editable_wheels=permit_editable_wheels,
- link=parts.link,
- constraint=constraint,
- use_pep517=use_pep517,
- isolated=isolated,
- global_options=global_options,
- hash_options=hash_options,
- config_settings=config_settings,
- extras=parts.extras,
- )
-
-
-def _looks_like_path(name: str) -> bool:
- """Checks whether the string "looks like" a path on the filesystem.
-
- This does not check whether the target actually exists, only judge from the
- appearance.
-
- Returns true if any of the following conditions is true:
- * a path separator is found (either os.path.sep or os.path.altsep);
- * a dot is found (which represents the current directory).
- """
- if os.path.sep in name:
- return True
- if os.path.altsep is not None and os.path.altsep in name:
- return True
- if name.startswith("."):
- return True
- return False
-
-
-def _get_url_from_path(path: str, name: str) -> Optional[str]:
- """
- First, it checks whether a provided path is an installable directory. If it
- is, returns the path.
-
- If false, check if the path is an archive file (such as a .whl).
- The function checks if the path is a file. If false, if the path has
- an @, it will treat it as a PEP 440 URL requirement and return the path.
- """
- if _looks_like_path(name) and os.path.isdir(path):
- if is_installable_dir(path):
- return path_to_url(path)
- # TODO: The is_installable_dir test here might not be necessary
- # now that it is done in load_pyproject_toml too.
- raise InstallationError(
- f"Directory {name!r} is not installable. Neither 'setup.py' "
- "nor 'pyproject.toml' found."
- )
- if not is_archive_file(path):
- return None
- if os.path.isfile(path):
- return path_to_url(path)
- urlreq_parts = name.split("@", 1)
- if len(urlreq_parts) >= 2 and not _looks_like_path(urlreq_parts[0]):
- # If the path contains '@' and the part before it does not look
- # like a path, try to treat it as a PEP 440 URL req instead.
- return None
- logger.warning(
- "Requirement %r looks like a filename, but the file does not exist",
- name,
- )
- return path_to_url(path)
-
-
-def parse_req_from_line(name: str, line_source: Optional[str]) -> RequirementParts:
- if is_url(name):
- marker_sep = "; "
- else:
- marker_sep = ";"
- if marker_sep in name:
- name, markers_as_string = name.split(marker_sep, 1)
- markers_as_string = markers_as_string.strip()
- if not markers_as_string:
- markers = None
- else:
- markers = Marker(markers_as_string)
- else:
- markers = None
- name = name.strip()
- req_as_string = None
- path = os.path.normpath(os.path.abspath(name))
- link = None
- extras_as_string = None
-
- if is_url(name):
- link = Link(name)
- else:
- p, extras_as_string = _strip_extras(path)
- url = _get_url_from_path(p, name)
- if url is not None:
- link = Link(url)
-
- # it's a local file, dir, or url
- if link:
- # Handle relative file URLs
- if link.scheme == "file" and re.search(r"\.\./", link.url):
- link = Link(path_to_url(os.path.normpath(os.path.abspath(link.path))))
- # wheel file
- if link.is_wheel:
- wheel = Wheel(link.filename) # can raise InvalidWheelFilename
- req_as_string = f"{wheel.name}=={wheel.version}"
- else:
- # set the req to the egg fragment. when it's not there, this
- # will become an 'unnamed' requirement
- req_as_string = link.egg_fragment
-
- # a requirement specifier
- else:
- req_as_string = name
-
- extras = convert_extras(extras_as_string)
-
- def with_source(text: str) -> str:
- if not line_source:
- return text
- return f"{text} (from {line_source})"
-
- def _parse_req_string(req_as_string: str) -> Requirement:
- try:
- req = get_requirement(req_as_string)
- except InvalidRequirement:
- if os.path.sep in req_as_string:
- add_msg = "It looks like a path."
- add_msg += deduce_helpful_msg(req_as_string)
- elif "=" in req_as_string and not any(
- op in req_as_string for op in operators
- ):
- add_msg = "= is not a valid operator. Did you mean == ?"
- else:
- add_msg = ""
- msg = with_source(f"Invalid requirement: {req_as_string!r}")
- if add_msg:
- msg += f"\nHint: {add_msg}"
- raise InstallationError(msg)
- else:
- # Deprecate extras after specifiers: "name>=1.0[extras]"
- # This currently works by accident because _strip_extras() parses
- # any extras in the end of the string and those are saved in
- # RequirementParts
- for spec in req.specifier:
- spec_str = str(spec)
- if spec_str.endswith("]"):
- msg = f"Extras after version '{spec_str}'."
- raise InstallationError(msg)
- return req
-
- if req_as_string is not None:
- req: Optional[Requirement] = _parse_req_string(req_as_string)
- else:
- req = None
-
- return RequirementParts(req, link, markers, extras)
-
-
-def install_req_from_line(
- name: str,
- comes_from: Optional[Union[str, InstallRequirement]] = None,
- *,
- use_pep517: Optional[bool] = None,
- isolated: bool = False,
- global_options: Optional[List[str]] = None,
- hash_options: Optional[Dict[str, List[str]]] = None,
- constraint: bool = False,
- line_source: Optional[str] = None,
- user_supplied: bool = False,
- config_settings: Optional[Dict[str, Union[str, List[str]]]] = None,
-) -> InstallRequirement:
- """Creates an InstallRequirement from a name, which might be a
- requirement, directory containing 'setup.py', filename, or URL.
-
- :param line_source: An optional string describing where the line is from,
- for logging purposes in case of an error.
- """
- parts = parse_req_from_line(name, line_source)
-
- return InstallRequirement(
- parts.requirement,
- comes_from,
- link=parts.link,
- markers=parts.markers,
- use_pep517=use_pep517,
- isolated=isolated,
- global_options=global_options,
- hash_options=hash_options,
- config_settings=config_settings,
- constraint=constraint,
- extras=parts.extras,
- user_supplied=user_supplied,
- )
-
-
-def install_req_from_req_string(
- req_string: str,
- comes_from: Optional[InstallRequirement] = None,
- isolated: bool = False,
- use_pep517: Optional[bool] = None,
- user_supplied: bool = False,
-) -> InstallRequirement:
- try:
- req = get_requirement(req_string)
- except InvalidRequirement:
- raise InstallationError(f"Invalid requirement: '{req_string}'")
-
- domains_not_allowed = [
- PyPI.file_storage_domain,
- TestPyPI.file_storage_domain,
- ]
- if (
- req.url
- and comes_from
- and comes_from.link
- and comes_from.link.netloc in domains_not_allowed
- ):
- # Explicitly disallow pypi packages that depend on external urls
- raise InstallationError(
- "Packages installed from PyPI cannot depend on packages "
- "which are not also hosted on PyPI.\n"
- "{} depends on {} ".format(comes_from.name, req)
- )
-
- return InstallRequirement(
- req,
- comes_from,
- isolated=isolated,
- use_pep517=use_pep517,
- user_supplied=user_supplied,
- )
-
-
-def install_req_from_parsed_requirement(
- parsed_req: ParsedRequirement,
- isolated: bool = False,
- use_pep517: Optional[bool] = None,
- user_supplied: bool = False,
- config_settings: Optional[Dict[str, Union[str, List[str]]]] = None,
-) -> InstallRequirement:
- if parsed_req.is_editable:
- req = install_req_from_editable(
- parsed_req.requirement,
- comes_from=parsed_req.comes_from,
- use_pep517=use_pep517,
- constraint=parsed_req.constraint,
- isolated=isolated,
- user_supplied=user_supplied,
- config_settings=config_settings,
- )
-
- else:
- req = install_req_from_line(
- parsed_req.requirement,
- comes_from=parsed_req.comes_from,
- use_pep517=use_pep517,
- isolated=isolated,
- global_options=(
- parsed_req.options.get("global_options", [])
- if parsed_req.options
- else []
- ),
- hash_options=(
- parsed_req.options.get("hashes", {}) if parsed_req.options else {}
- ),
- constraint=parsed_req.constraint,
- line_source=parsed_req.line_source,
- user_supplied=user_supplied,
- config_settings=config_settings,
- )
- return req
-
-
-def install_req_from_link_and_ireq(
- link: Link, ireq: InstallRequirement
-) -> InstallRequirement:
- return InstallRequirement(
- req=ireq.req,
- comes_from=ireq.comes_from,
- editable=ireq.editable,
- link=link,
- markers=ireq.markers,
- use_pep517=ireq.use_pep517,
- isolated=ireq.isolated,
- global_options=ireq.global_options,
- hash_options=ireq.hash_options,
- config_settings=ireq.config_settings,
- user_supplied=ireq.user_supplied,
- )
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/urllib3/util/ssl_match_hostname.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/urllib3/util/ssl_match_hostname.py
deleted file mode 100644
index 1dd950c489607d06ecc5218292a1b55558b47be8..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/urllib3/util/ssl_match_hostname.py
+++ /dev/null
@@ -1,159 +0,0 @@
-"""The match_hostname() function from Python 3.3.3, essential when using SSL."""
-
-# Note: This file is under the PSF license as the code comes from the python
-# stdlib. http://docs.python.org/3/license.html
-
-import re
-import sys
-
-# ipaddress has been backported to 2.6+ in pypi. If it is installed on the
-# system, use it to handle IPAddress ServerAltnames (this was added in
-# python-3.5) otherwise only do DNS matching. This allows
-# util.ssl_match_hostname to continue to be used in Python 2.7.
-try:
- import ipaddress
-except ImportError:
- ipaddress = None
-
-__version__ = "3.5.0.1"
-
-
-class CertificateError(ValueError):
- pass
-
-
-def _dnsname_match(dn, hostname, max_wildcards=1):
- """Matching according to RFC 6125, section 6.4.3
-
- http://tools.ietf.org/html/rfc6125#section-6.4.3
- """
- pats = []
- if not dn:
- return False
-
- # Ported from python3-syntax:
- # leftmost, *remainder = dn.split(r'.')
- parts = dn.split(r".")
- leftmost = parts[0]
- remainder = parts[1:]
-
- wildcards = leftmost.count("*")
- if wildcards > max_wildcards:
- # Issue #17980: avoid denials of service by refusing more
- # than one wildcard per fragment. A survey of established
- # policy among SSL implementations showed it to be a
- # reasonable choice.
- raise CertificateError(
- "too many wildcards in certificate DNS name: " + repr(dn)
- )
-
- # speed up common case w/o wildcards
- if not wildcards:
- return dn.lower() == hostname.lower()
-
- # RFC 6125, section 6.4.3, subitem 1.
- # The client SHOULD NOT attempt to match a presented identifier in which
- # the wildcard character comprises a label other than the left-most label.
- if leftmost == "*":
- # When '*' is a fragment by itself, it matches a non-empty dotless
- # fragment.
- pats.append("[^.]+")
- elif leftmost.startswith("xn--") or hostname.startswith("xn--"):
- # RFC 6125, section 6.4.3, subitem 3.
- # The client SHOULD NOT attempt to match a presented identifier
- # where the wildcard character is embedded within an A-label or
- # U-label of an internationalized domain name.
- pats.append(re.escape(leftmost))
- else:
- # Otherwise, '*' matches any dotless string, e.g. www*
- pats.append(re.escape(leftmost).replace(r"\*", "[^.]*"))
-
- # add the remaining fragments, ignore any wildcards
- for frag in remainder:
- pats.append(re.escape(frag))
-
- pat = re.compile(r"\A" + r"\.".join(pats) + r"\Z", re.IGNORECASE)
- return pat.match(hostname)
-
-
-def _to_unicode(obj):
- if isinstance(obj, str) and sys.version_info < (3,):
- # ignored flake8 # F821 to support python 2.7 function
- obj = unicode(obj, encoding="ascii", errors="strict") # noqa: F821
- return obj
-
-
-def _ipaddress_match(ipname, host_ip):
- """Exact matching of IP addresses.
-
- RFC 6125 explicitly doesn't define an algorithm for this
- (section 1.7.2 - "Out of Scope").
- """
- # OpenSSL may add a trailing newline to a subjectAltName's IP address
- # Divergence from upstream: ipaddress can't handle byte str
- ip = ipaddress.ip_address(_to_unicode(ipname).rstrip())
- return ip == host_ip
-
-
-def match_hostname(cert, hostname):
- """Verify that *cert* (in decoded format as returned by
- SSLSocket.getpeercert()) matches the *hostname*. RFC 2818 and RFC 6125
- rules are followed, but IP addresses are not accepted for *hostname*.
-
- CertificateError is raised on failure. On success, the function
- returns nothing.
- """
- if not cert:
- raise ValueError(
- "empty or no certificate, match_hostname needs a "
- "SSL socket or SSL context with either "
- "CERT_OPTIONAL or CERT_REQUIRED"
- )
- try:
- # Divergence from upstream: ipaddress can't handle byte str
- host_ip = ipaddress.ip_address(_to_unicode(hostname))
- except (UnicodeError, ValueError):
- # ValueError: Not an IP address (common case)
- # UnicodeError: Divergence from upstream: Have to deal with ipaddress not taking
- # byte strings. addresses should be all ascii, so we consider it not
- # an ipaddress in this case
- host_ip = None
- except AttributeError:
- # Divergence from upstream: Make ipaddress library optional
- if ipaddress is None:
- host_ip = None
- else: # Defensive
- raise
- dnsnames = []
- san = cert.get("subjectAltName", ())
- for key, value in san:
- if key == "DNS":
- if host_ip is None and _dnsname_match(value, hostname):
- return
- dnsnames.append(value)
- elif key == "IP Address":
- if host_ip is not None and _ipaddress_match(value, host_ip):
- return
- dnsnames.append(value)
- if not dnsnames:
- # The subject is only checked when there is no dNSName entry
- # in subjectAltName
- for sub in cert.get("subject", ()):
- for key, value in sub:
- # XXX according to RFC 2818, the most specific Common Name
- # must be used.
- if key == "commonName":
- if _dnsname_match(value, hostname):
- return
- dnsnames.append(value)
- if len(dnsnames) > 1:
- raise CertificateError(
- "hostname %r "
- "doesn't match either of %s" % (hostname, ", ".join(map(repr, dnsnames)))
- )
- elif len(dnsnames) == 1:
- raise CertificateError("hostname %r doesn't match %r" % (hostname, dnsnames[0]))
- else:
- raise CertificateError(
- "no appropriate commonName or subjectAltName fields were found"
- )
diff --git a/spaces/BigSalmon/MASKK/app.py b/spaces/BigSalmon/MASKK/app.py
deleted file mode 100644
index 20887437f900d3135653a24d5d818de5f720b597..0000000000000000000000000000000000000000
--- a/spaces/BigSalmon/MASKK/app.py
+++ /dev/null
@@ -1,39 +0,0 @@
-import torch
-import streamlit as st
-import numpy as np
-import pandas as pd
-import os
-import torch
-import torch.nn as nn
-from transformers import ElectraModel, AutoConfig, GPT2LMHeadModel
-from transformers.activations import get_activation
-from transformers import AutoTokenizer
-
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-from transformers import AutoTokenizer, AutoModelForMaskedLM
-artist_name = st.text_input("Model", "roberta-base")
-tokenizer = AutoTokenizer.from_pretrained("roberta-base")
-model = AutoModelForMaskedLM.from_pretrained(artist_name)
-
-first = "Boston is a place to live."
-
-with st.form(key='my_form'):
- prompt = st.text_area(label='Enter Text. Put where you want the model to fill in the blank. You can use more than one at a time.', value=first)
- submit_button = st.form_submit_button(label='Submit')
-
- if submit_button:
- a_list = []
- token_ids = tokenizer.encode(prompt, return_tensors='pt')
- token_ids_tk = tokenizer.tokenize(prompt, return_tensors='pt')
- masked_position = (token_ids.squeeze() == tokenizer.mask_token_id).nonzero()
- masked_pos = [mask.item() for mask in masked_position ]
- with torch.no_grad():
- output = model(token_ids)
- last_hidden_state = output[0].squeeze()
- for mask_index in masked_pos:
- mask_hidden_state = last_hidden_state[mask_index]
- idx = torch.topk(mask_hidden_state, k=100, dim=0)[1]
- words = [tokenizer.decode(i.item()).strip() for i in idx]
- st.text_area(label = 'Infill:', value=words)
\ No newline at end of file
diff --git a/spaces/CVH-vn1210/make_hair/minigpt4/datasets/datasets/base_dataset.py b/spaces/CVH-vn1210/make_hair/minigpt4/datasets/datasets/base_dataset.py
deleted file mode 100644
index e9e1c6f26f09adc3500ab7253cb555d54daf76ae..0000000000000000000000000000000000000000
--- a/spaces/CVH-vn1210/make_hair/minigpt4/datasets/datasets/base_dataset.py
+++ /dev/null
@@ -1,68 +0,0 @@
-"""
- Copyright (c) 2022, salesforce.com, inc.
- All rights reserved.
- SPDX-License-Identifier: BSD-3-Clause
- For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
-"""
-
-import json
-from typing import Iterable
-
-from torch.utils.data import Dataset, ConcatDataset
-from torch.utils.data.dataloader import default_collate
-
-
-class BaseDataset(Dataset):
- def __init__(
- self, vis_processor=None, text_processor=None, vis_root=None, ann_paths=[]
- ):
- """
- vis_root (string): Root directory of images (e.g. coco/images/)
- ann_root (string): directory to store the annotation file
- """
- self.vis_root = vis_root
-
- self.annotation = []
- for ann_path in ann_paths:
- self.annotation.extend(json.load(open(ann_path, "r"))['annotations'])
-
- self.vis_processor = vis_processor
- self.text_processor = text_processor
-
- self._add_instance_ids()
-
- def __len__(self):
- return len(self.annotation)
-
- def collater(self, samples):
- return default_collate(samples)
-
- def set_processors(self, vis_processor, text_processor):
- self.vis_processor = vis_processor
- self.text_processor = text_processor
-
- def _add_instance_ids(self, key="instance_id"):
- for idx, ann in enumerate(self.annotation):
- ann[key] = str(idx)
-
-
-class ConcatDataset(ConcatDataset):
- def __init__(self, datasets: Iterable[Dataset]) -> None:
- super().__init__(datasets)
-
- def collater(self, samples):
- # TODO For now only supports datasets with same underlying collater implementations
-
- all_keys = set()
- for s in samples:
- all_keys.update(s)
-
- shared_keys = all_keys
- for s in samples:
- shared_keys = shared_keys & set(s.keys())
-
- samples_shared_keys = []
- for s in samples:
- samples_shared_keys.append({k: s[k] for k in s.keys() if k in shared_keys})
-
- return self.datasets[0].collater(samples_shared_keys)
diff --git a/spaces/CVH-vn1210/make_hair/minigpt4/datasets/datasets/dataloader_utils.py b/spaces/CVH-vn1210/make_hair/minigpt4/datasets/datasets/dataloader_utils.py
deleted file mode 100644
index 3459972e5bda3e4a40788acf97ebe3c114fe7c3e..0000000000000000000000000000000000000000
--- a/spaces/CVH-vn1210/make_hair/minigpt4/datasets/datasets/dataloader_utils.py
+++ /dev/null
@@ -1,162 +0,0 @@
-"""
- Copyright (c) 2022, salesforce.com, inc.
- All rights reserved.
- SPDX-License-Identifier: BSD-3-Clause
- For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
-"""
-
-import time
-import random
-import torch
-from minigpt4.datasets.data_utils import move_to_cuda
-from torch.utils.data import DataLoader
-
-
-class MultiIterLoader:
- """
- A simple wrapper for iterating over multiple iterators.
-
- Args:
- loaders (List[Loader]): List of Iterator loaders.
- ratios (List[float]): List of ratios to sample from each loader. If None, all loaders are sampled uniformly.
- """
-
- def __init__(self, loaders, ratios=None):
- # assert all loaders has __next__ method
- for loader in loaders:
- assert hasattr(
- loader, "__next__"
- ), "Loader {} has no __next__ method.".format(loader)
-
- if ratios is None:
- ratios = [1.0] * len(loaders)
- else:
- assert len(ratios) == len(loaders)
- ratios = [float(ratio) / sum(ratios) for ratio in ratios]
-
- self.loaders = loaders
- self.ratios = ratios
-
- def __next__(self):
- # random sample from each loader by ratio
- loader_idx = random.choices(range(len(self.loaders)), self.ratios, k=1)[0]
- return next(self.loaders[loader_idx])
-
-
-class PrefetchLoader(object):
- """
- Modified from https://github.com/ChenRocks/UNITER.
-
- overlap compute and cuda data transfer
- (copied and then modified from nvidia apex)
- """
-
- def __init__(self, loader):
- self.loader = loader
- self.stream = torch.cuda.Stream()
-
- def __iter__(self):
- loader_it = iter(self.loader)
- self.preload(loader_it)
- batch = self.next(loader_it)
- while batch is not None:
- is_tuple = isinstance(batch, tuple)
- if is_tuple:
- task, batch = batch
-
- if is_tuple:
- yield task, batch
- else:
- yield batch
- batch = self.next(loader_it)
-
- def __len__(self):
- return len(self.loader)
-
- def preload(self, it):
- try:
- self.batch = next(it)
- except StopIteration:
- self.batch = None
- return
- # if record_stream() doesn't work, another option is to make sure
- # device inputs are created on the main stream.
- # self.next_input_gpu = torch.empty_like(self.next_input,
- # device='cuda')
- # self.next_target_gpu = torch.empty_like(self.next_target,
- # device='cuda')
- # Need to make sure the memory allocated for next_* is not still in use
- # by the main stream at the time we start copying to next_*:
- # self.stream.wait_stream(torch.cuda.current_stream())
- with torch.cuda.stream(self.stream):
- self.batch = move_to_cuda(self.batch)
- # more code for the alternative if record_stream() doesn't work:
- # copy_ will record the use of the pinned source tensor in this
- # side stream.
- # self.next_input_gpu.copy_(self.next_input, non_blocking=True)
- # self.next_target_gpu.copy_(self.next_target, non_blocking=True)
- # self.next_input = self.next_input_gpu
- # self.next_target = self.next_target_gpu
-
- def next(self, it):
- torch.cuda.current_stream().wait_stream(self.stream)
- batch = self.batch
- if batch is not None:
- record_cuda_stream(batch)
- self.preload(it)
- return batch
-
- def __getattr__(self, name):
- method = self.loader.__getattribute__(name)
- return method
-
-
-def record_cuda_stream(batch):
- if isinstance(batch, torch.Tensor):
- batch.record_stream(torch.cuda.current_stream())
- elif isinstance(batch, list) or isinstance(batch, tuple):
- for t in batch:
- record_cuda_stream(t)
- elif isinstance(batch, dict):
- for t in batch.values():
- record_cuda_stream(t)
- else:
- pass
-
-
-class IterLoader:
- """
- A wrapper to convert DataLoader as an infinite iterator.
-
- Modified from:
- https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/iter_based_runner.py
- """
-
- def __init__(self, dataloader: DataLoader, use_distributed: bool = False):
- self._dataloader = dataloader
- self.iter_loader = iter(self._dataloader)
- self._use_distributed = use_distributed
- self._epoch = 0
-
- @property
- def epoch(self) -> int:
- return self._epoch
-
- def __next__(self):
- try:
- data = next(self.iter_loader)
- except StopIteration:
- self._epoch += 1
- if hasattr(self._dataloader.sampler, "set_epoch") and self._use_distributed:
- self._dataloader.sampler.set_epoch(self._epoch)
- time.sleep(2) # Prevent possible deadlock during epoch transition
- self.iter_loader = iter(self._dataloader)
- data = next(self.iter_loader)
-
- return data
-
- def __iter__(self):
- return self
-
- def __len__(self):
- return len(self._dataloader)
diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/structures/keypoints.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/structures/keypoints.py
deleted file mode 100644
index 2242815f31dfe88aaabbf4b49f724c999a71912d..0000000000000000000000000000000000000000
--- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/structures/keypoints.py
+++ /dev/null
@@ -1,209 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-import numpy as np
-from typing import Any, List, Tuple, Union
-import torch
-
-from detectron2.layers import interpolate
-
-
-class Keypoints:
- """
- Stores keypoint annotation data. GT Instances have a `gt_keypoints` property
- containing the x,y location and visibility flag of each keypoint. This tensor has shape
- (N, K, 3) where N is the number of instances and K is the number of keypoints per instance.
-
- The visibility flag follows the COCO format and must be one of three integers:
- * v=0: not labeled (in which case x=y=0)
- * v=1: labeled but not visible
- * v=2: labeled and visible
- """
-
- def __init__(self, keypoints: Union[torch.Tensor, np.ndarray, List[List[float]]]):
- """
- Arguments:
- keypoints: A Tensor, numpy array, or list of the x, y, and visibility of each keypoint.
- The shape should be (N, K, 3) where N is the number of
- instances, and K is the number of keypoints per instance.
- """
- device = keypoints.device if isinstance(keypoints, torch.Tensor) else torch.device("cpu")
- keypoints = torch.as_tensor(keypoints, dtype=torch.float32, device=device)
- assert keypoints.dim() == 3 and keypoints.shape[2] == 3, keypoints.shape
- self.tensor = keypoints
-
- def __len__(self) -> int:
- return self.tensor.size(0)
-
- def to(self, *args: Any, **kwargs: Any) -> "Keypoints":
- return type(self)(self.tensor.to(*args, **kwargs))
-
- @property
- def device(self) -> torch.device:
- return self.tensor.device
-
- def to_heatmap(self, boxes: torch.Tensor, heatmap_size: int) -> torch.Tensor:
- """
- Arguments:
- boxes: Nx4 tensor, the boxes to draw the keypoints to
-
- Returns:
- heatmaps:
- A tensor of shape (N, K) containing an integer spatial label
- in the range [0, heatmap_size**2 - 1] for each keypoint in the input.
- valid:
- A tensor of shape (N, K) containing whether each keypoint is in the roi or not.
- """
- return _keypoints_to_heatmap(self.tensor, boxes, heatmap_size)
-
- def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "Keypoints":
- """
- Create a new `Keypoints` by indexing on this `Keypoints`.
-
- The following usage are allowed:
-
- 1. `new_kpts = kpts[3]`: return a `Keypoints` which contains only one instance.
- 2. `new_kpts = kpts[2:10]`: return a slice of key points.
- 3. `new_kpts = kpts[vector]`, where vector is a torch.ByteTensor
- with `length = len(kpts)`. Nonzero elements in the vector will be selected.
-
- Note that the returned Keypoints might share storage with this Keypoints,
- subject to Pytorch's indexing semantics.
- """
- if isinstance(item, int):
- return Keypoints([self.tensor[item]])
- return Keypoints(self.tensor[item])
-
- def __repr__(self) -> str:
- s = self.__class__.__name__ + "("
- s += "num_instances={})".format(len(self.tensor))
- return s
-
-
-# TODO make this nicer, this is a direct translation from C2 (but removing the inner loop)
-def _keypoints_to_heatmap(
- keypoints: torch.Tensor, rois: torch.Tensor, heatmap_size: int
-) -> Tuple[torch.Tensor, torch.Tensor]:
- """
- Encode keypoint locations into a target heatmap for use in SoftmaxWithLoss across space.
-
- Maps keypoints from the half-open interval [x1, x2) on continuous image coordinates to the
- closed interval [0, heatmap_size - 1] on discrete image coordinates. We use the
- continuous-discrete conversion from Heckbert 1990 ("What is the coordinate of a pixel?"):
- d = floor(c) and c = d + 0.5, where d is a discrete coordinate and c is a continuous coordinate.
-
- Arguments:
- keypoints: tensor of keypoint locations in of shape (N, K, 3).
- rois: Nx4 tensor of rois in xyxy format
- heatmap_size: integer side length of square heatmap.
-
- Returns:
- heatmaps: A tensor of shape (N, K) containing an integer spatial label
- in the range [0, heatmap_size**2 - 1] for each keypoint in the input.
- valid: A tensor of shape (N, K) containing whether each keypoint is in
- the roi or not.
- """
-
- if rois.numel() == 0:
- return rois.new().long(), rois.new().long()
- offset_x = rois[:, 0]
- offset_y = rois[:, 1]
- scale_x = heatmap_size / (rois[:, 2] - rois[:, 0])
- scale_y = heatmap_size / (rois[:, 3] - rois[:, 1])
-
- offset_x = offset_x[:, None]
- offset_y = offset_y[:, None]
- scale_x = scale_x[:, None]
- scale_y = scale_y[:, None]
-
- x = keypoints[..., 0]
- y = keypoints[..., 1]
-
- x_boundary_inds = x == rois[:, 2][:, None]
- y_boundary_inds = y == rois[:, 3][:, None]
-
- x = (x - offset_x) * scale_x
- x = x.floor().long()
- y = (y - offset_y) * scale_y
- y = y.floor().long()
-
- x[x_boundary_inds] = heatmap_size - 1
- y[y_boundary_inds] = heatmap_size - 1
-
- valid_loc = (x >= 0) & (y >= 0) & (x < heatmap_size) & (y < heatmap_size)
- vis = keypoints[..., 2] > 0
- valid = (valid_loc & vis).long()
-
- lin_ind = y * heatmap_size + x
- heatmaps = lin_ind * valid
-
- return heatmaps, valid
-
-
-@torch.no_grad()
-def heatmaps_to_keypoints(maps: torch.Tensor, rois: torch.Tensor) -> torch.Tensor:
- """
- Extract predicted keypoint locations from heatmaps.
-
- Args:
- maps (Tensor): (#ROIs, #keypoints, POOL_H, POOL_W). The predicted heatmap of logits for
- each ROI and each keypoint.
- rois (Tensor): (#ROIs, 4). The box of each ROI.
-
- Returns:
- Tensor of shape (#ROIs, #keypoints, 4) with the last dimension corresponding to
- (x, y, logit, score) for each keypoint.
-
- When converting discrete pixel indices in an NxN image to a continuous keypoint coordinate,
- we maintain consistency with :meth:`Keypoints.to_heatmap` by using the conversion from
- Heckbert 1990: c = d + 0.5, where d is a discrete coordinate and c is a continuous coordinate.
- """
- offset_x = rois[:, 0]
- offset_y = rois[:, 1]
-
- widths = (rois[:, 2] - rois[:, 0]).clamp(min=1)
- heights = (rois[:, 3] - rois[:, 1]).clamp(min=1)
- widths_ceil = widths.ceil()
- heights_ceil = heights.ceil()
-
- num_rois, num_keypoints = maps.shape[:2]
- xy_preds = maps.new_zeros(rois.shape[0], num_keypoints, 4)
-
- width_corrections = widths / widths_ceil
- height_corrections = heights / heights_ceil
-
- keypoints_idx = torch.arange(num_keypoints, device=maps.device)
-
- for i in range(num_rois):
- outsize = (int(heights_ceil[i]), int(widths_ceil[i]))
- roi_map = interpolate(maps[[i]], size=outsize, mode="bicubic", align_corners=False).squeeze(
- 0
- ) # #keypoints x H x W
-
- # softmax over the spatial region
- max_score, _ = roi_map.view(num_keypoints, -1).max(1)
- max_score = max_score.view(num_keypoints, 1, 1)
- tmp_full_resolution = (roi_map - max_score).exp_()
- tmp_pool_resolution = (maps[i] - max_score).exp_()
- # Produce scores over the region H x W, but normalize with POOL_H x POOL_W,
- # so that the scores of objects of different absolute sizes will be more comparable
- roi_map_scores = tmp_full_resolution / tmp_pool_resolution.sum((1, 2), keepdim=True)
-
- w = roi_map.shape[2]
- pos = roi_map.view(num_keypoints, -1).argmax(1)
-
- x_int = pos % w
- y_int = (pos - x_int) // w
-
- assert (
- roi_map_scores[keypoints_idx, y_int, x_int]
- == roi_map_scores.view(num_keypoints, -1).max(1)[0]
- ).all()
-
- x = (x_int.float() + 0.5) * width_corrections[i]
- y = (y_int.float() + 0.5) * height_corrections[i]
-
- xy_preds[i, :, 0] = x + offset_x[i]
- xy_preds[i, :, 1] = y + offset_y[i]
- xy_preds[i, :, 2] = roi_map[keypoints_idx, y_int, x_int]
- xy_preds[i, :, 3] = roi_map_scores[keypoints_idx, y_int, x_int]
-
- return xy_preds
diff --git a/spaces/CVPR/LIVE/thrust/thrust/iterator/counting_iterator.h b/spaces/CVPR/LIVE/thrust/thrust/iterator/counting_iterator.h
deleted file mode 100644
index 25d495db05ee3d18467ef7975147a839086bfe4a..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/iterator/counting_iterator.h
+++ /dev/null
@@ -1,247 +0,0 @@
-/*
- * Copyright 2008-2013 NVIDIA Corporation
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-
-/*! \file thrust/iterator/counting_iterator.h
- * \brief An iterator which returns an increasing incrementable value
- * when dereferenced
- */
-
-/*
- * Copyright David Abrahams 2003.
- *
- * Distributed under the Boost Software License, Version 1.0.
- * (See accompanying NOTICE file for the complete license)
- *
- * For more information, see http://www.boost.org
- */
-
-#pragma once
-
-#include
-#include
-#include
-#include
-
-// #include the details first
-#include
-
-namespace thrust
-{
-
-/*! \addtogroup iterators
- * \{
- */
-
-/*! \addtogroup fancyiterator Fancy Iterators
- * \ingroup iterators
- * \{
- */
-
-/*! \p counting_iterator is an iterator which represents a pointer into a range
- * of sequentially changing values. This iterator is useful for creating a range
- * filled with a sequence without explicitly storing it in memory. Using
- * \p counting_iterator saves memory capacity and bandwidth.
- *
- * The following code snippet demonstrates how to create a \p counting_iterator whose
- * \c value_type is \c int and which sequentially increments by \c 1.
- *
- * \code
- * #include
- * ...
- * // create iterators
- * thrust::counting_iterator first(10);
- * thrust::counting_iterator last = first + 3;
- *
- * first[0] // returns 10
- * first[1] // returns 11
- * first[100] // returns 110
- *
- * // sum of [first, last)
- * thrust::reduce(first, last); // returns 33 (i.e. 10 + 11 + 12)
- *
- * // initialize vector to [0,1,2,..]
- * thrust::counting_iterator iter(0);
- * thrust::device_vector vec(500);
- * thrust::copy(iter, iter + vec.size(), vec.begin());
- * \endcode
- *
- * This next example demonstrates how to use a \p counting_iterator with the
- * \p thrust::copy_if function to compute the indices of the non-zero elements
- * of a \p device_vector. In this example, we use the \p make_counting_iterator
- * function to avoid specifying the type of the \p counting_iterator.
- *
- * \code
- * #include
- * #include
- * #include
- * #include
- *
- * int main()
- * {
- * // this example computes indices for all the nonzero values in a sequence
- *
- * // sequence of zero and nonzero values
- * thrust::device_vector stencil(8);
- * stencil[0] = 0;
- * stencil[1] = 1;
- * stencil[2] = 1;
- * stencil[3] = 0;
- * stencil[4] = 0;
- * stencil[5] = 1;
- * stencil[6] = 0;
- * stencil[7] = 1;
- *
- * // storage for the nonzero indices
- * thrust::device_vector indices(8);
- *
- * // compute indices of nonzero elements
- * typedef thrust::device_vector::iterator IndexIterator;
- *
- * // use make_counting_iterator to define the sequence [0, 8)
- * IndexIterator indices_end = thrust::copy_if(thrust::make_counting_iterator(0),
- * thrust::make_counting_iterator(8),
- * stencil.begin(),
- * indices.begin(),
- * thrust::identity());
- * // indices now contains [1,2,5,7]
- *
- * return 0;
- * }
- * \endcode
- *
- * \see make_counting_iterator
- */
-template
- class counting_iterator
- : public detail::counting_iterator_base::type
-{
- /*! \cond
- */
- typedef typename detail::counting_iterator_base::type super_t;
-
- friend class thrust::iterator_core_access;
-
- public:
- typedef typename super_t::reference reference;
- typedef typename super_t::difference_type difference_type;
-
- /*! \endcond
- */
-
- /*! Null constructor initializes this \p counting_iterator's \c Incrementable
- * counter using its null constructor.
- */
- __host__ __device__
- counting_iterator() {}
-
- /*! Copy constructor copies the value of another \p counting_iterator into a
- * new \p counting_iterator.
- *
- * \p rhs The \p counting_iterator to copy.
- */
- __host__ __device__
- counting_iterator(counting_iterator const &rhs):super_t(rhs.base()){}
-
- /*! Copy constructor copies the value of another counting_iterator
- * with related System type.
- *
- * \param rhs The \p counting_iterator to copy.
- */
- template
- __host__ __device__
- counting_iterator(counting_iterator const &rhs,
- typename thrust::detail::enable_if_convertible<
- typename thrust::iterator_system >::type,
- typename thrust::iterator_system::type
- >::type * = 0)
- : super_t(rhs.base()){}
-
- /*! This \c explicit constructor copies the value of an \c Incrementable
- * into a new \p counting_iterator's \c Incrementable counter.
- *
- * \param x The initial value of the new \p counting_iterator's \c Incrementable
- * counter.
- */
- __host__ __device__
- explicit counting_iterator(Incrementable x):super_t(x){}
-
-#if THRUST_CPP_DIALECT >= 2011
- counting_iterator & operator=(const counting_iterator &) = default;
-#endif
-
- /*! \cond
- */
- private:
- __host__ __device__
- reference dereference() const
- {
- return this->base_reference();
- }
-
- // note that we implement equal specially for floating point counting_iterator
- template
- __host__ __device__
- bool equal(counting_iterator const& y) const
- {
- typedef thrust::detail::counting_iterator_equal e;
- return e::equal(this->base(), y.base());
- }
-
- template
- __host__ __device__
- difference_type
- distance_to(counting_iterator const& y) const
- {
- typedef typename
- thrust::detail::eval_if<
- thrust::detail::is_numeric::value,
- thrust::detail::identity_ >,
- thrust::detail::identity_ >
- >::type d;
-
- return d::distance(this->base(), y.base());
- }
-
- /*! \endcond
- */
-}; // end counting_iterator
-
-
-/*! \p make_counting_iterator creates a \p counting_iterator
- * using an initial value for its \c Incrementable counter.
- *
- * \param x The initial value of the new \p counting_iterator's counter.
- * \return A new \p counting_iterator whose counter has been initialized to \p x.
- */
-template
-inline __host__ __device__
-counting_iterator make_counting_iterator(Incrementable x)
-{
- return counting_iterator(x);
-}
-
-/*! \} // end fancyiterators
- */
-
-/*! \} // end iterators
- */
-
-} // end thrust
-
diff --git a/spaces/CVPR/LIVE/thrust/thrust/system/cpp/detail/generate.h b/spaces/CVPR/LIVE/thrust/thrust/system/cpp/detail/generate.h
deleted file mode 100644
index c6ae90664ad9538e73febfde86c334011de417c8..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/system/cpp/detail/generate.h
+++ /dev/null
@@ -1,22 +0,0 @@
-/*
- * Copyright 2008-2013 NVIDIA Corporation
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#pragma once
-
-#include
-
-// this system has no special version of this algorithm
-
diff --git a/spaces/CVPR/lama-example/saicinpainting/__init__.py b/spaces/CVPR/lama-example/saicinpainting/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/CVPR/regionclip-demo/detectron2/export/torchscript.py b/spaces/CVPR/regionclip-demo/detectron2/export/torchscript.py
deleted file mode 100644
index 480451a9df7ae42958b93150fd2156ee4029f2a7..0000000000000000000000000000000000000000
--- a/spaces/CVPR/regionclip-demo/detectron2/export/torchscript.py
+++ /dev/null
@@ -1,133 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import os
-import torch
-
-from detectron2.utils.env import TORCH_VERSION
-from detectron2.utils.file_io import PathManager
-
-from .torchscript_patch import freeze_training_mode, patch_instances
-
-__all__ = ["scripting_with_instances", "dump_torchscript_IR"]
-
-
-def scripting_with_instances(model, fields):
- """
- Run :func:`torch.jit.script` on a model that uses the :class:`Instances` class. Since
- attributes of :class:`Instances` are "dynamically" added in eager mode，it is difficult
- for scripting to support it out of the box. This function is made to support scripting
- a model that uses :class:`Instances`. It does the following:
-
- 1. Create a scriptable ``new_Instances`` class which behaves similarly to ``Instances``,
- but with all attributes been "static".
- The attributes need to be statically declared in the ``fields`` argument.
- 2. Register ``new_Instances``, and force scripting compiler to
- use it when trying to compile ``Instances``.
-
- After this function, the process will be reverted. User should be able to script another model
- using different fields.
-
- Example:
- Assume that ``Instances`` in the model consist of two attributes named
- ``proposal_boxes`` and ``objectness_logits`` with type :class:`Boxes` and
- :class:`Tensor` respectively during inference. You can call this function like:
- ::
- fields = {"proposal_boxes": Boxes, "objectness_logits": torch.Tensor}
- torchscipt_model = scripting_with_instances(model, fields)
-
- Note:
- It only support models in evaluation mode.
-
- Args:
- model (nn.Module): The input model to be exported by scripting.
- fields (Dict[str, type]): Attribute names and corresponding type that
- ``Instances`` will use in the model. Note that all attributes used in ``Instances``
- need to be added, regardless of whether they are inputs/outputs of the model.
- Data type not defined in detectron2 is not supported for now.
-
- Returns:
- torch.jit.ScriptModule: the model in torchscript format
- """
- assert TORCH_VERSION >= (1, 8), "This feature is not available in PyTorch < 1.8"
- assert (
- not model.training
- ), "Currently we only support exporting models in evaluation mode to torchscript"
-
- with freeze_training_mode(model), patch_instances(fields):
- scripted_model = torch.jit.script(model)
- return scripted_model
-
-
-# alias for old name
-export_torchscript_with_instances = scripting_with_instances
-
-
-def dump_torchscript_IR(model, dir):
- """
- Dump IR of a TracedModule/ScriptModule/Function in various format (code, graph,
- inlined graph). Useful for debugging.
-
- Args:
- model (TracedModule/ScriptModule/ScriptFUnction): traced or scripted module
- dir (str): output directory to dump files.
- """
- PathManager.mkdirs(dir)
-
- def _get_script_mod(mod):
- if isinstance(mod, torch.jit.TracedModule):
- return mod._actual_script_module
- return mod
-
- # Dump pretty-printed code: https://pytorch.org/docs/stable/jit.html#inspecting-code
- with PathManager.open(os.path.join(dir, "model_ts_code.txt"), "w") as f:
-
- def get_code(mod):
- # Try a few ways to get code using private attributes.
- try:
- # This contains more information than just `mod.code`
- return _get_script_mod(mod)._c.code
- except AttributeError:
- pass
- try:
- return mod.code
- except AttributeError:
- return None
-
- def dump_code(prefix, mod):
- code = get_code(mod)
- name = prefix or "root model"
- if code is None:
- f.write(f"Could not found code for {name} (type={mod.original_name})\n")
- f.write("\n")
- else:
- f.write(f"\nCode for {name}, type={mod.original_name}:\n")
- f.write(code)
- f.write("\n")
- f.write("-" * 80)
-
- for name, m in mod.named_children():
- dump_code(prefix + "." + name, m)
-
- if isinstance(model, torch.jit.ScriptFunction):
- f.write(get_code(model))
- else:
- dump_code("", model)
-
- def _get_graph(model):
- try:
- # Recursively dump IR of all modules
- return _get_script_mod(model)._c.dump_to_str(True, False, False)
- except AttributeError:
- return model.graph.str()
-
- with PathManager.open(os.path.join(dir, "model_ts_IR.txt"), "w") as f:
- f.write(_get_graph(model))
-
- # Dump IR of the entire graph (all submodules inlined)
- with PathManager.open(os.path.join(dir, "model_ts_IR_inlined.txt"), "w") as f:
- f.write(str(model.inlined_graph))
-
- if not isinstance(model, torch.jit.ScriptFunction):
- # Dump the model structure in pytorch style
- with PathManager.open(os.path.join(dir, "model.txt"), "w") as f:
- f.write(str(model))
diff --git a/spaces/CVPR/regionclip-demo/detectron2/modeling/backbone/resnet.py b/spaces/CVPR/regionclip-demo/detectron2/modeling/backbone/resnet.py
deleted file mode 100644
index 5b8e842c585a81b5345ade4ca1da62a4904a122a..0000000000000000000000000000000000000000
--- a/spaces/CVPR/regionclip-demo/detectron2/modeling/backbone/resnet.py
+++ /dev/null
@@ -1,694 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import numpy as np
-import fvcore.nn.weight_init as weight_init
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from detectron2.layers import (
- CNNBlockBase,
- Conv2d,
- DeformConv,
- ModulatedDeformConv,
- ShapeSpec,
- get_norm,
-)
-
-from .backbone import Backbone
-from .build import BACKBONE_REGISTRY
-
-__all__ = [
- "ResNetBlockBase",
- "BasicBlock",
- "BottleneckBlock",
- "DeformBottleneckBlock",
- "BasicStem",
- "ResNet",
- "make_stage",
- "build_resnet_backbone",
-]
-
-
-class BasicBlock(CNNBlockBase):
- """
- The basic residual block for ResNet-18 and ResNet-34 defined in :paper:`ResNet`,
- with two 3x3 conv layers and a projection shortcut if needed.
- """
-
- def __init__(self, in_channels, out_channels, *, stride=1, norm="BN"):
- """
- Args:
- in_channels (int): Number of input channels.
- out_channels (int): Number of output channels.
- stride (int): Stride for the first conv.
- norm (str or callable): normalization for all conv layers.
- See :func:`layers.get_norm` for supported format.
- """
- super().__init__(in_channels, out_channels, stride)
-
- if in_channels != out_channels:
- self.shortcut = Conv2d(
- in_channels,
- out_channels,
- kernel_size=1,
- stride=stride,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
- else:
- self.shortcut = None
-
- self.conv1 = Conv2d(
- in_channels,
- out_channels,
- kernel_size=3,
- stride=stride,
- padding=1,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
-
- self.conv2 = Conv2d(
- out_channels,
- out_channels,
- kernel_size=3,
- stride=1,
- padding=1,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
-
- for layer in [self.conv1, self.conv2, self.shortcut]:
- if layer is not None: # shortcut can be None
- weight_init.c2_msra_fill(layer)
-
- def forward(self, x):
- out = self.conv1(x)
- out = F.relu_(out)
- out = self.conv2(out)
-
- if self.shortcut is not None:
- shortcut = self.shortcut(x)
- else:
- shortcut = x
-
- out += shortcut
- out = F.relu_(out)
- return out
-
-
-class BottleneckBlock(CNNBlockBase):
- """
- The standard bottleneck residual block used by ResNet-50, 101 and 152
- defined in :paper:`ResNet`. It contains 3 conv layers with kernels
- 1x1, 3x3, 1x1, and a projection shortcut if needed.
- """
-
- def __init__(
- self,
- in_channels,
- out_channels,
- *,
- bottleneck_channels,
- stride=1,
- num_groups=1,
- norm="BN",
- stride_in_1x1=False,
- dilation=1,
- ):
- """
- Args:
- bottleneck_channels (int): number of output channels for the 3x3
- "bottleneck" conv layers.
- num_groups (int): number of groups for the 3x3 conv layer.
- norm (str or callable): normalization for all conv layers.
- See :func:`layers.get_norm` for supported format.
- stride_in_1x1 (bool): when stride>1, whether to put stride in the
- first 1x1 convolution or the bottleneck 3x3 convolution.
- dilation (int): the dilation rate of the 3x3 conv layer.
- """
- super().__init__(in_channels, out_channels, stride)
-
- if in_channels != out_channels:
- self.shortcut = Conv2d(
- in_channels,
- out_channels,
- kernel_size=1,
- stride=stride,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
- else:
- self.shortcut = None
-
- # The original MSRA ResNet models have stride in the first 1x1 conv
- # The subsequent fb.torch.resnet and Caffe2 ResNe[X]t implementations have
- # stride in the 3x3 conv
- stride_1x1, stride_3x3 = (stride, 1) if stride_in_1x1 else (1, stride)
-
- self.conv1 = Conv2d(
- in_channels,
- bottleneck_channels,
- kernel_size=1,
- stride=stride_1x1,
- bias=False,
- norm=get_norm(norm, bottleneck_channels),
- )
-
- self.conv2 = Conv2d(
- bottleneck_channels,
- bottleneck_channels,
- kernel_size=3,
- stride=stride_3x3,
- padding=1 * dilation,
- bias=False,
- groups=num_groups,
- dilation=dilation,
- norm=get_norm(norm, bottleneck_channels),
- )
-
- self.conv3 = Conv2d(
- bottleneck_channels,
- out_channels,
- kernel_size=1,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
-
- for layer in [self.conv1, self.conv2, self.conv3, self.shortcut]:
- if layer is not None: # shortcut can be None
- weight_init.c2_msra_fill(layer)
-
- # Zero-initialize the last normalization in each residual branch,
- # so that at the beginning, the residual branch starts with zeros,
- # and each residual block behaves like an identity.
- # See Sec 5.1 in "Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour":
- # "For BN layers, the learnable scaling coefficient γ is initialized
- # to be 1, except for each residual block's last BN
- # where γ is initialized to be 0."
-
- # nn.init.constant_(self.conv3.norm.weight, 0)
- # TODO this somehow hurts performance when training GN models from scratch.
- # Add it as an option when we need to use this code to train a backbone.
-
- def forward(self, x):
- out = self.conv1(x)
- out = F.relu_(out)
-
- out = self.conv2(out)
- out = F.relu_(out)
-
- out = self.conv3(out)
-
- if self.shortcut is not None:
- shortcut = self.shortcut(x)
- else:
- shortcut = x
-
- out += shortcut
- out = F.relu_(out)
- return out
-
-
-class DeformBottleneckBlock(CNNBlockBase):
- """
- Similar to :class:`BottleneckBlock`, but with :paper:`deformable conv `
- in the 3x3 convolution.
- """
-
- def __init__(
- self,
- in_channels,
- out_channels,
- *,
- bottleneck_channels,
- stride=1,
- num_groups=1,
- norm="BN",
- stride_in_1x1=False,
- dilation=1,
- deform_modulated=False,
- deform_num_groups=1,
- ):
- super().__init__(in_channels, out_channels, stride)
- self.deform_modulated = deform_modulated
-
- if in_channels != out_channels:
- self.shortcut = Conv2d(
- in_channels,
- out_channels,
- kernel_size=1,
- stride=stride,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
- else:
- self.shortcut = None
-
- stride_1x1, stride_3x3 = (stride, 1) if stride_in_1x1 else (1, stride)
-
- self.conv1 = Conv2d(
- in_channels,
- bottleneck_channels,
- kernel_size=1,
- stride=stride_1x1,
- bias=False,
- norm=get_norm(norm, bottleneck_channels),
- )
-
- if deform_modulated:
- deform_conv_op = ModulatedDeformConv
- # offset channels are 2 or 3 (if with modulated) * kernel_size * kernel_size
- offset_channels = 27
- else:
- deform_conv_op = DeformConv
- offset_channels = 18
-
- self.conv2_offset = Conv2d(
- bottleneck_channels,
- offset_channels * deform_num_groups,
- kernel_size=3,
- stride=stride_3x3,
- padding=1 * dilation,
- dilation=dilation,
- )
- self.conv2 = deform_conv_op(
- bottleneck_channels,
- bottleneck_channels,
- kernel_size=3,
- stride=stride_3x3,
- padding=1 * dilation,
- bias=False,
- groups=num_groups,
- dilation=dilation,
- deformable_groups=deform_num_groups,
- norm=get_norm(norm, bottleneck_channels),
- )
-
- self.conv3 = Conv2d(
- bottleneck_channels,
- out_channels,
- kernel_size=1,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
-
- for layer in [self.conv1, self.conv2, self.conv3, self.shortcut]:
- if layer is not None: # shortcut can be None
- weight_init.c2_msra_fill(layer)
-
- nn.init.constant_(self.conv2_offset.weight, 0)
- nn.init.constant_(self.conv2_offset.bias, 0)
-
- def forward(self, x):
- out = self.conv1(x)
- out = F.relu_(out)
-
- if self.deform_modulated:
- offset_mask = self.conv2_offset(out)
- offset_x, offset_y, mask = torch.chunk(offset_mask, 3, dim=1)
- offset = torch.cat((offset_x, offset_y), dim=1)
- mask = mask.sigmoid()
- out = self.conv2(out, offset, mask)
- else:
- offset = self.conv2_offset(out)
- out = self.conv2(out, offset)
- out = F.relu_(out)
-
- out = self.conv3(out)
-
- if self.shortcut is not None:
- shortcut = self.shortcut(x)
- else:
- shortcut = x
-
- out += shortcut
- out = F.relu_(out)
- return out
-
-
-class BasicStem(CNNBlockBase):
- """
- The standard ResNet stem (layers before the first residual block),
- with a conv, relu and max_pool.
- """
-
- def __init__(self, in_channels=3, out_channels=64, norm="BN"):
- """
- Args:
- norm (str or callable): norm after the first conv layer.
- See :func:`layers.get_norm` for supported format.
- """
- super().__init__(in_channels, out_channels, 4)
- self.in_channels = in_channels
- self.conv1 = Conv2d(
- in_channels,
- out_channels,
- kernel_size=7,
- stride=2,
- padding=3,
- bias=False,
- norm=get_norm(norm, out_channels),
- )
- weight_init.c2_msra_fill(self.conv1)
-
- def forward(self, x):
- x = self.conv1(x)
- x = F.relu_(x)
- x = F.max_pool2d(x, kernel_size=3, stride=2, padding=1)
- return x
-
-
-class ResNet(Backbone):
- """
- Implement :paper:`ResNet`.
- """
-
- def __init__(self, stem, stages, num_classes=None, out_features=None, freeze_at=0):
- """
- Args:
- stem (nn.Module): a stem module
- stages (list[list[CNNBlockBase]]): several (typically 4) stages,
- each contains multiple :class:`CNNBlockBase`.
- num_classes (None or int): if None, will not perform classification.
- Otherwise, will create a linear layer.
- out_features (list[str]): name of the layers whose outputs should
- be returned in forward. Can be anything in "stem", "linear", or "res2" ...
- If None, will return the output of the last layer.
- freeze_at (int): The number of stages at the beginning to freeze.
- see :meth:`freeze` for detailed explanation.
- """
- super().__init__()
- self.stem = stem
- self.num_classes = num_classes
-
- current_stride = self.stem.stride
- self._out_feature_strides = {"stem": current_stride}
- self._out_feature_channels = {"stem": self.stem.out_channels}
-
- self.stage_names, self.stages = [], []
-
- if out_features is not None:
- # Avoid keeping unused layers in this module. They consume extra memory
- # and may cause allreduce to fail
- num_stages = max(
- [{"res2": 1, "res3": 2, "res4": 3, "res5": 4}.get(f, 0) for f in out_features]
- )
- stages = stages[:num_stages]
- for i, blocks in enumerate(stages):
- assert len(blocks) > 0, len(blocks)
- for block in blocks:
- assert isinstance(block, CNNBlockBase), block
-
- name = "res" + str(i + 2)
- stage = nn.Sequential(*blocks)
-
- self.add_module(name, stage)
- self.stage_names.append(name)
- self.stages.append(stage)
-
- self._out_feature_strides[name] = current_stride = int(
- current_stride * np.prod([k.stride for k in blocks])
- )
- self._out_feature_channels[name] = curr_channels = blocks[-1].out_channels
- self.stage_names = tuple(self.stage_names) # Make it static for scripting
-
- if num_classes is not None:
- self.avgpool = nn.AdaptiveAvgPool2d((1, 1))
- self.linear = nn.Linear(curr_channels, num_classes)
-
- # Sec 5.1 in "Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour":
- # "The 1000-way fully-connected layer is initialized by
- # drawing weights from a zero-mean Gaussian with standard deviation of 0.01."
- nn.init.normal_(self.linear.weight, std=0.01)
- name = "linear"
-
- if out_features is None:
- out_features = [name]
- self._out_features = out_features
- assert len(self._out_features)
- children = [x[0] for x in self.named_children()]
- for out_feature in self._out_features:
- assert out_feature in children, "Available children: {}".format(", ".join(children))
- self.freeze(freeze_at)
-
- def forward(self, x):
- """
- Args:
- x: Tensor of shape (N,C,H,W). H, W must be a multiple of ``self.size_divisibility``.
-
- Returns:
- dict[str->Tensor]: names and the corresponding features
- """
- assert x.dim() == 4, f"ResNet takes an input of shape (N, C, H, W). Got {x.shape} instead!"
- outputs = {}
- x = self.stem(x)
- if "stem" in self._out_features:
- outputs["stem"] = x
- for name, stage in zip(self.stage_names, self.stages):
- x = stage(x)
- if name in self._out_features:
- outputs[name] = x
- if self.num_classes is not None:
- x = self.avgpool(x)
- x = torch.flatten(x, 1)
- x = self.linear(x)
- if "linear" in self._out_features:
- outputs["linear"] = x
- return outputs
-
- def output_shape(self):
- return {
- name: ShapeSpec(
- channels=self._out_feature_channels[name], stride=self._out_feature_strides[name]
- )
- for name in self._out_features
- }
-
- def freeze(self, freeze_at=0):
- """
- Freeze the first several stages of the ResNet. Commonly used in
- fine-tuning.
-
- Layers that produce the same feature map spatial size are defined as one
- "stage" by :paper:`FPN`.
-
- Args:
- freeze_at (int): number of stages to freeze.
- `1` means freezing the stem. `2` means freezing the stem and
- one residual stage, etc.
-
- Returns:
- nn.Module: this ResNet itself
- """
- if freeze_at >= 1:
- self.stem.freeze()
- for idx, stage in enumerate(self.stages, start=2):
- if freeze_at >= idx:
- for block in stage.children():
- block.freeze()
- return self
-
- @staticmethod
- def make_stage(block_class, num_blocks, *, in_channels, out_channels, **kwargs):
- """
- Create a list of blocks of the same type that forms one ResNet stage.
-
- Args:
- block_class (type): a subclass of CNNBlockBase that's used to create all blocks in this
- stage. A module of this type must not change spatial resolution of inputs unless its
- stride != 1.
- num_blocks (int): number of blocks in this stage
- in_channels (int): input channels of the entire stage.
- out_channels (int): output channels of **every block** in the stage.
- kwargs: other arguments passed to the constructor of
- `block_class`. If the argument name is "xx_per_block", the
- argument is a list of values to be passed to each block in the
- stage. Otherwise, the same argument is passed to every block
- in the stage.
-
- Returns:
- list[CNNBlockBase]: a list of block module.
-
- Examples:
- ::
- stage = ResNet.make_stage(
- BottleneckBlock, 3, in_channels=16, out_channels=64,
- bottleneck_channels=16, num_groups=1,
- stride_per_block=[2, 1, 1],
- dilations_per_block=[1, 1, 2]
- )
-
- Usually, layers that produce the same feature map spatial size are defined as one
- "stage" (in :paper:`FPN`). Under such definition, ``stride_per_block[1:]`` should
- all be 1.
- """
- blocks = []
- for i in range(num_blocks):
- curr_kwargs = {}
- for k, v in kwargs.items():
- if k.endswith("_per_block"):
- assert len(v) == num_blocks, (
- f"Argument '{k}' of make_stage should have the "
- f"same length as num_blocks={num_blocks}."
- )
- newk = k[: -len("_per_block")]
- assert newk not in kwargs, f"Cannot call make_stage with both {k} and {newk}!"
- curr_kwargs[newk] = v[i]
- else:
- curr_kwargs[k] = v
-
- blocks.append(
- block_class(in_channels=in_channels, out_channels=out_channels, **curr_kwargs)
- )
- in_channels = out_channels
- return blocks
-
- @staticmethod
- def make_default_stages(depth, block_class=None, **kwargs):
- """
- Created list of ResNet stages from pre-defined depth (one of 18, 34, 50, 101, 152).
- If it doesn't create the ResNet variant you need, please use :meth:`make_stage`
- instead for fine-grained customization.
-
- Args:
- depth (int): depth of ResNet
- block_class (type): the CNN block class. Has to accept
- `bottleneck_channels` argument for depth > 50.
- By default it is BasicBlock or BottleneckBlock, based on the
- depth.
- kwargs:
- other arguments to pass to `make_stage`. Should not contain
- stride and channels, as they are predefined for each depth.
-
- Returns:
- list[list[CNNBlockBase]]: modules in all stages; see arguments of
- :class:`ResNet.__init__`.
- """
- num_blocks_per_stage = {
- 18: [2, 2, 2, 2],
- 34: [3, 4, 6, 3],
- 50: [3, 4, 6, 3],
- 101: [3, 4, 23, 3],
- 152: [3, 8, 36, 3],
- }[depth]
- if block_class is None:
- block_class = BasicBlock if depth < 50 else BottleneckBlock
- if depth < 50:
- in_channels = [64, 64, 128, 256]
- out_channels = [64, 128, 256, 512]
- else:
- in_channels = [64, 256, 512, 1024]
- out_channels = [256, 512, 1024, 2048]
- ret = []
- for (n, s, i, o) in zip(num_blocks_per_stage, [1, 2, 2, 2], in_channels, out_channels):
- if depth >= 50:
- kwargs["bottleneck_channels"] = o // 4
- ret.append(
- ResNet.make_stage(
- block_class=block_class,
- num_blocks=n,
- stride_per_block=[s] + [1] * (n - 1),
- in_channels=i,
- out_channels=o,
- **kwargs,
- )
- )
- return ret
-
-
-ResNetBlockBase = CNNBlockBase
-"""
-Alias for backward compatibiltiy.
-"""
-
-
-def make_stage(*args, **kwargs):
- """
- Deprecated alias for backward compatibiltiy.
- """
- return ResNet.make_stage(*args, **kwargs)
-
-
-@BACKBONE_REGISTRY.register()
-def build_resnet_backbone(cfg, input_shape):
- """
- Create a ResNet instance from config.
-
- Returns:
- ResNet: a :class:`ResNet` instance.
- """
- # need registration of new blocks/stems?
- norm = cfg.MODEL.RESNETS.NORM
- stem = BasicStem(
- in_channels=input_shape.channels,
- out_channels=cfg.MODEL.RESNETS.STEM_OUT_CHANNELS,
- norm=norm,
- )
-
- # fmt: off
- freeze_at = cfg.MODEL.BACKBONE.FREEZE_AT
- out_features = cfg.MODEL.RESNETS.OUT_FEATURES
- depth = cfg.MODEL.RESNETS.DEPTH
- num_groups = cfg.MODEL.RESNETS.NUM_GROUPS
- width_per_group = cfg.MODEL.RESNETS.WIDTH_PER_GROUP
- bottleneck_channels = num_groups * width_per_group
- in_channels = cfg.MODEL.RESNETS.STEM_OUT_CHANNELS
- out_channels = cfg.MODEL.RESNETS.RES2_OUT_CHANNELS
- stride_in_1x1 = cfg.MODEL.RESNETS.STRIDE_IN_1X1
- res5_dilation = cfg.MODEL.RESNETS.RES5_DILATION
- deform_on_per_stage = cfg.MODEL.RESNETS.DEFORM_ON_PER_STAGE
- deform_modulated = cfg.MODEL.RESNETS.DEFORM_MODULATED
- deform_num_groups = cfg.MODEL.RESNETS.DEFORM_NUM_GROUPS
- # fmt: on
- assert res5_dilation in {1, 2}, "res5_dilation cannot be {}.".format(res5_dilation)
-
- num_blocks_per_stage = {
- 18: [2, 2, 2, 2],
- 34: [3, 4, 6, 3],
- 50: [3, 4, 6, 3],
- 101: [3, 4, 23, 3],
- 152: [3, 8, 36, 3],
- }[depth]
-
- if depth in [18, 34]:
- assert out_channels == 64, "Must set MODEL.RESNETS.RES2_OUT_CHANNELS = 64 for R18/R34"
- assert not any(
- deform_on_per_stage
- ), "MODEL.RESNETS.DEFORM_ON_PER_STAGE unsupported for R18/R34"
- assert res5_dilation == 1, "Must set MODEL.RESNETS.RES5_DILATION = 1 for R18/R34"
- assert num_groups == 1, "Must set MODEL.RESNETS.NUM_GROUPS = 1 for R18/R34"
-
- stages = []
-
- for idx, stage_idx in enumerate(range(2, 6)):
- # res5_dilation is used this way as a convention in R-FCN & Deformable Conv paper
- dilation = res5_dilation if stage_idx == 5 else 1
- first_stride = 1 if idx == 0 or (stage_idx == 5 and dilation == 2) else 2
- stage_kargs = {
- "num_blocks": num_blocks_per_stage[idx],
- "stride_per_block": [first_stride] + [1] * (num_blocks_per_stage[idx] - 1),
- "in_channels": in_channels,
- "out_channels": out_channels,
- "norm": norm,
- }
- # Use BasicBlock for R18 and R34.
- if depth in [18, 34]:
- stage_kargs["block_class"] = BasicBlock
- else:
- stage_kargs["bottleneck_channels"] = bottleneck_channels
- stage_kargs["stride_in_1x1"] = stride_in_1x1
- stage_kargs["dilation"] = dilation
- stage_kargs["num_groups"] = num_groups
- if deform_on_per_stage[idx]:
- stage_kargs["block_class"] = DeformBottleneckBlock
- stage_kargs["deform_modulated"] = deform_modulated
- stage_kargs["deform_num_groups"] = deform_num_groups
- else:
- stage_kargs["block_class"] = BottleneckBlock
- blocks = ResNet.make_stage(**stage_kargs)
- in_channels = out_channels
- out_channels *= 2
- bottleneck_channels *= 2
- stages.append(blocks)
- return ResNet(stem, stages, out_features=out_features, freeze_at=freeze_at)
diff --git a/spaces/ChandraMohanNayal/AutoGPT/autogpt/cli.py b/spaces/ChandraMohanNayal/AutoGPT/autogpt/cli.py
deleted file mode 100644
index a2e99cb421cad005528cb160e948ce59ccfcdb66..0000000000000000000000000000000000000000
--- a/spaces/ChandraMohanNayal/AutoGPT/autogpt/cli.py
+++ /dev/null
@@ -1,145 +0,0 @@
-"""Main script for the autogpt package."""
-import click
-
-
-@click.group(invoke_without_command=True)
-@click.option("-c", "--continuous", is_flag=True, help="Enable Continuous Mode")
-@click.option(
- "--skip-reprompt",
- "-y",
- is_flag=True,
- help="Skips the re-prompting messages at the beginning of the script",
-)
-@click.option(
- "--ai-settings",
- "-C",
- help="Specifies which ai_settings.yaml file to use, will also automatically skip the re-prompt.",
-)
-@click.option(
- "-l",
- "--continuous-limit",
- type=int,
- help="Defines the number of times to run in continuous mode",
-)
-@click.option("--speak", is_flag=True, help="Enable Speak Mode")
-@click.option("--debug", is_flag=True, help="Enable Debug Mode")
-@click.option("--gpt3only", is_flag=True, help="Enable GPT3.5 Only Mode")
-@click.option("--gpt4only", is_flag=True, help="Enable GPT4 Only Mode")
-@click.option(
- "--use-memory",
- "-m",
- "memory_type",
- type=str,
- help="Defines which Memory backend to use",
-)
-@click.option(
- "-b",
- "--browser-name",
- help="Specifies which web-browser to use when using selenium to scrape the web.",
-)
-@click.option(
- "--allow-downloads",
- is_flag=True,
- help="Dangerous: Allows Auto-GPT to download files natively.",
-)
-@click.option(
- "--skip-news",
- is_flag=True,
- help="Specifies whether to suppress the output of latest news on startup.",
-)
-@click.pass_context
-def main(
- ctx: click.Context,
- continuous: bool,
- continuous_limit: int,
- ai_settings: str,
- skip_reprompt: bool,
- speak: bool,
- debug: bool,
- gpt3only: bool,
- gpt4only: bool,
- memory_type: str,
- browser_name: str,
- allow_downloads: bool,
- skip_news: bool,
-) -> None:
- """
- Welcome to AutoGPT an experimental open-source application showcasing the capabilities of the GPT-4 pushing the boundaries of AI.
-
- Start an Auto-GPT assistant.
- """
- # Put imports inside function to avoid importing everything when starting the CLI
- import logging
-
- from colorama import Fore
-
- from autogpt.agent.agent import Agent
- from autogpt.config import Config, check_openai_api_key
- from autogpt.configurator import create_config
- from autogpt.logs import logger
- from autogpt.memory import get_memory
- from autogpt.prompt import construct_prompt
- from autogpt.utils import get_current_git_branch, get_latest_bulletin
-
- if ctx.invoked_subcommand is None:
- cfg = Config()
- # TODO: fill in llm values here
- check_openai_api_key()
- create_config(
- continuous,
- continuous_limit,
- ai_settings,
- skip_reprompt,
- speak,
- debug,
- gpt3only,
- gpt4only,
- memory_type,
- browser_name,
- allow_downloads,
- skip_news,
- )
- logger.set_level(logging.DEBUG if cfg.debug_mode else logging.INFO)
- ai_name = ""
- if not cfg.skip_news:
- motd = get_latest_bulletin()
- if motd:
- logger.typewriter_log("NEWS: ", Fore.GREEN, motd)
- git_branch = get_current_git_branch()
- if git_branch and git_branch != "stable":
- logger.typewriter_log(
- "WARNING: ",
- Fore.RED,
- f"You are running on `{git_branch}` branch "
- "- this is not a supported branch.",
- )
- system_prompt = construct_prompt()
- # print(prompt)
- # Initialize variables
- full_message_history = []
- next_action_count = 0
- # Make a constant:
- triggering_prompt = (
- "Determine which next command to use, and respond using the"
- " format specified above:"
- )
- # Initialize memory and make sure it is empty.
- # this is particularly important for indexing and referencing pinecone memory
- memory = get_memory(cfg, init=True)
- logger.typewriter_log(
- "Using memory of type:", Fore.GREEN, f"{memory.__class__.__name__}"
- )
- logger.typewriter_log("Using Browser:", Fore.GREEN, cfg.selenium_web_browser)
- agent = Agent(
- ai_name=ai_name,
- memory=memory,
- full_message_history=full_message_history,
- next_action_count=next_action_count,
- system_prompt=system_prompt,
- triggering_prompt=triggering_prompt,
- )
- agent.start_interaction_loop()
-
-
-if __name__ == "__main__":
- main()
diff --git a/spaces/Chintan-Donda/KKMS-KSSW-HF/src/constants.py b/spaces/Chintan-Donda/KKMS-KSSW-HF/src/constants.py
deleted file mode 100644
index 202bb53eee2dcc79d53b20dd3ae219db08a85cfc..0000000000000000000000000000000000000000
--- a/spaces/Chintan-Donda/KKMS-KSSW-HF/src/constants.py
+++ /dev/null
@@ -1,143 +0,0 @@
-import os
-import src.web_crawler as web_crawler_utils
-import src.weather as weather_utils
-
-LOAD_FROM_EXISTING_INDEX_STORE = False
-INDEX_TYPE = 'FAISS'
-
-# Path from where to load the data (from the local directory)
-DATA_PATH = './data/'
-
-# Path to store the index/vector db
-OUTPUT_PATH = os.path.join('./output/', INDEX_TYPE)
-# Create OUTPUT_PATH directory if not present
-if not os.path.exists(OUTPUT_PATH):
- os.makedirs(OUTPUT_PATH)
-
-# Index categories (There would be an index for each category. On asking the query, App will search for the relevant docs/information only from the respective index category.)
-INDEX_CATEGORY = [
- 'crops',
- 'fruits',
- 'pest_management',
- 'govt_policy',
- 'insurance',
- 'soil',
- 'general',
- 'vegetables'
-]
-
-# Doctype of the master index of each index category. Master index for each index category would be stored under this key.
-INDEX_CATEGORY_MASTER_INDEX_DOC_TYPE = 'master'
-
-# List of data sources/types & from where to load the data and create the index/vector store
-# 2nd item is the type of source from where the data would be loaded. Currently it could come from either a file or URL.
-DATA_SOURCES = {
- 'PDF': 'pdf',
- 'Text File': 'textfile',
- 'Online PDF': 'online_pdf', # web_crawler_utils.get_ipm_packages_pdfs_urls()[:1]
- 'URLs': 'urls',
-}
-
-# LangChain related constants
-SIMILARITY_TOP_K = 1
-MODE = 'embedding'
-RESPONSE_MODE = 'default'
-TEXT_SPLITTER_CHUNK_SIZE = 1000
-TEXT_SPLITTER_CHUNK_OVERLAP = 0
-TEXT_SPLITTER_SEPARATOR = '\n\n'
-
-
-URLS = [
- # Govt. Schemes
- 'https://agricoop.nic.in/en/Major#gsc.tab=0'
- 'https://agricoop.nic.in/#gsc.tab=0',
-
- 'https://dmi.gov.in/Documents/GrantCAGrapes.pdf',
- 'https://dmi.gov.in/Documents/organicfaq.pdf',
- 'https://dmi.gov.in/Documents/CAGMOrganic-III.pdf',
- 'https://dmi.gov.in/GradesStandard.aspx',
- 'https://www.india.gov.in/topics/agriculture',
- 'https://www.india.gov.in/farmers-portal',
-
- # Pest Management related
- 'https://niphm.gov.in/IPMPackages/Maize.pdf',
-
- # Banned Pesticides
- 'https://ppqs.gov.in/divisions/cib-rc/registered-products', # Online PDF links on the page
-
- # Mandi Price related
- 'https://agmarknet.gov.in/',
-
- # General information related: Information of interests are present on the 2nd level url
- 'https://www.manage.gov.in/nf/nf.asp',
-
- # Weather forecast related
- 'https://nwp.imd.gov.in/blf/blf_temp/', # need to select state -> district (on the new page) -> displays detailed table -> can get info at the block level as well from the same page on selection
- 'https://nwp.imd.gov.in/blf/blf_temp/dis.php?value=12gujarat', # to get weather forecast for the given state
- 'https://nwp.imd.gov.in/blf/blf_temp/block.php?dis=12BHAVNAGAR', # to get the weather forecast for the given district
-]
-
-
-# Supported Indian laguages for translating the English text to Indian language
-INDIC_LANGUAGE = {
- 'Hindi': 'hi',
- 'Gujarati': 'gu',
- 'Kannada': 'kn',
- 'Marathi': 'mr',
- 'Panjabi': 'pa',
- 'Bengali': "bn",
- 'Telugu': 'te',
- 'Tamil': 'ta',
- 'Malayalam': 'ml',
-}
-
-# State list used in the Mandi Price widget dropdown list
-MANDI_PRICE_STATES = [
- 'ANDAMAN AND NICOBAR ISLANDS',
- 'ANDHRA PRADESH',
- 'ASSAM',
- 'BIHAR',
- 'CHANDIGARH',
- 'CHHATTISGARH',
- 'GOA',
- 'GUJARAT',
- 'HARYANA',
- 'HIMACHAL PRADESH',
- 'JAMMU AND KASHMIR',
- 'JHARKHAND',
- 'KARNATAKA',
- 'KERALA',
- 'MADHYA PRADESH',
- 'MAHARASHTRA',
- 'NAGALAND',
- 'ODISHA',
- 'PUDUCHERRY',
- 'PUNJAB',
- 'RAJASTHAN',
- 'TAMIL NADU',
- 'TELANGANA',
- 'TRIPURA',
- 'UTTAR PRADESH',
- 'UTTARAKHAND',
- 'WEST BENGAL'
-]
-
-# State list used in the Weather forecast widget dropdown list
-weather_utils_obj = weather_utils.WEATHER()
-WEATHER_FORECAST_STATE_CODES = weather_utils_obj.get_state_names_codes()
-
-# LIST OF PESTICIDES WHICH ARE BANNED AND RESTRICTED USE (List created from: https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1896140)
-BANNED_PESTICIDES_FORMULATIONS = [
- 'Alachlor',
- 'Aldicarb',
- 'Aldrin',
- 'Benzene Hexachloride',
- 'Benomyl',
- 'Calcium Cyanide',
- 'Carbaryl',
- 'Chlorbenzilate',
- 'Chlordane',
- 'Chlorofenvinphos',
- 'Copper Acetoarsenite',
-]
-
diff --git a/spaces/ChristopherMarais/Andrew_AI-BB_classification-beta/mysite/andrew_alpha/migrations/__init__.py b/spaces/ChristopherMarais/Andrew_AI-BB_classification-beta/mysite/andrew_alpha/migrations/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/CrafterHide/Sariwon/README.md b/spaces/CrafterHide/Sariwon/README.md
deleted file mode 100644
index 3c1285ddef6ae7a9cc400e33383f603e8dd5ccaa..0000000000000000000000000000000000000000
--- a/spaces/CrafterHide/Sariwon/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Sariwon
-emoji: 😻
-colorFrom: green
-colorTo: pink
-sdk: gradio
-sdk_version: 3.41.0
-app_file: app.py
-pinned: false
-license: openrail
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Cropinky/hana_hanak_houses/realesrgan/utils.py b/spaces/Cropinky/hana_hanak_houses/realesrgan/utils.py
deleted file mode 100644
index 67e5232d61e93807f22b052499a733cd348a61a0..0000000000000000000000000000000000000000
--- a/spaces/Cropinky/hana_hanak_houses/realesrgan/utils.py
+++ /dev/null
@@ -1,313 +0,0 @@
-import cv2
-import math
-import numpy as np
-import os
-import queue
-import threading
-import torch
-from basicsr.utils.download_util import load_file_from_url
-from torch.nn import functional as F
-
-ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-
-
-class RealESRGANer():
- """A helper class for upsampling images with RealESRGAN.
-
- Args:
- scale (int): Upsampling scale factor used in the networks. It is usually 2 or 4.
- model_path (str): The path to the pretrained model. It can be urls (will first download it automatically).
- model (nn.Module): The defined network. Default: None.
- tile (int): As too large images result in the out of GPU memory issue, so this tile option will first crop
- input images into tiles, and then process each of them. Finally, they will be merged into one image.
- 0 denotes for do not use tile. Default: 0.
- tile_pad (int): The pad size for each tile, to remove border artifacts. Default: 10.
- pre_pad (int): Pad the input images to avoid border artifacts. Default: 10.
- half (float): Whether to use half precision during inference. Default: False.
- """
-
- def __init__(self,
- scale,
- model_path,
- dni_weight=None,
- model=None,
- tile=0,
- tile_pad=10,
- pre_pad=10,
- half=False,
- device=None,
- gpu_id=None):
- self.scale = scale
- self.tile_size = tile
- self.tile_pad = tile_pad
- self.pre_pad = pre_pad
- self.mod_scale = None
- self.half = half
-
- # initialize model
- if gpu_id:
- self.device = torch.device(
- f'cuda:{gpu_id}' if torch.cuda.is_available() else 'cpu') if device is None else device
- else:
- self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
-
- if isinstance(model_path, list):
- # dni
- assert len(model_path) == len(dni_weight), 'model_path and dni_weight should have the save length.'
- loadnet = self.dni(model_path[0], model_path[1], dni_weight)
- else:
- # if the model_path starts with https, it will first download models to the folder: weights
- if model_path.startswith('https://'):
- model_path = load_file_from_url(
- url=model_path, model_dir=os.path.join(ROOT_DIR, 'weights'), progress=True, file_name=None)
- loadnet = torch.load(model_path, map_location=torch.device('cpu'))
-
- # prefer to use params_ema
- if 'params_ema' in loadnet:
- keyname = 'params_ema'
- else:
- keyname = 'params'
- model.load_state_dict(loadnet[keyname], strict=True)
-
- model.eval()
- self.model = model.to(self.device)
- if self.half:
- self.model = self.model.half()
-
- def dni(self, net_a, net_b, dni_weight, key='params', loc='cpu'):
- """Deep network interpolation.
-
- ``Paper: Deep Network Interpolation for Continuous Imagery Effect Transition``
- """
- net_a = torch.load(net_a, map_location=torch.device(loc))
- net_b = torch.load(net_b, map_location=torch.device(loc))
- for k, v_a in net_a[key].items():
- net_a[key][k] = dni_weight[0] * v_a + dni_weight[1] * net_b[key][k]
- return net_a
-
- def pre_process(self, img):
- """Pre-process, such as pre-pad and mod pad, so that the images can be divisible
- """
- img = torch.from_numpy(np.transpose(img, (2, 0, 1))).float()
- self.img = img.unsqueeze(0).to(self.device)
- if self.half:
- self.img = self.img.half()
-
- # pre_pad
- if self.pre_pad != 0:
- self.img = F.pad(self.img, (0, self.pre_pad, 0, self.pre_pad), 'reflect')
- # mod pad for divisible borders
- if self.scale == 2:
- self.mod_scale = 2
- elif self.scale == 1:
- self.mod_scale = 4
- if self.mod_scale is not None:
- self.mod_pad_h, self.mod_pad_w = 0, 0
- _, _, h, w = self.img.size()
- if (h % self.mod_scale != 0):
- self.mod_pad_h = (self.mod_scale - h % self.mod_scale)
- if (w % self.mod_scale != 0):
- self.mod_pad_w = (self.mod_scale - w % self.mod_scale)
- self.img = F.pad(self.img, (0, self.mod_pad_w, 0, self.mod_pad_h), 'reflect')
-
- def process(self):
- # model inference
- self.output = self.model(self.img)
-
- def tile_process(self):
- """It will first crop input images to tiles, and then process each tile.
- Finally, all the processed tiles are merged into one images.
-
- Modified from: https://github.com/ata4/esrgan-launcher
- """
- batch, channel, height, width = self.img.shape
- output_height = height * self.scale
- output_width = width * self.scale
- output_shape = (batch, channel, output_height, output_width)
-
- # start with black image
- self.output = self.img.new_zeros(output_shape)
- tiles_x = math.ceil(width / self.tile_size)
- tiles_y = math.ceil(height / self.tile_size)
-
- # loop over all tiles
- for y in range(tiles_y):
- for x in range(tiles_x):
- # extract tile from input image
- ofs_x = x * self.tile_size
- ofs_y = y * self.tile_size
- # input tile area on total image
- input_start_x = ofs_x
- input_end_x = min(ofs_x + self.tile_size, width)
- input_start_y = ofs_y
- input_end_y = min(ofs_y + self.tile_size, height)
-
- # input tile area on total image with padding
- input_start_x_pad = max(input_start_x - self.tile_pad, 0)
- input_end_x_pad = min(input_end_x + self.tile_pad, width)
- input_start_y_pad = max(input_start_y - self.tile_pad, 0)
- input_end_y_pad = min(input_end_y + self.tile_pad, height)
-
- # input tile dimensions
- input_tile_width = input_end_x - input_start_x
- input_tile_height = input_end_y - input_start_y
- tile_idx = y * tiles_x + x + 1
- input_tile = self.img[:, :, input_start_y_pad:input_end_y_pad, input_start_x_pad:input_end_x_pad]
-
- # upscale tile
- try:
- with torch.no_grad():
- output_tile = self.model(input_tile)
- except RuntimeError as error:
- print('Error', error)
- print(f'\tTile {tile_idx}/{tiles_x * tiles_y}')
-
- # output tile area on total image
- output_start_x = input_start_x * self.scale
- output_end_x = input_end_x * self.scale
- output_start_y = input_start_y * self.scale
- output_end_y = input_end_y * self.scale
-
- # output tile area without padding
- output_start_x_tile = (input_start_x - input_start_x_pad) * self.scale
- output_end_x_tile = output_start_x_tile + input_tile_width * self.scale
- output_start_y_tile = (input_start_y - input_start_y_pad) * self.scale
- output_end_y_tile = output_start_y_tile + input_tile_height * self.scale
-
- # put tile into output image
- self.output[:, :, output_start_y:output_end_y,
- output_start_x:output_end_x] = output_tile[:, :, output_start_y_tile:output_end_y_tile,
- output_start_x_tile:output_end_x_tile]
-
- def post_process(self):
- # remove extra pad
- if self.mod_scale is not None:
- _, _, h, w = self.output.size()
- self.output = self.output[:, :, 0:h - self.mod_pad_h * self.scale, 0:w - self.mod_pad_w * self.scale]
- # remove prepad
- if self.pre_pad != 0:
- _, _, h, w = self.output.size()
- self.output = self.output[:, :, 0:h - self.pre_pad * self.scale, 0:w - self.pre_pad * self.scale]
- return self.output
-
- @torch.no_grad()
- def enhance(self, img, outscale=None, alpha_upsampler='realesrgan'):
- h_input, w_input = img.shape[0:2]
- # img: numpy
- img = img.astype(np.float32)
- if np.max(img) > 256: # 16-bit image
- max_range = 65535
- print('\tInput is a 16-bit image')
- else:
- max_range = 255
- img = img / max_range
- if len(img.shape) == 2: # gray image
- img_mode = 'L'
- img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
- elif img.shape[2] == 4: # RGBA image with alpha channel
- img_mode = 'RGBA'
- alpha = img[:, :, 3]
- img = img[:, :, 0:3]
- img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
- if alpha_upsampler == 'realesrgan':
- alpha = cv2.cvtColor(alpha, cv2.COLOR_GRAY2RGB)
- else:
- img_mode = 'RGB'
- img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-
- # ------------------- process image (without the alpha channel) ------------------- #
- self.pre_process(img)
- if self.tile_size > 0:
- self.tile_process()
- else:
- self.process()
- output_img = self.post_process()
- output_img = output_img.data.squeeze().float().cpu().clamp_(0, 1).numpy()
- output_img = np.transpose(output_img[[2, 1, 0], :, :], (1, 2, 0))
- if img_mode == 'L':
- output_img = cv2.cvtColor(output_img, cv2.COLOR_BGR2GRAY)
-
- # ------------------- process the alpha channel if necessary ------------------- #
- if img_mode == 'RGBA':
- if alpha_upsampler == 'realesrgan':
- self.pre_process(alpha)
- if self.tile_size > 0:
- self.tile_process()
- else:
- self.process()
- output_alpha = self.post_process()
- output_alpha = output_alpha.data.squeeze().float().cpu().clamp_(0, 1).numpy()
- output_alpha = np.transpose(output_alpha[[2, 1, 0], :, :], (1, 2, 0))
- output_alpha = cv2.cvtColor(output_alpha, cv2.COLOR_BGR2GRAY)
- else: # use the cv2 resize for alpha channel
- h, w = alpha.shape[0:2]
- output_alpha = cv2.resize(alpha, (w * self.scale, h * self.scale), interpolation=cv2.INTER_LINEAR)
-
- # merge the alpha channel
- output_img = cv2.cvtColor(output_img, cv2.COLOR_BGR2BGRA)
- output_img[:, :, 3] = output_alpha
-
- # ------------------------------ return ------------------------------ #
- if max_range == 65535: # 16-bit image
- output = (output_img * 65535.0).round().astype(np.uint16)
- else:
- output = (output_img * 255.0).round().astype(np.uint8)
-
- if outscale is not None and outscale != float(self.scale):
- output = cv2.resize(
- output, (
- int(w_input * outscale),
- int(h_input * outscale),
- ), interpolation=cv2.INTER_LANCZOS4)
-
- return output, img_mode
-
-
-class PrefetchReader(threading.Thread):
- """Prefetch images.
-
- Args:
- img_list (list[str]): A image list of image paths to be read.
- num_prefetch_queue (int): Number of prefetch queue.
- """
-
- def __init__(self, img_list, num_prefetch_queue):
- super().__init__()
- self.que = queue.Queue(num_prefetch_queue)
- self.img_list = img_list
-
- def run(self):
- for img_path in self.img_list:
- img = cv2.imread(img_path, cv2.IMREAD_UNCHANGED)
- self.que.put(img)
-
- self.que.put(None)
-
- def __next__(self):
- next_item = self.que.get()
- if next_item is None:
- raise StopIteration
- return next_item
-
- def __iter__(self):
- return self
-
-
-class IOConsumer(threading.Thread):
-
- def __init__(self, opt, que, qid):
- super().__init__()
- self._queue = que
- self.qid = qid
- self.opt = opt
-
- def run(self):
- while True:
- msg = self._queue.get()
- if isinstance(msg, str) and msg == 'quit':
- break
-
- output = msg['output']
- save_path = msg['save_path']
- cv2.imwrite(save_path, output)
- print(f'IO worker {self.qid} is done.')
diff --git a/spaces/Cyril666/ContourNet-ABI/README.md b/spaces/Cyril666/ContourNet-ABI/README.md
deleted file mode 100644
index ee2b2c88f1f2c9167a826dd082b22baf6d7ac480..0000000000000000000000000000000000000000
--- a/spaces/Cyril666/ContourNet-ABI/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: ContourNet
-emoji: 🚀
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 3.0.10
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
diff --git a/spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/modeling/backbone/fbnet_modeldef.py b/spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/modeling/backbone/fbnet_modeldef.py
deleted file mode 100644
index fb1c96b3a4dbe735682ae81361ee0efed75cbb25..0000000000000000000000000000000000000000
--- a/spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/modeling/backbone/fbnet_modeldef.py
+++ /dev/null
@@ -1,218 +0,0 @@
-from __future__ import absolute_import, division, print_function, unicode_literals
-
-
-def add_archs(archs):
- global MODEL_ARCH
- for x in archs:
- assert x not in MODEL_ARCH, "Duplicated model name {} existed".format(x)
- MODEL_ARCH[x] = archs[x]
-
-
-MODEL_ARCH = {
- "default": {
- "block_op_type": [
- # stage 0
- ["ir_k3"],
- # stage 1
- ["ir_k3"] * 2,
- # stage 2
- ["ir_k3"] * 3,
- # stage 3
- ["ir_k3"] * 7,
- # stage 4, bbox head
- ["ir_k3"] * 4,
- # stage 5, rpn
- ["ir_k3"] * 3,
- # stage 5, mask head
- ["ir_k3"] * 5,
- ],
- "block_cfg": {
- "first": [32, 2],
- "stages": [
- # [t, c, n, s]
- # stage 0
- [[1, 16, 1, 1]],
- # stage 1
- [[6, 24, 2, 2]],
- # stage 2
- [[6, 32, 3, 2]],
- # stage 3
- [[6, 64, 4, 2], [6, 96, 3, 1]],
- # stage 4, bbox head
- [[4, 160, 1, 2], [6, 160, 2, 1], [6, 240, 1, 1]],
- # [[6, 160, 3, 2], [6, 320, 1, 1]],
- # stage 5, rpn head
- [[6, 96, 3, 1]],
- # stage 6, mask head
- [[4, 160, 1, 1], [6, 160, 3, 1], [3, 80, 1, -2]],
- ],
- # [c, channel_scale]
- "last": [0, 0.0],
- "backbone": [0, 1, 2, 3],
- "rpn": [5],
- "bbox": [4],
- "mask": [6],
- },
- },
- "xirb16d_dsmask": {
- "block_op_type": [
- # stage 0
- ["ir_k3"],
- # stage 1
- ["ir_k3"] * 2,
- # stage 2
- ["ir_k3"] * 3,
- # stage 3
- ["ir_k3"] * 7,
- # stage 4, bbox head
- ["ir_k3"] * 4,
- # stage 5, mask head
- ["ir_k3"] * 5,
- # stage 6, rpn
- ["ir_k3"] * 3,
- ],
- "block_cfg": {
- "first": [16, 2],
- "stages": [
- # [t, c, n, s]
- # stage 0
- [[1, 16, 1, 1]],
- # stage 1
- [[6, 32, 2, 2]],
- # stage 2
- [[6, 48, 3, 2]],
- # stage 3
- [[6, 96, 4, 2], [6, 128, 3, 1]],
- # stage 4, bbox head
- [[4, 128, 1, 2], [6, 128, 2, 1], [6, 160, 1, 1]],
- # stage 5, mask head
- [[4, 128, 1, 2], [6, 128, 2, 1], [6, 128, 1, -2], [3, 64, 1, -2]],
- # stage 6, rpn head
- [[6, 128, 3, 1]],
- ],
- # [c, channel_scale]
- "last": [0, 0.0],
- "backbone": [0, 1, 2, 3],
- "rpn": [6],
- "bbox": [4],
- "mask": [5],
- },
- },
- "mobilenet_v2": {
- "block_op_type": [
- # stage 0
- ["ir_k3"],
- # stage 1
- ["ir_k3"] * 2,
- # stage 2
- ["ir_k3"] * 3,
- # stage 3
- ["ir_k3"] * 7,
- # stage 4
- ["ir_k3"] * 4,
- ],
- "block_cfg": {
- "first": [32, 2],
- "stages": [
- # [t, c, n, s]
- # stage 0
- [[1, 16, 1, 1]],
- # stage 1
- [[6, 24, 2, 2]],
- # stage 2
- [[6, 32, 3, 2]],
- # stage 3
- [[6, 64, 4, 2], [6, 96, 3, 1]],
- # stage 4
- [[6, 160, 3, 1], [6, 320, 1, 1]],
- ],
- # [c, channel_scale]
- "last": [0, 0.0],
- "backbone": [0, 1, 2, 3],
- "bbox": [4],
- },
- },
-}
-
-
-MODEL_ARCH_CHAM = {
- "cham_v1a": {
- "block_op_type": [
- # stage 0
- ["ir_k3"],
- # stage 1
- ["ir_k7"] * 2,
- # stage 2
- ["ir_k3"] * 5,
- # stage 3
- ["ir_k5"] * 7 + ["ir_k3"] * 5,
- # stage 4, bbox head
- ["ir_k3"] * 5,
- # stage 5, rpn
- ["ir_k3"] * 3,
- ],
- "block_cfg": {
- "first": [32, 2],
- "stages": [
- # [t, c, n, s]
- # stage 0
- [[1, 24, 1, 1]],
- # stage 1
- [[4, 48, 2, 2]],
- # stage 2
- [[7, 64, 5, 2]],
- # stage 3
- [[12, 56, 7, 2], [8, 88, 5, 1]],
- # stage 4, bbox head
- [[7, 152, 4, 2], [10, 104, 1, 1]],
- # stage 5, rpn head
- [[8, 88, 3, 1]],
- ],
- # [c, channel_scale]
- "last": [0, 0.0],
- "backbone": [0, 1, 2, 3],
- "rpn": [5],
- "bbox": [4],
- },
- },
- "cham_v2": {
- "block_op_type": [
- # stage 0
- ["ir_k3"],
- # stage 1
- ["ir_k5"] * 4,
- # stage 2
- ["ir_k7"] * 6,
- # stage 3
- ["ir_k5"] * 3 + ["ir_k3"] * 6,
- # stage 4, bbox head
- ["ir_k3"] * 7,
- # stage 5, rpn
- ["ir_k3"] * 1,
- ],
- "block_cfg": {
- "first": [32, 2],
- "stages": [
- # [t, c, n, s]
- # stage 0
- [[1, 24, 1, 1]],
- # stage 1
- [[8, 32, 4, 2]],
- # stage 2
- [[5, 48, 6, 2]],
- # stage 3
- [[9, 56, 3, 2], [6, 56, 6, 1]],
- # stage 4, bbox head
- [[2, 160, 6, 2], [6, 112, 1, 1]],
- # stage 5, rpn head
- [[6, 56, 1, 1]],
- ],
- # [c, channel_scale]
- "last": [0, 0.0],
- "backbone": [0, 1, 2, 3],
- "rpn": [5],
- "bbox": [4],
- },
- },
-}
-add_archs(MODEL_ARCH_CHAM)
diff --git a/spaces/DEEMOSTECH/ChatAvatar/static/js/main.7e2a9dc1.js b/spaces/DEEMOSTECH/ChatAvatar/static/js/main.7e2a9dc1.js
deleted file mode 100644
index fc1cdee11c4ebe8db57ae6521026e06e8687631c..0000000000000000000000000000000000000000
--- a/spaces/DEEMOSTECH/ChatAvatar/static/js/main.7e2a9dc1.js
+++ /dev/null
@@ -1,3 +0,0 @@
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e(e,t,n,r){this.codePoints=e,this.required=t===Ce,this.start=n,this.end=r}return e.prototype.slice=function(){return u.apply(void 0,this.codePoints.slice(this.start,this.end))},e}(),Ve=function(e,t){var n=l(e),r=Ne(n,t),i=r[0],A=r[1],a=r[2],o=n.length,s=0,u=0;return{next:function(){if(u>=o)return{done:!0,value:null};for(var e=Se;u=Dt&&e<=57},jt=function(e){return e>=55296&&e<=57343},Xt=function(e){return Wt(e)||e>=Ot&&e<=zt||e>=It&&e<=Ht},qt=function(e){return e>=It&&e<=Nt},Yt=function(e){return e>=Ot&&e<=Kt},Jt=function(e){return qt(e)||Yt(e)},Zt=function(e){return e>=wt},$t=function(e){return e===je||e===Ye||e===Je},en=function(e){return Jt(e)||Zt(e)||e===at},tn=function(e){return en(e)||Wt(e)||e===ot},nn=function(e){return e>=Ut&&e<=Mt||e===Ft||e>=Tt&&e<=kt||e===Qt},rn=function(e,t){return e===qe&&t!==je},An=function(e,t,n){return e===ot?en(t)||rn(t,n):!!en(e)||!(e!==qe||!rn(e,t))},an=function(e,t,n){return e===bt||e===ot?!!Wt(t)||t===Et&&Wt(n):Wt(e===Et?t:e)},on=function(e){var t=0,n=1;e[t]!==bt&&e[t]!==ot||(e[t]===ot&&(n=-1),t++);for(var r=[];Wt(e[t]);)r.push(e[t++]);var i=r.length?parseInt(u.apply(void 0,r),10):0;e[t]===Et&&t++;for(var A=[];Wt(e[t]);)A.push(e[t++]);var a=A.length,o=a?parseInt(u.apply(void 0,A),10):0;e[t]!==Vt&&e[t]!==Rt||t++;var s=1;e[t]!==bt&&e[t]!==ot||(e[t]===ot&&(s=-1),t++);for(var l=[];Wt(e[t]);)l.push(e[t++]);var c=l.length?parseInt(u.apply(void 0,l),10):0;return n*(i+o*Math.pow(10,-a))*Math.pow(10,s*c)},sn={type:2},ln={type:3},un={type:4},cn={type:13},dn={type:8},hn={type:21},fn={type:9},pn={type:10},gn={type:11},mn={type:12},vn={type:14},yn={type:23},wn={type:1},Bn={type:25},_n={type:24},bn={type:26},xn={type:27},Cn={type:28},Sn={type:29},En={type:31},Un={type:32},Mn=function(){function e(){this._value=[]}return e.prototype.write=function(e){this._value=this._value.concat(l(e))},e.prototype.read=function(){for(var e=[],t=this.consumeToken();t!==Un;)e.push(t),t=this.consumeToken();return e},e.prototype.consumeToken=function(){var e=this.consumeCodePoint();switch(e){case Ze:return this.consumeStringToken(Ze);case et:var t=this.peekCodePoint(0),n=this.peekCodePoint(1),r=this.peekCodePoint(2);if(tn(t)||rn(n,r)){var i=An(t,n,r)?Ge:ze;return{type:5,value:this.consumeName(),flags:i}}break;case tt:if(this.peekCodePoint(0)===$e)return this.consumeCodePoint(),cn;break;case rt:return this.consumeStringToken(rt);case it:return sn;case At:return ln;case _t:if(this.peekCodePoint(0)===$e)return this.consumeCodePoint(),vn;break;case bt:if(an(e,this.peekCodePoint(0),this.peekCodePoint(1)))return this.reconsumeCodePoint(e),this.consumeNumericToken();break;case xt:return un;case ot:var A=e,a=this.peekCodePoint(0),o=this.peekCodePoint(1);if(an(A,a,o))return this.reconsumeCodePoint(e),this.consumeNumericToken();if(An(A,a,o))return this.reconsumeCodePoint(e),this.consumeIdentLikeToken();if(a===ot&&o===ut)return this.consumeCodePoint(),this.consumeCodePoint(),_n;break;case Et:if(an(e,this.peekCodePoint(0),this.peekCodePoint(1)))return this.reconsumeCodePoint(e),this.consumeNumericToken();break;case Xe:if(this.peekCodePoint(0)===_t)for(this.consumeCodePoint();;){var s=this.consumeCodePoint();if(s===_t&&(s=this.consumeCodePoint())===Xe)return this.consumeToken();if(s===Lt)return this.consumeToken()}break;case Ct:return bn;case St:return xn;case lt:if(this.peekCodePoint(0)===st&&this.peekCodePoint(1)===ot&&this.peekCodePoint(2)===ot)return this.consumeCodePoint(),this.consumeCodePoint(),Bn;break;case ct:var l=this.peekCodePoint(0),c=this.peekCodePoint(1),d=this.peekCodePoint(2);if(An(l,c,d))return{type:7,value:this.consumeName()};break;case dt:return Cn;case qe:if(rn(e,this.peekCodePoint(0)))return this.reconsumeCodePoint(e),this.consumeIdentLikeToken();break;case ht:return Sn;case ft:if(this.peekCodePoint(0)===$e)return this.consumeCodePoint(),dn;break;case pt:return gn;case mt:return mn;case Pt:case Gt:var h=this.peekCodePoint(0),f=this.peekCodePoint(1);return h!==bt||!Xt(f)&&f!==gt||(this.consumeCodePoint(),this.consumeUnicodeRangeToken()),this.reconsumeCodePoint(e),this.consumeIdentLikeToken();case vt:if(this.peekCodePoint(0)===$e)return this.consumeCodePoint(),fn;if(this.peekCodePoint(0)===vt)return this.consumeCodePoint(),hn;break;case yt:if(this.peekCodePoint(0)===$e)return this.consumeCodePoint(),pn;break;case Lt:return Un}return $t(e)?(this.consumeWhiteSpace(),En):Wt(e)?(this.reconsumeCodePoint(e),this.consumeNumericToken()):en(e)?(this.reconsumeCodePoint(e),this.consumeIdentLikeToken()):{type:6,value:u(e)}},e.prototype.consumeCodePoint=function(){var e=this._value.shift();return"undefined"===typeof e?-1:e},e.prototype.reconsumeCodePoint=function(e){this._value.unshift(e)},e.prototype.peekCodePoint=function(e){return e>=this._value.length?-1:this._value[e]},e.prototype.consumeUnicodeRangeToken=function(){for(var e=[],t=this.consumeCodePoint();Xt(t)&&e.length<6;)e.push(t),t=this.consumeCodePoint();for(var n=!1;t===gt&&e.length<6;)e.push(t),t=this.consumeCodePoint(),n=!0;if(n)return{type:30,start:parseInt(u.apply(void 0,e.map((function(e){return e===gt?Dt:e}))),16),end:parseInt(u.apply(void 0,e.map((function(e){return e===gt?zt:e}))),16)};var r=parseInt(u.apply(void 0,e),16);if(this.peekCodePoint(0)===ot&&Xt(this.peekCodePoint(1))){this.consumeCodePoint(),t=this.consumeCodePoint();for(var i=[];Xt(t)&&i.length<6;)i.push(t),t=this.consumeCodePoint();return{type:30,start:r,end:parseInt(u.apply(void 0,i),16)}}return{type:30,start:r,end:r}},e.prototype.consumeIdentLikeToken=function(){var e=this.consumeName();return"url"===e.toLowerCase()&&this.peekCodePoint(0)===it?(this.consumeCodePoint(),this.consumeUrlToken()):this.peekCodePoint(0)===it?(this.consumeCodePoint(),{type:19,value:e}):{type:20,value:e}},e.prototype.consumeUrlToken=function(){var e=[];if(this.consumeWhiteSpace(),this.peekCodePoint(0)===Lt)return{type:22,value:""};var t=this.peekCodePoint(0);if(t===rt||t===Ze){var n=this.consumeStringToken(this.consumeCodePoint());return 0===n.type&&(this.consumeWhiteSpace(),this.peekCodePoint(0)===Lt||this.peekCodePoint(0)===At)?(this.consumeCodePoint(),{type:22,value:n.value}):(this.consumeBadUrlRemnants(),yn)}for(;;){var r=this.consumeCodePoint();if(r===Lt||r===At)return{type:22,value:u.apply(void 0,e)};if($t(r))return this.consumeWhiteSpace(),this.peekCodePoint(0)===Lt||this.peekCodePoint(0)===At?(this.consumeCodePoint(),{type:22,value:u.apply(void 0,e)}):(this.consumeBadUrlRemnants(),yn);if(r===Ze||r===rt||r===it||nn(r))return this.consumeBadUrlRemnants(),yn;if(r===qe){if(!rn(r,this.peekCodePoint(0)))return this.consumeBadUrlRemnants(),yn;e.push(this.consumeEscapedCodePoint())}else e.push(r)}},e.prototype.consumeWhiteSpace=function(){for(;$t(this.peekCodePoint(0));)this.consumeCodePoint()},e.prototype.consumeBadUrlRemnants=function(){for(;;){var e=this.consumeCodePoint();if(e===At||e===Lt)return;rn(e,this.peekCodePoint(0))&&this.consumeEscapedCodePoint()}},e.prototype.consumeStringSlice=function(e){for(var t=5e4,n="";e>0;){var r=Math.min(t,e);n+=u.apply(void 0,this._value.splice(0,r)),e-=r}return this._value.shift(),n},e.prototype.consumeStringToken=function(e){for(var t="",n=0;;){var r=this._value[n];if(r===Lt||void 0===r||r===e)return{type:0,value:t+=this.consumeStringSlice(n)};if(r===je)return this._value.splice(0,n),wn;if(r===qe){var i=this._value[n+1];i!==Lt&&void 0!==i&&(i===je?(t+=this.consumeStringSlice(n),n=-1,this._value.shift()):rn(r,i)&&(t+=this.consumeStringSlice(n),t+=u(this.consumeEscapedCodePoint()),n=-1))}n++}},e.prototype.consumeNumber=function(){var e=[],t=Ke,n=this.peekCodePoint(0);for(n!==bt&&n!==ot||e.push(this.consumeCodePoint());Wt(this.peekCodePoint(0));)e.push(this.consumeCodePoint());n=this.peekCodePoint(0);var r=this.peekCodePoint(1);if(n===Et&&Wt(r))for(e.push(this.consumeCodePoint(),this.consumeCodePoint()),t=We;Wt(this.peekCodePoint(0));)e.push(this.consumeCodePoint());n=this.peekCodePoint(0),r=this.peekCodePoint(1);var i=this.peekCodePoint(2);if((n===Vt||n===Rt)&&((r===bt||r===ot)&&Wt(i)||Wt(r)))for(e.push(this.consumeCodePoint(),this.consumeCodePoint()),t=We;Wt(this.peekCodePoint(0));)e.push(this.consumeCodePoint());return[on(e),t]},e.prototype.consumeNumericToken=function(){var e=this.consumeNumber(),t=e[0],n=e[1],r=this.peekCodePoint(0),i=this.peekCodePoint(1),A=this.peekCodePoint(2);return An(r,i,A)?{type:15,number:t,flags:n,unit:this.consumeName()}:r===nt?(this.consumeCodePoint(),{type:16,number:t,flags:n}):{type:17,number:t,flags:n}},e.prototype.consumeEscapedCodePoint=function(){var e=this.consumeCodePoint();if(Xt(e)){for(var t=u(e);Xt(this.peekCodePoint(0))&&t.length<6;)t+=u(this.consumeCodePoint());$t(this.peekCodePoint(0))&&this.consumeCodePoint();var n=parseInt(t,16);return 0===n||jt(n)||n>1114111?Bt:n}return e===Lt?Bt:e},e.prototype.consumeName=function(){for(var e="";;){var t=this.consumeCodePoint();if(tn(t))e+=u(t);else{if(!rn(t,this.peekCodePoint(0)))return this.reconsumeCodePoint(t),e;e+=u(this.consumeEscapedCodePoint())}}},e}(),Fn=function(){function e(e){this._tokens=e}return e.create=function(t){var n=new Mn;return n.write(t),new e(n.read())},e.parseValue=function(t){return e.create(t).parseComponentValue()},e.parseValues=function(t){return e.create(t).parseComponentValues()},e.prototype.parseComponentValue=function(){for(var e=this.consumeToken();31===e.type;)e=this.consumeToken();if(32===e.type)throw new SyntaxError("Error parsing CSS component value, unexpected EOF");this.reconsumeToken(e);var t=this.consumeComponentValue();do{e=this.consumeToken()}while(31===e.type);if(32===e.type)return t;throw new SyntaxError("Error parsing CSS component value, multiple values found when expecting only one")},e.prototype.parseComponentValues=function(){for(var e=[];;){var t=this.consumeComponentValue();if(32===t.type)return e;e.push(t),e.push()}},e.prototype.consumeComponentValue=function(){var e=this.consumeToken();switch(e.type){case 11:case 28:case 2:return this.consumeSimpleBlock(e.type);case 19:return this.consumeFunction(e)}return e},e.prototype.consumeSimpleBlock=function(e){for(var t={type:e,values:[]},n=this.consumeToken();;){if(32===n.type||Pn(n,e))return t;this.reconsumeToken(n),t.values.push(this.consumeComponentValue()),n=this.consumeToken()}},e.prototype.consumeFunction=function(e){for(var t={name:e.value,values:[],type:18};;){var n=this.consumeToken();if(32===n.type||3===n.type)return t;this.reconsumeToken(n),t.values.push(this.consumeComponentValue())}},e.prototype.consumeToken=function(){var e=this._tokens.shift();return"undefined"===typeof e?Un:e},e.prototype.reconsumeToken=function(e){this._tokens.unshift(e)},e}(),Tn=function(e){return 15===e.type},kn=function(e){return 17===e.type},Qn=function(e){return 20===e.type},Ln=function(e){return 0===e.type},Dn=function(e,t){return Qn(e)&&e.value===t},In=function(e){return 31!==e.type},Rn=function(e){return 31!==e.type&&4!==e.type},Hn=function(e){var t=[],n=[];return e.forEach((function(e){if(4===e.type){if(0===n.length)throw new Error("Error parsing function args, zero tokens for arg");return t.push(n),void(n=[])}31!==e.type&&n.push(e)})),n.length&&t.push(n),t},Pn=function(e,t){return 11===t&&12===e.type||28===t&&29===e.type||2===t&&3===e.type},Nn=function(e){return 17===e.type||15===e.type},On=function(e){return 16===e.type||Nn(e)},Vn=function(e){return e.length>1?[e[0],e[1]]:[e[0]]},zn={type:17,number:0,flags:Ke},Gn={type:16,number:50,flags:Ke},Kn={type:16,number:100,flags:Ke},Wn=function(e,t,n){var r=e[0],i=e[1];return[jn(r,t),jn("undefined"!==typeof i?i:r,n)]},jn=function(e,t){if(16===e.type)return e.number/100*t;if(Tn(e))switch(e.unit){case"rem":case"em":return 16*e.number;default:return e.number}return e.number},Xn="deg",qn="grad",Yn="rad",Jn="turn",Zn={name:"angle",parse:function(e,t){if(15===t.type)switch(t.unit){case Xn:return Math.PI*t.number/180;case qn:return Math.PI/200*t.number;case Yn:return t.number;case Jn:return 2*Math.PI*t.number}throw new Error("Unsupported angle type")}},$n=function(e){return 15===e.type&&(e.unit===Xn||e.unit===qn||e.unit===Yn||e.unit===Jn)},er=function(e){switch(e.filter(Qn).map((function(e){return e.value})).join(" ")){case"to bottom right":case"to right bottom":case"left top":case"top left":return[zn,zn];case"to top":case"bottom":return tr(0);case"to bottom left":case"to left bottom":case"right 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Io(e,"\u30a2\u30a4\u30a6\u30a8\u30aa\u30ab\u30ad\u30af\u30b1\u30b3\u30b5\u30b7\u30b9\u30bb\u30bd\u30bf\u30c1\u30c4\u30c6\u30c8\u30ca\u30cb\u30cc\u30cd\u30ce\u30cf\u30d2\u30d5\u30d8\u30db\u30de\u30df\u30e0\u30e1\u30e2\u30e4\u30e6\u30e8\u30e9\u30ea\u30eb\u30ec\u30ed\u30ef\u30f0\u30f1\u30f2\u30f3",i);case 29:return Io(e,"\u30a4\u30ed\u30cf\u30cb\u30db\u30d8\u30c8\u30c1\u30ea\u30cc\u30eb\u30f2\u30ef\u30ab\u30e8\u30bf\u30ec\u30bd\u30c4\u30cd\u30ca\u30e9\u30e0\u30a6\u30f0\u30ce\u30aa\u30af\u30e4\u30de\u30b1\u30d5\u30b3\u30a8\u30c6\u30a2\u30b5\u30ad\u30e6\u30e1\u30df\u30b7\u30f1\u30d2\u30e2\u30bb\u30b9",i);case 34:return Do(e,3792,3801,!0,r);case 37:return Do(e,6160,6169,!0,r);case 38:return Do(e,4160,4169,!0,r);case 39:return Do(e,2918,2927,!0,r);case 40:return Do(e,1776,1785,!0,r);case 43:return Do(e,3046,3055,!0,r);case 44:return Do(e,3174,3183,!0,r);case 45:return Do(e,3664,3673,!0,r);case 46:return Do(e,3872,3881,!0,r);default:return 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wo(t)&&(wo(e)&&e.currentSrc&&e.currentSrc!==e.src&&(t.src=e.currentSrc,t.srcset=""),"lazy"===t.loading&&(t.loading="eager")),Eo(t)?this.createCustomElementClone(t):t},e.prototype.createCustomElementClone=function(e){var t=document.createElement("html2canvascustomelement");return ts(e.style,t),t},e.prototype.createStyleClone=function(e){try{var t=e.sheet;if(t&&t.cssRules){var n=[].slice.call(t.cssRules,0).reduce((function(e,t){return t&&"string"===typeof t.cssText?e+t.cssText:e}),""),r=e.cloneNode(!1);return r.textContent=n,r}}catch(Rt){if(this.context.logger.error("Unable to access cssRules property",Rt),"SecurityError"!==Rt.name)throw Rt}return e.cloneNode(!1)},e.prototype.createCanvasClone=function(e){var t;if(this.options.inlineImages&&e.ownerDocument){var n=e.ownerDocument.createElement("img");try{return n.src=e.toDataURL(),n}catch(Rt){this.context.logger.info("Unable to inline canvas contents, canvas is tainted",e)}}var r=e.cloneNode(!1);try{r.width=e.width,r.height=e.height;var i=e.getContext("2d"),A=r.getContext("2d");if(A)if(!this.options.allowTaint&&i)A.putImageData(i.getImageData(0,0,e.width,e.height),0,0);else{var a=null!==(t=e.getContext("webgl2"))&&void 0!==t?t:e.getContext("webgl");if(a){var o=a.getContextAttributes();!1===(null===o||void 0===o?void 0:o.preserveDrawingBuffer)&&this.context.logger.warn("Unable to clone WebGL context as it has preserveDrawingBuffer=false",e)}A.drawImage(e,0,0)}return r}catch(Rt){this.context.logger.info("Unable to clone canvas as it is tainted",e)}return r},e.prototype.createVideoClone=function(e){var t=e.ownerDocument.createElement("canvas");t.width=e.offsetWidth,t.height=e.offsetHeight;var n=t.getContext("2d");try{return n&&(n.drawImage(e,0,0,t.width,t.height),this.options.allowTaint||n.getImageData(0,0,t.width,t.height)),t}catch(Rt){this.context.logger.info("Unable to clone video as it is tainted",e)}var r=e.ownerDocument.createElement("canvas");return r.width=e.offsetWidth,r.height=e.offsetHeight,r},e.prototype.appendChildNode=function(e,t,n){so(t)&&(bo(t)||t.hasAttribute(jo)||"function"===typeof this.options.ignoreElements&&this.options.ignoreElements(t))||this.options.copyStyles&&so(t)&&_o(t)||e.appendChild(this.cloneNode(t,n))},e.prototype.cloneChildNodes=function(e,t,n){for(var r=this,i=e.shadowRoot?e.shadowRoot.firstChild:e.firstChild;i;i=i.nextSibling)if(so(i)&&So(i)&&"function"===typeof i.assignedNodes){var A=i.assignedNodes();A.length&&A.forEach((function(e){return r.appendChildNode(t,e,n)}))}else this.appendChildNode(t,i,n)},e.prototype.cloneNode=function(e,t){if(oo(e))return document.createTextNode(e.data);if(!e.ownerDocument)return e.cloneNode(!1);var n=e.ownerDocument.defaultView;if(n&&so(e)&&(lo(e)||uo(e))){var r=this.createElementClone(e);r.style.transitionProperty="none";var i=n.getComputedStyle(e),A=n.getComputedStyle(e,":before"),a=n.getComputedStyle(e,":after");this.referenceElement===e&&lo(r)&&(this.clonedReferenceElement=r),mo(r)&&us(r);var o=this.counters.parse(new mA(this.context,i)),s=this.resolvePseudoContent(e,r,A,KA.BEFORE);Eo(e)&&(t=!0),yo(e)||this.cloneChildNodes(e,r,t),s&&r.insertBefore(s,r.firstChild);var l=this.resolvePseudoContent(e,r,a,KA.AFTER);return l&&r.appendChild(l),this.counters.pop(o),(i&&(this.options.copyStyles||uo(e))&&!Bo(e)||t)&&ts(i,r),0===e.scrollTop&&0===e.scrollLeft||this.scrolledElements.push([r,e.scrollLeft,e.scrollTop]),(xo(e)||Co(e))&&(xo(r)||Co(r))&&(r.value=e.value),r}return e.cloneNode(!1)},e.prototype.resolvePseudoContent=function(e,t,n,r){var i=this;if(n){var A=n.content,a=t.ownerDocument;if(a&&A&&"none"!==A&&"-moz-alt-content"!==A&&"none"!==n.display){this.counters.parse(new mA(this.context,n));var o=new 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t=-1===[2,3].indexOf(this.container.styles.position),n=this.parent,r=this.effects.slice(0);n;){var i=n.effects.filter((function(e){return!Ds(e)}));if(t||0!==n.container.styles.position||!n.parent){if(r.unshift.apply(r,i),t=-1===[2,3].indexOf(n.container.styles.position),0!==n.container.styles.overflowX){var A=Us(n.curves),a=Fs(n.curves);Rs(A,a)||r.unshift(new ks(a,6))}}else r.unshift.apply(r,i);n=n.parent}return r.filter((function(t){return iA(t.target,e)}))},e}(),Os=function e(t,n,r,i){t.container.elements.forEach((function(A){var a=iA(A.flags,4),o=iA(A.flags,2),s=new Ns(A,t);iA(A.styles.display,2048)&&i.push(s);var l=iA(A.flags,8)?[]:i;if(a||o){var u=a||A.styles.isPositioned()?r:n,c=new Ps(s);if(A.styles.isPositioned()||A.styles.opacity<1||A.styles.isTransformed()){var d=A.styles.zIndex.order;if(d<0){var h=0;u.negativeZIndex.some((function(e,t){return d>e.element.container.styles.zIndex.order?(h=t,!1):h>0})),u.negativeZIndex.splice(h,0,c)}else if(d>0){var f=0;u.positiveZIndex.some((function(e,t){return d>=e.element.container.styles.zIndex.order?(f=t+1,!1):f>0})),u.positiveZIndex.splice(f,0,c)}else u.zeroOrAutoZIndexOrTransformedOrOpacity.push(c)}else A.styles.isFloating()?u.nonPositionedFloats.push(c):u.nonPositionedInlineLevel.push(c);e(s,c,a?c:r,l)}else A.styles.isInlineLevel()?n.inlineLevel.push(s):n.nonInlineLevel.push(s),e(s,n,r,l);iA(A.flags,8)&&Vs(A,l)}))},Vs=function(e,t){for(var n=e instanceof Va?e.start:1,r=e instanceof Va&&e.reversed,i=0;i0&&e.intrinsicHeight>0){var r=Js(e),i=Fs(t);this.path(i),this.ctx.save(),this.ctx.clip(),this.ctx.drawImage(n,0,0,e.intrinsicWidth,e.intrinsicHeight,r.left,r.top,r.width,r.height),this.ctx.restore()}},n.prototype.renderNodeContent=function(e){return r(this,void 0,void 0,(function(){var t,r,A,o,s,l,u,c,d,h,f,p,g,m,v,y,w,B;return i(this,(function(i){switch(i.label){case 0:this.applyEffects(e.getEffects(4)),t=e.container,r=e.curves,A=t.styles,o=0,s=t.textNodes,i.label=1;case 1:return 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3!==l.style?[3,7]:[4,this.renderDashedDottedBorder(l.color,l.width,a,e.curves,3)];case 6:return i.sent(),[3,11];case 7:return 4!==l.style?[3,9]:[4,this.renderDoubleBorder(l.color,l.width,a,e.curves)];case 8:return i.sent(),[3,11];case 9:return[4,this.renderSolidBorder(l.color,a,e.curves)];case 10:i.sent(),i.label=11;case 11:a++,i.label=12;case 12:return o++,[3,3];case 13:return[2]}}))}))},n.prototype.renderDashedDottedBorder=function(e,t,n,A,a){return r(this,void 0,void 0,(function(){var r,o,s,l,u,c,d,h,f,p,g,m,v,y,w,B;return i(this,(function(i){return 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e=this.io;this.subs=[ah(e,"open",this.onopen.bind(this)),ah(e,"packet",this.onpacket.bind(this)),ah(e,"error",this.onerror.bind(this)),ah(e,"close",this.onclose.bind(this))]}}},{key:"active",get:function(){return!!this.subs}},{key:"connect",value:function(){return this.connected||(this.subEvents(),this.io._reconnecting||this.io.open(),"open"===this.io._readyState&&this.onopen()),this}},{key:"open",value:function(){return this.connect()}},{key:"send",value:function(){for(var e=arguments.length,t=new Array(e),n=0;n1?t-1:0),r=1;r1?n-1:0),i=1;in._opts.retries&&(n._queue.shift(),t&&t(e));else if(n._queue.shift(),t){for(var i=arguments.length,A=new Array(i>1?i-1:0),a=1;a0&&void 0!==arguments[0]&&arguments[0];if(this.connected&&0!==this._queue.length){var t=this._queue[0];t.pending&&!e||(t.pending=!0,t.tryCount++,this.flags=t.flags,this.emit.apply(this,t.args))}}},{key:"packet",value:function(e){e.nsp=this.nsp,this.io._packet(e)}},{key:"onopen",value:function(){var e=this;"function"==typeof this.auth?this.auth((function(t){e._sendConnectPacket(t)})):this._sendConnectPacket(this.auth)}},{key:"_sendConnectPacket",value:function(e){this.packet({type:th.CONNECT,data:this._pid?Object.assign({pid:this._pid,offset:this._lastOffset},e):e})}},{key:"onerror",value:function(e){this.connected||this.emitReserved("connect_error",e)}},{key:"onclose",value:function(e,t){this.connected=!1,delete this.id,this.emitReserved("disconnect",e,t)}},{key:"onpacket",value:function(e){if(e.nsp===this.nsp)switch(e.type){case th.CONNECT:e.data&&e.data.sid?this.onconnect(e.data.sid,e.data.pid):this.emitReserved("connect_error",new Error("It seems you are trying to reach a Socket.IO server in v2.x with a v3.x client, but they are not compatible (more information here: https://socket.io/docs/v3/migrating-from-2-x-to-3-0/)"));break;case th.EVENT:case th.BINARY_EVENT:this.onevent(e);break;case th.ACK:case th.BINARY_ACK:this.onack(e);break;case th.DISCONNECT:this.ondisconnect();break;case th.CONNECT_ERROR:this.destroy();var t=new Error(e.data.message);t.data=e.data.data,this.emitReserved("connect_error",t)}}},{key:"onevent",value:function(e){var t=e.data||[];null!=e.id&&t.push(this.ack(e.id)),this.connected?this.emitEvent(t):this.receiveBuffer.push(Object.freeze(t))}},{key:"emitEvent",value:function(e){if(this._anyListeners&&this._anyListeners.length){var t,r=k(this._anyListeners.slice());try{for(r.s();!(t=r.n()).done;){t.value.apply(this,e)}}catch(Xx){r.e(Xx)}finally{r.f()}}jc(S(n.prototype),"emit",this).apply(this,e),this._pid&&e.length&&"string"===typeof e[e.length-1]&&(this._lastOffset=e[e.length-1])}},{key:"ack",value:function(e){var t=this,n=!1;return function(){if(!n){n=!0;for(var r=arguments.length,i=new Array(r),A=0;A0&&e.jitter<=1?e.jitter:0,this.attempts=0}lh.prototype.duration=function(){var e=this.ms*Math.pow(this.factor,this.attempts++);if(this.jitter){var t=Math.random(),n=Math.floor(t*this.jitter*e);e=0==(1&Math.floor(10*t))?e-n:e+n}return 0|Math.min(e,this.max)},lh.prototype.reset=function(){this.attempts=0},lh.prototype.setMin=function(e){this.ms=e},lh.prototype.setMax=function(e){this.max=e},lh.prototype.setJitter=function(e){this.jitter=e};var uh=function(t){C(r,t);var n=M(r);function r(t,i){var A,a;B(this,r),(A=n.call(this)).nsps={},A.subs=[],t&&"object"===typeof t&&(i=t,t=void 0),(i=i||{}).path=i.path||"/socket.io",A.opts=i,fd(U(A),i),A.reconnection(!1!==i.reconnection),A.reconnectionAttempts(i.reconnectionAttempts||1/0),A.reconnectionDelay(i.reconnectionDelay||1e3),A.reconnectionDelayMax(i.reconnectionDelayMax||5e3),A.randomizationFactor(null!==(a=i.randomizationFactor)&&void 0!==a?a:.5),A.backoff=new lh({min:A.reconnectionDelay(),max:A.reconnectionDelayMax(),jitter:A.randomizationFactor()}),A.timeout(null==i.timeout?2e4:i.timeout),A._readyState="closed",A.uri=t;var o=i.parser||e;return A.encoder=new o.Encoder,A.decoder=new o.Decoder,A._autoConnect=!1!==i.autoConnect,A._autoConnect&&A.open(),A}return b(r,[{key:"reconnection",value:function(e){return arguments.length?(this._reconnection=!!e,this):this._reconnection}},{key:"reconnectionAttempts",value:function(e){return void 0===e?this._reconnectionAttempts:(this._reconnectionAttempts=e,this)}},{key:"reconnectionDelay",value:function(e){var t;return void 0===e?this._reconnectionDelay:(this._reconnectionDelay=e,null===(t=this.backoff)||void 0===t||t.setMin(e),this)}},{key:"randomizationFactor",value:function(e){var t;return void 0===e?this._randomizationFactor:(this._randomizationFactor=e,null===(t=this.backoff)||void 0===t||t.setJitter(e),this)}},{key:"reconnectionDelayMax",value:function(e){var t;return void 0===e?this._reconnectionDelayMax:(this._reconnectionDelayMax=e,null===(t=this.backoff)||void 0===t||t.setMax(e),this)}},{key:"timeout",value:function(e){return arguments.length?(this._timeout=e,this):this._timeout}},{key:"maybeReconnectOnOpen",value:function(){!this._reconnecting&&this._reconnection&&0===this.backoff.attempts&&this.reconnect()}},{key:"open",value:function(e){var t=this;if(~this._readyState.indexOf("open"))return this;this.engine=new zd(this.uri,this.opts);var n=this.engine,r=this;this._readyState="opening",this.skipReconnect=!1;var i=ah(n,"open",(function(){r.onopen(),e&&e()})),A=ah(n,"error",(function(n){r.cleanup(),r._readyState="closed",t.emitReserved("error",n),e?e(n):r.maybeReconnectOnOpen()}));if(!1!==this._timeout){var a=this._timeout;0===a&&i();var o=this.setTimeoutFn((function(){i(),n.close(),n.emit("error",new Error("timeout"))}),a);this.opts.autoUnref&&o.unref(),this.subs.push((function(){clearTimeout(o)}))}return this.subs.push(i),this.subs.push(A),this}},{key:"connect",value:function(e){return this.open(e)}},{key:"onopen",value:function(){this.cleanup(),this._readyState="open",this.emitReserved("open");var e=this.engine;this.subs.push(ah(e,"ping",this.onping.bind(this)),ah(e,"data",this.ondata.bind(this)),ah(e,"error",this.onerror.bind(this)),ah(e,"close",this.onclose.bind(this)),ah(this.decoder,"decoded",this.ondecoded.bind(this)))}},{key:"onping",value:function(){this.emitReserved("ping")}},{key:"ondata",value:function(e){try{this.decoder.add(e)}catch(t){this.onclose("parse error",t)}}},{key:"ondecoded",value:function(e){var t=this;Dd((function(){t.emitReserved("packet",e)}),this.setTimeoutFn)}},{key:"onerror",value:function(e){this.emitReserved("error",e)}},{key:"socket",value:function(e,t){var n=this.nsps[e];return n?this._autoConnect&&!n.active&&n.connect():(n=new sh(this,e,t),this.nsps[e]=n),n}},{key:"_destroy",value:function(e){for(var t=0,n=Object.keys(this.nsps);t=this._reconnectionAttempts)this.backoff.reset(),this.emitReserved("reconnect_failed"),this._reconnecting=!1;else{var n=this.backoff.duration();this._reconnecting=!0;var r=this.setTimeoutFn((function(){t.skipReconnect||(e.emitReserved("reconnect_attempt",t.backoff.attempts),t.skipReconnect||t.open((function(n){n?(t._reconnecting=!1,t.reconnect(),e.emitReserved("reconnect_error",n)):t.onreconnect()})))}),n);this.opts.autoUnref&&r.unref(),this.subs.push((function(){clearTimeout(r)}))}}},{key:"onreconnect",value:function(){var e=this.backoff.attempts;this._reconnecting=!1,this.backoff.reset(),this.emitReserved("reconnect",e)}}]),r}(ld),ch={};function dh(e,t){"object"===typeof e&&(t=e,e=void 0);var n,r=function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"",n=arguments.length>2?arguments[2]:void 0,r=e;n=n||"undefined"!==typeof location&&location,null==e&&(e=n.protocol+"//"+n.host),"string"===typeof e&&("/"===e.charAt(0)&&(e="/"===e.charAt(1)?n.protocol+e:n.host+e),/^(https?|wss?):\/\//.test(e)||(e="undefined"!==typeof n?n.protocol+"//"+e:"https://"+e),r=Vd(e)),r.port||(/^(http|ws)$/.test(r.protocol)?r.port="80":/^(http|ws)s$/.test(r.protocol)&&(r.port="443")),r.path=r.path||"/";var i=-1!==r.host.indexOf(":")?"["+r.host+"]":r.host;return r.id=r.protocol+"://"+i+":"+r.port+t,r.href=r.protocol+"://"+i+(n&&n.port===r.port?"":":"+r.port),r}(e,(t=t||{}).path||"/socket.io"),i=r.source,A=r.id,a=r.path,o=ch[A]&&a in ch[A].nsps;return t.forceNew||t["force new connection"]||!1===t.multiplex||o?n=new uh(i,t):(ch[A]||(ch[A]=new uh(i,t)),n=ch[A]),r.query&&!t.query&&(t.query=r.queryKey),n.socket(r.path,t)}Object.assign(dh,{Manager:uh,Socket:sh,io:dh,connect:dh});var hh,fh="https://hyperhuman.deemos.com/api",ph=Wc,gh=function(e){e&&(ph=Wc.create({headers:{Authorization:"Bearer ".concat(e)}}))},mh={username:"huggingface",email:"merife6322@duiter.com",password:"123456"},vh=function(e){var t=e.email,n=e.password;return ph.post("".concat(fh,"/user/login"),{email:t,password:n})},yh=function(e){var t=e.user_uuid,n=e.username;return ph.post("".concat(fh,"/user/get_info"),{user_uuid:t,username:n})},wh=function(){var e=l(o().mark((function e(){return o().wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(!hh){e.next=2;break}return e.abrupt("return",!1);case 2:return console.log("start chat"),e.abrupt("return",ph.get("".concat(fh,"/chat").concat("")));case 4:case"end":return e.stop()}}),e)})));return function(){return e.apply(this,arguments)}}(),Bh=function(){hh&&hh.connected&&(console.log("close ws"),hh.close(),console.log(hh))},_h=function(e){var t=e.task_uuid,n=e.prompt;return ph.post("".concat(fh,"/task/generate"),{task_uuid:t,prompt:n})},bh=function(e){return ph.post("".concat(fh,"/task/check_progress/").concat(e))},xh=function(e){var t=e.type,n=e.page_num;return Wc.post("".concat(fh,"/task/cards"),{type:t,page_num:n})},Ch=function(e){return Wc.post("".concat(fh,"/task/card/").concat(e))},Sh=function(e){var t=e.task_uuid,n=e.type,r=e.name,i=e.token;return 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this.convert(e,t,this.workingColorSpace)}},Zg={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},$g={r:0,g:0,b:0},em={h:0,s:0,l:0},tm={h:0,s:0,l:0};function nm(e,t,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?e+6*(t-e)*n:n<.5?t:n<2/3?e+6*(t-e)*(2/3-n):e}function rm(e,t){return t.r=e.r,t.g=e.g,t.b=e.b,t}var im,Am=function(e){function t(e,n,r){return B(this,t),this.isColor=!0,this.r=1,this.g=1,this.b=1,void 0===n&&void 0===r?this.set(e):this.setRGB(e,n,r)}return b(t,[{key:"set",value:function(e){return e&&e.isColor?this.copy(e):"number"===typeof e?this.setHex(e):"string"===typeof e&&this.setStyle(e),this}},{key:"setScalar",value:function(e){return this.r=e,this.g=e,this.b=e,this}},{key:"setHex",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:Bg;return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(255&e)/255,Jg.toWorkingColorSpace(this,t),this}},{key:"setRGB",value:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:Jg.workingColorSpace;return this.r=e,this.g=t,this.b=n,Jg.toWorkingColorSpace(this,r),this}},{key:"setHSL",value:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:Jg.workingColorSpace;if(e=Dg(e,1),t=Lg(t,0,1),n=Lg(n,0,1),0===t)this.r=this.g=this.b=n;else{var i=n<=.5?n*(1+t):n+t-n*t,A=2*n-i;this.r=nm(A,i,e+1/3),this.g=nm(A,i,e),this.b=nm(A,i,e-1/3)}return Jg.toWorkingColorSpace(this,r),this}},{key:"setStyle",value:function(e){var t,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:Bg;function r(t){void 0!==t&&parseFloat(t)<1&&console.warn("THREE.Color: Alpha component of "+e+" will be ignored.")}if(t=/^((?:rgb|hsl)a?)\(([^\)]*)\)/.exec(e)){var i,A=t[1],a=t[2];switch(A){case"rgb":case"rgba":if(i=/^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(a))return this.r=Math.min(255,parseInt(i[1],10))/255,this.g=Math.min(255,parseInt(i[2],10))/255,this.b=Math.min(255,parseInt(i[3],10))/255,Jg.toWorkingColorSpace(this,n),r(i[4]),this;if(i=/^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(a))return this.r=Math.min(100,parseInt(i[1],10))/100,this.g=Math.min(100,parseInt(i[2],10))/100,this.b=Math.min(100,parseInt(i[3],10))/100,Jg.toWorkingColorSpace(this,n),r(i[4]),this;break;case"hsl":case"hsla":if(i=/^\s*(\d*\.?\d+)\s*,\s*(\d*\.?\d+)\%\s*,\s*(\d*\.?\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(a)){var o=parseFloat(i[1])/360,s=parseFloat(i[2])/100,l=parseFloat(i[3])/100;return r(i[4]),this.setHSL(o,s,l,n)}}}else if(t=/^\#([A-Fa-f\d]+)$/.exec(e)){var u=t[1],c=u.length;if(3===c)return this.r=parseInt(u.charAt(0)+u.charAt(0),16)/255,this.g=parseInt(u.charAt(1)+u.charAt(1),16)/255,this.b=parseInt(u.charAt(2)+u.charAt(2),16)/255,Jg.toWorkingColorSpace(this,n),this;if(6===c)return this.r=parseInt(u.charAt(0)+u.charAt(1),16)/255,this.g=parseInt(u.charAt(2)+u.charAt(3),16)/255,this.b=parseInt(u.charAt(4)+u.charAt(5),16)/255,Jg.toWorkingColorSpace(this,n),this}return e&&e.length>0?this.setColorName(e,n):this}},{key:"setColorName",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:Bg,n=Zg[e.toLowerCase()];return void 0!==n?this.setHex(n,t):console.warn("THREE.Color: Unknown color "+e),this}},{key:"clone",value:function(){return new this.constructor(this.r,this.g,this.b)}},{key:"copy",value:function(e){return this.r=e.r,this.g=e.g,this.b=e.b,this}},{key:"copySRGBToLinear",value:function(e){return this.r=Xg(e.r),this.g=Xg(e.g),this.b=Xg(e.b),this}},{key:"copyLinearToSRGB",value:function(e){return this.r=qg(e.r),this.g=qg(e.g),this.b=qg(e.b),this}},{key:"convertSRGBToLinear",value:function(){return this.copySRGBToLinear(this),this}},{key:"convertLinearToSRGB",value:function(){return this.copyLinearToSRGB(this),this}},{key:"getHex",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:Bg;return Jg.fromWorkingColorSpace(rm(this,$g),e),Lg(255*$g.r,0,255)<<16^Lg(255*$g.g,0,255)<<8^Lg(255*$g.b,0,255)<<0}},{key:"getHexString",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:Bg;return("000000"+this.getHex(e).toString(16)).slice(-6)}},{key:"getHSL",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:Jg.workingColorSpace;Jg.fromWorkingColorSpace(rm(this,$g),t);var n,r,i=$g.r,A=$g.g,a=$g.b,o=Math.max(i,A,a),s=Math.min(i,A,a),l=(s+o)/2;if(s===o)n=0,r=0;else{var u=o-s;switch(r=l<=.5?u/(o+s):u/(2-o-s),o){case i:n=(A-a)/u+(A1&&void 0!==arguments[1]?arguments[1]:Jg.workingColorSpace;return Jg.fromWorkingColorSpace(rm(this,$g),t),e.r=$g.r,e.g=$g.g,e.b=$g.b,e}},{key:"getStyle",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:Bg;return Jg.fromWorkingColorSpace(rm(this,$g),e),e!==Bg?"color(".concat(e," ").concat($g.r," ").concat($g.g," ").concat($g.b,")"):"rgb(".concat(255*$g.r|0,",").concat(255*$g.g|0,",").concat(255*$g.b|0,")")}},{key:"offsetHSL",value:function(e,t,n){return this.getHSL(em),em.h+=e,em.s+=t,em.l+=n,this.setHSL(em.h,em.s,em.l),this}},{key:"add",value:function(e){return this.r+=e.r,this.g+=e.g,this.b+=e.b,this}},{key:"addColors",value:function(e,t){return this.r=e.r+t.r,this.g=e.g+t.g,this.b=e.b+t.b,this}},{key:"addScalar",value:function(e){return this.r+=e,this.g+=e,this.b+=e,this}},{key:"sub",value:function(e){return this.r=Math.max(0,this.r-e.r),this.g=Math.max(0,this.g-e.g),this.b=Math.max(0,this.b-e.b),this}},{key:"multiply",value:function(e){return this.r*=e.r,this.g*=e.g,this.b*=e.b,this}},{key:"multiplyScalar",value:function(e){return this.r*=e,this.g*=e,this.b*=e,this}},{key:"lerp",value:function(e,t){return this.r+=(e.r-this.r)*t,this.g+=(e.g-this.g)*t,this.b+=(e.b-this.b)*t,this}},{key:"lerpColors",value:function(e,t,n){return this.r=e.r+(t.r-e.r)*n,this.g=e.g+(t.g-e.g)*n,this.b=e.b+(t.b-e.b)*n,this}},{key:"lerpHSL",value:function(e,t){this.getHSL(em),e.getHSL(tm);var n=Ig(em.h,tm.h,t),r=Ig(em.s,tm.s,t),i=Ig(em.l,tm.l,t);return this.setHSL(n,r,i),this}},{key:"equals",value:function(e){return e.r===this.r&&e.g===this.g&&e.b===this.b}},{key:"fromArray",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return this.r=e[t],this.g=e[t+1],this.b=e[t+2],this}},{key:"toArray",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return e[t]=this.r,e[t+1]=this.g,e[t+2]=this.b,e}},{key:"fromBufferAttribute",value:function(e,t){return this.r=e.getX(t),this.g=e.getY(t),this.b=e.getZ(t),this}},{key:"toJSON",value:function(){return this.getHex()}},{key:Symbol.iterator,value:o().mark((function e(){return o().wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.r;case 2:return e.next=4,this.g;case 4:return e.next=6,this.b;case 6:case"end":return e.stop()}}),e,this)}))}]),t}();Am.NAMES=Zg;var am=function(){function e(){B(this,e)}return b(e,null,[{key:"getDataURL",value:function(e){if(/^data:/i.test(e.src))return e.src;if("undefined"==typeof HTMLCanvasElement)return e.src;var t;if(e instanceof HTMLCanvasElement)t=e;else{void 0===im&&(im=jg("canvas")),im.width=e.width,im.height=e.height;var n=im.getContext("2d");e instanceof ImageData?n.putImageData(e,0,0):n.drawImage(e,0,0,e.width,e.height),t=im}return t.width>2048||t.height>2048?(console.warn("THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons",e),t.toDataURL("image/jpeg",.6)):t.toDataURL("image/png")}},{key:"sRGBToLinear",value:function(e){if("undefined"!==typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!==typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!==typeof ImageBitmap&&e instanceof ImageBitmap){var t=jg("canvas");t.width=e.width,t.height=e.height;var n=t.getContext("2d");n.drawImage(e,0,0,e.width,e.height);for(var r=n.getImageData(0,0,e.width,e.height),i=r.data,A=0;A0&&void 0!==arguments[0]?arguments[0]:null;B(this,e),this.isSource=!0,this.uuid=Qg(),this.data=t,this.version=0}return b(e,[{key:"needsUpdate",set:function(e){!0===e&&this.version++}},{key:"toJSON",value:function(e){var t=void 0===e||"string"===typeof e;if(!t&&void 0!==e.images[this.uuid])return e.images[this.uuid];var n={uuid:this.uuid,url:""},r=this.data;if(null!==r){var i;if(Array.isArray(r)){i=[];for(var A=0,a=r.length;A0&&void 0!==arguments[0]?arguments[0]:n.DEFAULT_IMAGE,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:n.DEFAULT_MAPPING,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:np,a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:np,o=arguments.length>4&&void 0!==arguments[4]?arguments[4]:op,s=arguments.length>5&&void 0!==arguments[5]?arguments[5]:lp,l=arguments.length>6&&void 0!==arguments[6]?arguments[6]:bp,u=arguments.length>7&&void 0!==arguments[7]?arguments[7]:cp,c=arguments.length>8&&void 0!==arguments[8]?arguments[8]:n.DEFAULT_ANISOTROPY,d=arguments.length>9&&void 0!==arguments[9]?arguments[9]:pg;return B(this,n),(e=t.call(this)).isTexture=!0,Object.defineProperty(U(e),"id",{value:lm++}),e.uuid=Qg(),e.name="",e.source=new om(r),e.mipmaps=[],e.mapping=i,e.wrapS=A,e.wrapT=a,e.magFilter=o,e.minFilter=s,e.anisotropy=c,e.format=l,e.internalFormat=null,e.type=u,e.offset=new zg(0,0),e.repeat=new zg(1,1),e.center=new zg(0,0),e.rotation=0,e.matrixAutoUpdate=!0,e.matrix=new Gg,e.generateMipmaps=!0,e.premultiplyAlpha=!1,e.flipY=!0,e.unpackAlignment=4,e.encoding=d,e.userData={},e.version=0,e.onUpdate=null,e.isRenderTargetTexture=!1,e.needsPMREMUpdate=!1,e}return b(n,[{key:"image",get:function(){return this.source.data},set:function(e){this.source.data=e}},{key:"updateMatrix",value:function(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}},{key:"clone",value:function(){return(new this.constructor).copy(this)}},{key:"copy",value:function(e){return this.name=e.name,this.source=e.source,this.mipmaps=e.mipmaps.slice(0),this.mapping=e.mapping,this.wrapS=e.wrapS,this.wrapT=e.wrapT,this.magFilter=e.magFilter,this.minFilter=e.minFilter,this.anisotropy=e.anisotropy,this.format=e.format,this.internalFormat=e.internalFormat,this.type=e.type,this.offset.copy(e.offset),this.repeat.copy(e.repeat),this.center.copy(e.center),this.rotation=e.rotation,this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrix.copy(e.matrix),this.generateMipmaps=e.generateMipmaps,this.premultiplyAlpha=e.premultiplyAlpha,this.flipY=e.flipY,this.unpackAlignment=e.unpackAlignment,this.encoding=e.encoding,this.userData=JSON.parse(JSON.stringify(e.userData)),this.needsUpdate=!0,this}},{key:"toJSON",value:function(e){var t=void 0===e||"string"===typeof e;if(!t&&void 0!==e.textures[this.uuid])return e.textures[this.uuid];var n={metadata:{version:4.5,type:"Texture",generator:"Texture.toJSON"},uuid:this.uuid,name:this.name,image:this.source.toJSON(e).uuid,mapping:this.mapping,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,type:this.type,encoding:this.encoding,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,generateMipmaps:this.generateMipmaps,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};return Object.keys(this.userData).length>0&&(n.userData=this.userData),t||(e.textures[this.uuid]=n),n}},{key:"dispose",value:function(){this.dispatchEvent({type:"dispose"})}},{key:"transformUv",value:function(e){if(300!==this.mapping)return e;if(e.applyMatrix3(this.matrix),e.x<0||e.x>1)switch(this.wrapS){case tp:e.x=e.x-Math.floor(e.x);break;case np:e.x=e.x<0?0:1;break;case rp:1===Math.abs(Math.floor(e.x)%2)?e.x=Math.ceil(e.x)-e.x:e.x=e.x-Math.floor(e.x)}if(e.y<0||e.y>1)switch(this.wrapT){case tp:e.y=e.y-Math.floor(e.y);break;case np:e.y=e.y<0?0:1;break;case rp:1===Math.abs(Math.floor(e.y)%2)?e.y=Math.ceil(e.y)-e.y:e.y=e.y-Math.floor(e.y)}return this.flipY&&(e.y=1-e.y),e}},{key:"needsUpdate",set:function(e){!0===e&&(this.version++,this.source.needsUpdate=!0)}}]),n}(Ug);um.DEFAULT_IMAGE=null,um.DEFAULT_MAPPING=300,um.DEFAULT_ANISOTROPY=1;var cm=function(e){function t(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:0,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0,i=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1;B(this,t),t.prototype.isVector4=!0,this.x=e,this.y=n,this.z=r,this.w=i}return b(t,[{key:"width",get:function(){return this.z},set:function(e){this.z=e}},{key:"height",get:function(){return this.w},set:function(e){this.w=e}},{key:"set",value:function(e,t,n,r){return this.x=e,this.y=t,this.z=n,this.w=r,this}},{key:"setScalar",value:function(e){return this.x=e,this.y=e,this.z=e,this.w=e,this}},{key:"setX",value:function(e){return this.x=e,this}},{key:"setY",value:function(e){return this.y=e,this}},{key:"setZ",value:function(e){return this.z=e,this}},{key:"setW",value:function(e){return this.w=e,this}},{key:"setComponent",value:function(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;case 3:this.w=t;break;default:throw new Error("index is out of range: "+e)}return this}},{key:"getComponent",value:function(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error("index is out of range: "+e)}}},{key:"clone",value:function(){return new this.constructor(this.x,this.y,this.z,this.w)}},{key:"copy",value:function(e){return this.x=e.x,this.y=e.y,this.z=e.z,this.w=void 0!==e.w?e.w:1,this}},{key:"add",value:function(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this.w+=e.w,this}},{key:"addScalar",value:function(e){return this.x+=e,this.y+=e,this.z+=e,this.w+=e,this}},{key:"addVectors",value:function(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this.w=e.w+t.w,this}},{key:"addScaledVector",value:function(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this.w+=e.w*t,this}},{key:"sub",value:function(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this.w-=e.w,this}},{key:"subScalar",value:function(e){return this.x-=e,this.y-=e,this.z-=e,this.w-=e,this}},{key:"subVectors",value:function(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this.w=e.w-t.w,this}},{key:"multiply",value:function(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this.w*=e.w,this}},{key:"multiplyScalar",value:function(e){return this.x*=e,this.y*=e,this.z*=e,this.w*=e,this}},{key:"applyMatrix4",value:function(e){var t=this.x,n=this.y,r=this.z,i=this.w,A=e.elements;return this.x=A[0]*t+A[4]*n+A[8]*r+A[12]*i,this.y=A[1]*t+A[5]*n+A[9]*r+A[13]*i,this.z=A[2]*t+A[6]*n+A[10]*r+A[14]*i,this.w=A[3]*t+A[7]*n+A[11]*r+A[15]*i,this}},{key:"divideScalar",value:function(e){return this.multiplyScalar(1/e)}},{key:"setAxisAngleFromQuaternion",value:function(e){this.w=2*Math.acos(e.w);var t=Math.sqrt(1-e.w*e.w);return t<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=e.x/t,this.y=e.y/t,this.z=e.z/t),this}},{key:"setAxisAngleFromRotationMatrix",value:function(e){var t,n,r,i,A=.01,a=.1,o=e.elements,s=o[0],l=o[4],u=o[8],c=o[1],d=o[5],h=o[9],f=o[2],p=o[6],g=o[10];if(Math.abs(l-c)v&&m>y?my?v1&&void 0!==arguments[1]?arguments[1]:0;return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this.w=e[t+3],this}},{key:"toArray",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e[t+3]=this.w,e}},{key:"fromBufferAttribute",value:function(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this.w=e.getW(t),this}},{key:"random",value:function(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this.w=Math.random(),this}},{key:Symbol.iterator,value:o().mark((function e(){return o().wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.x;case 2:return e.next=4,this.y;case 4:return e.next=6,this.z;case 6:return e.next=8,this.w;case 8:case"end":return e.stop()}}),e,this)}))}]),t}(),dm=function(e){C(n,e);var t=M(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:1,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{};B(this,n),(e=t.call(this)).isWebGLRenderTarget=!0,e.width=r,e.height=i,e.depth=1,e.scissor=new cm(0,0,r,i),e.scissorTest=!1,e.viewport=new cm(0,0,r,i);var a={width:r,height:i,depth:1};return e.texture=new um(a,A.mapping,A.wrapS,A.wrapT,A.magFilter,A.minFilter,A.format,A.type,A.anisotropy,A.encoding),e.texture.isRenderTargetTexture=!0,e.texture.flipY=!1,e.texture.generateMipmaps=void 0!==A.generateMipmaps&&A.generateMipmaps,e.texture.internalFormat=void 0!==A.internalFormat?A.internalFormat:null,e.texture.minFilter=void 0!==A.minFilter?A.minFilter:op,e.depthBuffer=void 0===A.depthBuffer||A.depthBuffer,e.stencilBuffer=void 0!==A.stencilBuffer&&A.stencilBuffer,e.depthTexture=void 0!==A.depthTexture?A.depthTexture:null,e.samples=void 0!==A.samples?A.samples:0,e}return b(n,[{key:"setSize",value:function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:1;this.width===e&&this.height===t&&this.depth===n||(this.width=e,this.height=t,this.depth=n,this.texture.image.width=e,this.texture.image.height=t,this.texture.image.depth=n,this.dispose()),this.viewport.set(0,0,e,t),this.scissor.set(0,0,e,t)}},{key:"clone",value:function(){return(new this.constructor).copy(this)}},{key:"copy",value:function(e){this.width=e.width,this.height=e.height,this.depth=e.depth,this.viewport.copy(e.viewport),this.texture=e.texture.clone(),this.texture.isRenderTargetTexture=!0;var t=Object.assign({},e.texture.image);return this.texture.source=new om(t),this.depthBuffer=e.depthBuffer,this.stencilBuffer=e.stencilBuffer,null!==e.depthTexture&&(this.depthTexture=e.depthTexture.clone()),this.samples=e.samples,this}},{key:"dispose",value:function(){this.dispatchEvent({type:"dispose"})}}]),n}(Ug),hm=function(e){C(n,e);var t=M(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:null,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:1,a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1;return B(this,n),(e=t.call(this,null)).isDataArrayTexture=!0,e.image={data:r,width:i,height:A,depth:a},e.magFilter=ip,e.minFilter=ip,e.wrapR=np,e.generateMipmaps=!1,e.flipY=!1,e.unpackAlignment=1,e}return b(n)}(um),fm=function(e){C(n,e);var t=M(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:null,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:1,a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1;return B(this,n),(e=t.call(this,null)).isData3DTexture=!0,e.image={data:r,width:i,height:A,depth:a},e.magFilter=ip,e.minFilter=ip,e.wrapR=np,e.generateMipmaps=!1,e.flipY=!1,e.unpackAlignment=1,e}return b(n)}(um),pm=function(e){function t(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:0,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0,i=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1;B(this,t),this.isQuaternion=!0,this._x=e,this._y=n,this._z=r,this._w=i}return b(t,[{key:"x",get:function(){return this._x},set:function(e){this._x=e,this._onChangeCallback()}},{key:"y",get:function(){return this._y},set:function(e){this._y=e,this._onChangeCallback()}},{key:"z",get:function(){return this._z},set:function(e){this._z=e,this._onChangeCallback()}},{key:"w",get:function(){return this._w},set:function(e){this._w=e,this._onChangeCallback()}},{key:"set",value:function(e,t,n,r){return this._x=e,this._y=t,this._z=n,this._w=r,this._onChangeCallback(),this}},{key:"clone",value:function(){return new this.constructor(this._x,this._y,this._z,this._w)}},{key:"copy",value:function(e){return this._x=e.x,this._y=e.y,this._z=e.z,this._w=e.w,this._onChangeCallback(),this}},{key:"setFromEuler",value:function(e,t){var n=e._x,r=e._y,i=e._z,A=e._order,a=Math.cos,o=Math.sin,s=a(n/2),l=a(r/2),u=a(i/2),c=o(n/2),d=o(r/2),h=o(i/2);switch(A){case"XYZ":this._x=c*l*u+s*d*h,this._y=s*d*u-c*l*h,this._z=s*l*h+c*d*u,this._w=s*l*u-c*d*h;break;case"YXZ":this._x=c*l*u+s*d*h,this._y=s*d*u-c*l*h,this._z=s*l*h-c*d*u,this._w=s*l*u+c*d*h;break;case"ZXY":this._x=c*l*u-s*d*h,this._y=s*d*u+c*l*h,this._z=s*l*h+c*d*u,this._w=s*l*u-c*d*h;break;case"ZYX":this._x=c*l*u-s*d*h,this._y=s*d*u+c*l*h,this._z=s*l*h-c*d*u,this._w=s*l*u+c*d*h;break;case"YZX":this._x=c*l*u+s*d*h,this._y=s*d*u+c*l*h,this._z=s*l*h-c*d*u,this._w=s*l*u-c*d*h;break;case"XZY":this._x=c*l*u-s*d*h,this._y=s*d*u-c*l*h,this._z=s*l*h+c*d*u,this._w=s*l*u+c*d*h;break;default:console.warn("THREE.Quaternion: .setFromEuler() encountered an unknown order: "+A)}return!1!==t&&this._onChangeCallback(),this}},{key:"setFromAxisAngle",value:function(e,t){var n=t/2,r=Math.sin(n);return this._x=e.x*r,this._y=e.y*r,this._z=e.z*r,this._w=Math.cos(n),this._onChangeCallback(),this}},{key:"setFromRotationMatrix",value:function(e){var t=e.elements,n=t[0],r=t[4],i=t[8],A=t[1],a=t[5],o=t[9],s=t[2],l=t[6],u=t[10],c=n+a+u;if(c>0){var d=.5/Math.sqrt(c+1);this._w=.25/d,this._x=(l-o)*d,this._y=(i-s)*d,this._z=(A-r)*d}else if(n>a&&n>u){var h=2*Math.sqrt(1+n-a-u);this._w=(l-o)/h,this._x=.25*h,this._y=(r+A)/h,this._z=(i+s)/h}else if(a>u){var f=2*Math.sqrt(1+a-n-u);this._w=(i-s)/f,this._x=(r+A)/f,this._y=.25*f,this._z=(o+l)/f}else{var p=2*Math.sqrt(1+u-n-a);this._w=(A-r)/p,this._x=(i+s)/p,this._y=(o+l)/p,this._z=.25*p}return this._onChangeCallback(),this}},{key:"setFromUnitVectors",value:function(e,t){var n=e.dot(t)+1;return nMath.abs(e.z)?(this._x=-e.y,this._y=e.x,this._z=0,this._w=n):(this._x=0,this._y=-e.z,this._z=e.y,this._w=n)):(this._x=e.y*t.z-e.z*t.y,this._y=e.z*t.x-e.x*t.z,this._z=e.x*t.y-e.y*t.x,this._w=n),this.normalize()}},{key:"angleTo",value:function(e){return 2*Math.acos(Math.abs(Lg(this.dot(e),-1,1)))}},{key:"rotateTowards",value:function(e,t){var n=this.angleTo(e);if(0===n)return this;var r=Math.min(1,t/n);return this.slerp(e,r),this}},{key:"identity",value:function(){return this.set(0,0,0,1)}},{key:"invert",value:function(){return this.conjugate()}},{key:"conjugate",value:function(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}},{key:"dot",value:function(e){return this._x*e._x+this._y*e._y+this._z*e._z+this._w*e._w}},{key:"lengthSq",value:function(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}},{key:"length",value:function(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}},{key:"normalize",value:function(){var e=this.length();return 0===e?(this._x=0,this._y=0,this._z=0,this._w=1):(e=1/e,this._x=this._x*e,this._y=this._y*e,this._z=this._z*e,this._w=this._w*e),this._onChangeCallback(),this}},{key:"multiply",value:function(e){return this.multiplyQuaternions(this,e)}},{key:"premultiply",value:function(e){return this.multiplyQuaternions(e,this)}},{key:"multiplyQuaternions",value:function(e,t){var n=e._x,r=e._y,i=e._z,A=e._w,a=t._x,o=t._y,s=t._z,l=t._w;return this._x=n*l+A*a+r*s-i*o,this._y=r*l+A*o+i*a-n*s,this._z=i*l+A*s+n*o-r*a,this._w=A*l-n*a-r*o-i*s,this._onChangeCallback(),this}},{key:"slerp",value:function(e,t){if(0===t)return this;if(1===t)return this.copy(e);var n=this._x,r=this._y,i=this._z,A=this._w,a=A*e._w+n*e._x+r*e._y+i*e._z;if(a<0?(this._w=-e._w,this._x=-e._x,this._y=-e._y,this._z=-e._z,a=-a):this.copy(e),a>=1)return this._w=A,this._x=n,this._y=r,this._z=i,this;var o=1-a*a;if(o<=Number.EPSILON){var s=1-t;return this._w=s*A+t*this._w,this._x=s*n+t*this._x,this._y=s*r+t*this._y,this._z=s*i+t*this._z,this.normalize(),this._onChangeCallback(),this}var l=Math.sqrt(o),u=Math.atan2(l,a),c=Math.sin((1-t)*u)/l,d=Math.sin(t*u)/l;return this._w=A*c+this._w*d,this._x=n*c+this._x*d,this._y=r*c+this._y*d,this._z=i*c+this._z*d,this._onChangeCallback(),this}},{key:"slerpQuaternions",value:function(e,t,n){return this.copy(e).slerp(t,n)}},{key:"random",value:function(){var e=Math.random(),t=Math.sqrt(1-e),n=Math.sqrt(e),r=2*Math.PI*Math.random(),i=2*Math.PI*Math.random();return this.set(t*Math.cos(r),n*Math.sin(i),n*Math.cos(i),t*Math.sin(r))}},{key:"equals",value:function(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._w===this._w}},{key:"fromArray",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return this._x=e[t],this._y=e[t+1],this._z=e[t+2],this._w=e[t+3],this._onChangeCallback(),this}},{key:"toArray",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._w,e}},{key:"fromBufferAttribute",value:function(e,t){return this._x=e.getX(t),this._y=e.getY(t),this._z=e.getZ(t),this._w=e.getW(t),this}},{key:"_onChange",value:function(e){return this._onChangeCallback=e,this}},{key:"_onChangeCallback",value:function(){}},{key:Symbol.iterator,value:o().mark((function e(){return o().wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this._x;case 2:return e.next=4,this._y;case 4:return e.next=6,this._z;case 6:return e.next=8,this._w;case 8:case"end":return e.stop()}}),e,this)}))}],[{key:"slerpFlat",value:function(e,t,n,r,i,A,a){var o=n[r+0],s=n[r+1],l=n[r+2],u=n[r+3],c=i[A+0],d=i[A+1],h=i[A+2],f=i[A+3];if(0===a)return e[t+0]=o,e[t+1]=s,e[t+2]=l,void(e[t+3]=u);if(1===a)return e[t+0]=c,e[t+1]=d,e[t+2]=h,void(e[t+3]=f);if(u!==f||o!==c||s!==d||l!==h){var p=1-a,g=o*c+s*d+l*h+u*f,m=g>=0?1:-1,v=1-g*g;if(v>Number.EPSILON){var y=Math.sqrt(v),w=Math.atan2(y,g*m);p=Math.sin(p*w)/y,a=Math.sin(a*w)/y}var B=a*m;if(o=o*p+c*B,s=s*p+d*B,l=l*p+h*B,u=u*p+f*B,p===1-a){var _=1/Math.sqrt(o*o+s*s+l*l+u*u);o*=_,s*=_,l*=_,u*=_}}e[t]=o,e[t+1]=s,e[t+2]=l,e[t+3]=u}},{key:"multiplyQuaternionsFlat",value:function(e,t,n,r,i,A){var a=n[r],o=n[r+1],s=n[r+2],l=n[r+3],u=i[A],c=i[A+1],d=i[A+2],h=i[A+3];return e[t]=a*h+l*u+o*d-s*c,e[t+1]=o*h+l*c+s*u-a*d,e[t+2]=s*h+l*d+a*c-o*u,e[t+3]=l*h-a*u-o*c-s*d,e}}]),t}(),gm=function(e){function t(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:0,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0;B(this,t),t.prototype.isVector3=!0,this.x=e,this.y=n,this.z=r}return b(t,[{key:"set",value:function(e,t,n){return void 0===n&&(n=this.z),this.x=e,this.y=t,this.z=n,this}},{key:"setScalar",value:function(e){return this.x=e,this.y=e,this.z=e,this}},{key:"setX",value:function(e){return this.x=e,this}},{key:"setY",value:function(e){return this.y=e,this}},{key:"setZ",value:function(e){return this.z=e,this}},{key:"setComponent",value:function(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;default:throw new Error("index is out of range: "+e)}return this}},{key:"getComponent",value:function(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error("index is out of range: "+e)}}},{key:"clone",value:function(){return new this.constructor(this.x,this.y,this.z)}},{key:"copy",value:function(e){return this.x=e.x,this.y=e.y,this.z=e.z,this}},{key:"add",value:function(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this}},{key:"addScalar",value:function(e){return this.x+=e,this.y+=e,this.z+=e,this}},{key:"addVectors",value:function(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this}},{key:"addScaledVector",value:function(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this}},{key:"sub",value:function(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this}},{key:"subScalar",value:function(e){return this.x-=e,this.y-=e,this.z-=e,this}},{key:"subVectors",value:function(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this}},{key:"multiply",value:function(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this}},{key:"multiplyScalar",value:function(e){return this.x*=e,this.y*=e,this.z*=e,this}},{key:"multiplyVectors",value:function(e,t){return this.x=e.x*t.x,this.y=e.y*t.y,this.z=e.z*t.z,this}},{key:"applyEuler",value:function(e){return this.applyQuaternion(vm.setFromEuler(e))}},{key:"applyAxisAngle",value:function(e,t){return this.applyQuaternion(vm.setFromAxisAngle(e,t))}},{key:"applyMatrix3",value:function(e){var t=this.x,n=this.y,r=this.z,i=e.elements;return this.x=i[0]*t+i[3]*n+i[6]*r,this.y=i[1]*t+i[4]*n+i[7]*r,this.z=i[2]*t+i[5]*n+i[8]*r,this}},{key:"applyNormalMatrix",value:function(e){return this.applyMatrix3(e).normalize()}},{key:"applyMatrix4",value:function(e){var t=this.x,n=this.y,r=this.z,i=e.elements,A=1/(i[3]*t+i[7]*n+i[11]*r+i[15]);return this.x=(i[0]*t+i[4]*n+i[8]*r+i[12])*A,this.y=(i[1]*t+i[5]*n+i[9]*r+i[13])*A,this.z=(i[2]*t+i[6]*n+i[10]*r+i[14])*A,this}},{key:"applyQuaternion",value:function(e){var t=this.x,n=this.y,r=this.z,i=e.x,A=e.y,a=e.z,o=e.w,s=o*t+A*r-a*n,l=o*n+a*t-i*r,u=o*r+i*n-A*t,c=-i*t-A*n-a*r;return this.x=s*o+c*-i+l*-a-u*-A,this.y=l*o+c*-A+u*-i-s*-a,this.z=u*o+c*-a+s*-A-l*-i,this}},{key:"project",value:function(e){return this.applyMatrix4(e.matrixWorldInverse).applyMatrix4(e.projectionMatrix)}},{key:"unproject",value:function(e){return this.applyMatrix4(e.projectionMatrixInverse).applyMatrix4(e.matrixWorld)}},{key:"transformDirection",value:function(e){var t=this.x,n=this.y,r=this.z,i=e.elements;return this.x=i[0]*t+i[4]*n+i[8]*r,this.y=i[1]*t+i[5]*n+i[9]*r,this.z=i[2]*t+i[6]*n+i[10]*r,this.normalize()}},{key:"divide",value:function(e){return this.x/=e.x,this.y/=e.y,this.z/=e.z,this}},{key:"divideScalar",value:function(e){return this.multiplyScalar(1/e)}},{key:"min",value:function(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this}},{key:"max",value:function(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this}},{key:"clamp",value:function(e,t){return this.x=Math.max(e.x,Math.min(t.x,this.x)),this.y=Math.max(e.y,Math.min(t.y,this.y)),this.z=Math.max(e.z,Math.min(t.z,this.z)),this}},{key:"clampScalar",value:function(e,t){return this.x=Math.max(e,Math.min(t,this.x)),this.y=Math.max(e,Math.min(t,this.y)),this.z=Math.max(e,Math.min(t,this.z)),this}},{key:"clampLength",value:function(e,t){var n=this.length();return this.divideScalar(n||1).multiplyScalar(Math.max(e,Math.min(t,n)))}},{key:"floor",value:function(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}},{key:"ceil",value:function(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}},{key:"round",value:function(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}},{key:"roundToZero",value:function(){return this.x=this.x<0?Math.ceil(this.x):Math.floor(this.x),this.y=this.y<0?Math.ceil(this.y):Math.floor(this.y),this.z=this.z<0?Math.ceil(this.z):Math.floor(this.z),this}},{key:"negate",value:function(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}},{key:"dot",value:function(e){return this.x*e.x+this.y*e.y+this.z*e.z}},{key:"lengthSq",value:function(){return this.x*this.x+this.y*this.y+this.z*this.z}},{key:"length",value:function(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}},{key:"manhattanLength",value:function(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}},{key:"normalize",value:function(){return this.divideScalar(this.length()||1)}},{key:"setLength",value:function(e){return this.normalize().multiplyScalar(e)}},{key:"lerp",value:function(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this}},{key:"lerpVectors",value:function(e,t,n){return this.x=e.x+(t.x-e.x)*n,this.y=e.y+(t.y-e.y)*n,this.z=e.z+(t.z-e.z)*n,this}},{key:"cross",value:function(e){return this.crossVectors(this,e)}},{key:"crossVectors",value:function(e,t){var n=e.x,r=e.y,i=e.z,A=t.x,a=t.y,o=t.z;return this.x=r*o-i*a,this.y=i*A-n*o,this.z=n*a-r*A,this}},{key:"projectOnVector",value:function(e){var t=e.lengthSq();if(0===t)return this.set(0,0,0);var n=e.dot(this)/t;return this.copy(e).multiplyScalar(n)}},{key:"projectOnPlane",value:function(e){return mm.copy(this).projectOnVector(e),this.sub(mm)}},{key:"reflect",value:function(e){return this.sub(mm.copy(e).multiplyScalar(2*this.dot(e)))}},{key:"angleTo",value:function(e){var t=Math.sqrt(this.lengthSq()*e.lengthSq());if(0===t)return Math.PI/2;var n=this.dot(e)/t;return Math.acos(Lg(n,-1,1))}},{key:"distanceTo",value:function(e){return Math.sqrt(this.distanceToSquared(e))}},{key:"distanceToSquared",value:function(e){var t=this.x-e.x,n=this.y-e.y,r=this.z-e.z;return t*t+n*n+r*r}},{key:"manhattanDistanceTo",value:function(e){return Math.abs(this.x-e.x)+Math.abs(this.y-e.y)+Math.abs(this.z-e.z)}},{key:"setFromSpherical",value:function(e){return this.setFromSphericalCoords(e.radius,e.phi,e.theta)}},{key:"setFromSphericalCoords",value:function(e,t,n){var r=Math.sin(t)*e;return this.x=r*Math.sin(n),this.y=Math.cos(t)*e,this.z=r*Math.cos(n),this}},{key:"setFromCylindrical",value:function(e){return this.setFromCylindricalCoords(e.radius,e.theta,e.y)}},{key:"setFromCylindricalCoords",value:function(e,t,n){return this.x=e*Math.sin(t),this.y=n,this.z=e*Math.cos(t),this}},{key:"setFromMatrixPosition",value:function(e){var t=e.elements;return this.x=t[12],this.y=t[13],this.z=t[14],this}},{key:"setFromMatrixScale",value:function(e){var t=this.setFromMatrixColumn(e,0).length(),n=this.setFromMatrixColumn(e,1).length(),r=this.setFromMatrixColumn(e,2).length();return this.x=t,this.y=n,this.z=r,this}},{key:"setFromMatrixColumn",value:function(e,t){return this.fromArray(e.elements,4*t)}},{key:"setFromMatrix3Column",value:function(e,t){return this.fromArray(e.elements,3*t)}},{key:"setFromEuler",value:function(e){return this.x=e._x,this.y=e._y,this.z=e._z,this}},{key:"equals",value:function(e){return e.x===this.x&&e.y===this.y&&e.z===this.z}},{key:"fromArray",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this}},{key:"toArray",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e}},{key:"fromBufferAttribute",value:function(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this}},{key:"random",value:function(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}},{key:"randomDirection",value:function(){var e=2*(Math.random()-.5),t=Math.random()*Math.PI*2,n=Math.sqrt(1-Math.pow(e,2));return this.x=n*Math.cos(t),this.y=n*Math.sin(t),this.z=e,this}},{key:Symbol.iterator,value:o().mark((function e(){return o().wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.x;case 2:return e.next=4,this.y;case 4:return e.next=6,this.z;case 6:case"end":return e.stop()}}),e,this)}))}]),t}(),mm=new gm,vm=new pm,ym=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:new gm(1/0,1/0,1/0),n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:new gm(-1/0,-1/0,-1/0);B(this,e),this.isBox3=!0,this.min=t,this.max=n}return b(e,[{key:"set",value:function(e,t){return this.min.copy(e),this.max.copy(t),this}},{key:"setFromArray",value:function(e){for(var t=1/0,n=1/0,r=1/0,i=-1/0,A=-1/0,a=-1/0,o=0,s=e.length;oi&&(i=l),u>A&&(A=u),c>a&&(a=c)}return this.min.set(t,n,r),this.max.set(i,A,a),this}},{key:"setFromBufferAttribute",value:function(e){for(var t=1/0,n=1/0,r=1/0,i=-1/0,A=-1/0,a=-1/0,o=0,s=e.count;oi&&(i=l),u>A&&(A=u),c>a&&(a=c)}return this.min.set(t,n,r),this.max.set(i,A,a),this}},{key:"setFromPoints",value:function(e){this.makeEmpty();for(var t=0,n=e.length;t1&&void 0!==arguments[1]&&arguments[1];return this.makeEmpty(),this.expandByObject(e,t)}},{key:"clone",value:function(){return(new this.constructor).copy(this)}},{key:"copy",value:function(e){return this.min.copy(e.min),this.max.copy(e.max),this}},{key:"makeEmpty",value:function(){return this.min.x=this.min.y=this.min.z=1/0,this.max.x=this.max.y=this.max.z=-1/0,this}},{key:"isEmpty",value:function(){return this.max.x1&&void 0!==arguments[1]&&arguments[1];e.updateWorldMatrix(!1,!1);var n=e.geometry;if(void 0!==n)if(t&&void 0!=n.attributes&&void 0!==n.attributes.position)for(var r=n.attributes.position,i=0,A=r.count;ithis.max.x||e.ythis.max.y||e.zthis.max.z)}},{key:"containsBox",value:function(e){return this.min.x<=e.min.x&&e.max.x<=this.max.x&&this.min.y<=e.min.y&&e.max.y<=this.max.y&&this.min.z<=e.min.z&&e.max.z<=this.max.z}},{key:"getParameter",value:function(e,t){return t.set((e.x-this.min.x)/(this.max.x-this.min.x),(e.y-this.min.y)/(this.max.y-this.min.y),(e.z-this.min.z)/(this.max.z-this.min.z))}},{key:"intersectsBox",value:function(e){return!(e.max.xthis.max.x||e.max.ythis.max.y||e.max.zthis.max.z)}},{key:"intersectsSphere",value:function(e){return this.clampPoint(e.center,Bm),Bm.distanceToSquared(e.center)<=e.radius*e.radius}},{key:"intersectsPlane",value:function(e){var t,n;return e.normal.x>0?(t=e.normal.x*this.min.x,n=e.normal.x*this.max.x):(t=e.normal.x*this.max.x,n=e.normal.x*this.min.x),e.normal.y>0?(t+=e.normal.y*this.min.y,n+=e.normal.y*this.max.y):(t+=e.normal.y*this.max.y,n+=e.normal.y*this.min.y),e.normal.z>0?(t+=e.normal.z*this.min.z,n+=e.normal.z*this.max.z):(t+=e.normal.z*this.max.z,n+=e.normal.z*this.min.z),t<=-e.constant&&n>=-e.constant}},{key:"intersectsTriangle",value:function(e){if(this.isEmpty())return!1;this.getCenter(Mm),Fm.subVectors(this.max,Mm),bm.subVectors(e.a,Mm),xm.subVectors(e.b,Mm),Cm.subVectors(e.c,Mm),Sm.subVectors(xm,bm),Em.subVectors(Cm,xm),Um.subVectors(bm,Cm);var t=[0,-Sm.z,Sm.y,0,-Em.z,Em.y,0,-Um.z,Um.y,Sm.z,0,-Sm.x,Em.z,0,-Em.x,Um.z,0,-Um.x,-Sm.y,Sm.x,0,-Em.y,Em.x,0,-Um.y,Um.x,0];return!!Qm(t,bm,xm,Cm,Fm)&&(!!Qm(t=[1,0,0,0,1,0,0,0,1],bm,xm,Cm,Fm)&&(Tm.crossVectors(Sm,Em),Qm(t=[Tm.x,Tm.y,Tm.z],bm,xm,Cm,Fm)))}},{key:"clampPoint",value:function(e,t){return t.copy(e).clamp(this.min,this.max)}},{key:"distanceToPoint",value:function(e){return Bm.copy(e).clamp(this.min,this.max).sub(e).length()}},{key:"getBoundingSphere",value:function(e){return this.getCenter(e.center),e.radius=.5*this.getSize(Bm).length(),e}},{key:"intersect",value:function(e){return this.min.max(e.min),this.max.min(e.max),this.isEmpty()&&this.makeEmpty(),this}},{key:"union",value:function(e){return this.min.min(e.min),this.max.max(e.max),this}},{key:"applyMatrix4",value:function(e){return this.isEmpty()||(wm[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(e),wm[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(e),wm[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(e),wm[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(e),wm[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(e),wm[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(e),wm[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(e),wm[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(e),this.setFromPoints(wm)),this}},{key:"translate",value:function(e){return this.min.add(e),this.max.add(e),this}},{key:"equals",value:function(e){return e.min.equals(this.min)&&e.max.equals(this.max)}}]),e}(),wm=[new gm,new gm,new gm,new gm,new gm,new gm,new gm,new gm],Bm=new gm,_m=new ym,bm=new gm,xm=new gm,Cm=new gm,Sm=new gm,Em=new gm,Um=new gm,Mm=new gm,Fm=new gm,Tm=new gm,km=new gm;function Qm(e,t,n,r,i){for(var A=0,a=e.length-3;A<=a;A+=3){km.fromArray(e,A);var o=i.x*Math.abs(km.x)+i.y*Math.abs(km.y)+i.z*Math.abs(km.z),s=t.dot(km),l=n.dot(km),u=r.dot(km);if(Math.max(-Math.max(s,l,u),Math.min(s,l,u))>o)return!1}return!0}var Lm=new ym,Dm=new gm,Im=new gm,Rm=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:new gm,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:-1;B(this,e),this.center=t,this.radius=n}return b(e,[{key:"set",value:function(e,t){return this.center.copy(e),this.radius=t,this}},{key:"setFromPoints",value:function(e,t){var n=this.center;void 0!==t?n.copy(t):Lm.setFromPoints(e).getCenter(n);for(var r=0,i=0,A=e.length;ithis.radius*this.radius&&(t.sub(this.center).normalize(),t.multiplyScalar(this.radius).add(this.center)),t}},{key:"getBoundingBox",value:function(e){return this.isEmpty()?(e.makeEmpty(),e):(e.set(this.center,this.center),e.expandByScalar(this.radius),e)}},{key:"applyMatrix4",value:function(e){return this.center.applyMatrix4(e),this.radius=this.radius*e.getMaxScaleOnAxis(),this}},{key:"translate",value:function(e){return this.center.add(e),this}},{key:"expandByPoint",value:function(e){if(this.isEmpty())return this.center.copy(e),this.radius=0,this;Dm.subVectors(e,this.center);var t=Dm.lengthSq();if(t>this.radius*this.radius){var n=Math.sqrt(t),r=.5*(n-this.radius);this.center.addScaledVector(Dm,r/n),this.radius+=r}return this}},{key:"union",value:function(e){return e.isEmpty()?this:this.isEmpty()?(this.copy(e),this):(!0===this.center.equals(e.center)?this.radius=Math.max(this.radius,e.radius):(Im.subVectors(e.center,this.center).setLength(e.radius),this.expandByPoint(Dm.copy(e.center).add(Im)),this.expandByPoint(Dm.copy(e.center).sub(Im))),this)}},{key:"equals",value:function(e){return e.center.equals(this.center)&&e.radius===this.radius}},{key:"clone",value:function(){return(new this.constructor).copy(this)}}]),e}(),Hm=new gm,Pm=new gm,Nm=new gm,Om=new gm,Vm=new gm,zm=new gm,Gm=new gm,Km=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:new gm,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:new gm(0,0,-1);B(this,e),this.origin=t,this.direction=n}return b(e,[{key:"set",value:function(e,t){return this.origin.copy(e),this.direction.copy(t),this}},{key:"copy",value:function(e){return this.origin.copy(e.origin),this.direction.copy(e.direction),this}},{key:"at",value:function(e,t){return t.copy(this.direction).multiplyScalar(e).add(this.origin)}},{key:"lookAt",value:function(e){return this.direction.copy(e).sub(this.origin).normalize(),this}},{key:"recast",value:function(e){return this.origin.copy(this.at(e,Hm)),this}},{key:"closestPointToPoint",value:function(e,t){t.subVectors(e,this.origin);var n=t.dot(this.direction);return n<0?t.copy(this.origin):t.copy(this.direction).multiplyScalar(n).add(this.origin)}},{key:"distanceToPoint",value:function(e){return Math.sqrt(this.distanceSqToPoint(e))}},{key:"distanceSqToPoint",value:function(e){var t=Hm.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(Hm.copy(this.direction).multiplyScalar(t).add(this.origin),Hm.distanceToSquared(e))}},{key:"distanceSqToSegment",value:function(e,t,n,r){Pm.copy(e).add(t).multiplyScalar(.5),Nm.copy(t).sub(e).normalize(),Om.copy(this.origin).sub(Pm);var i,A,a,o,s=.5*e.distanceTo(t),l=-this.direction.dot(Nm),u=Om.dot(this.direction),c=-Om.dot(Nm),d=Om.lengthSq(),h=Math.abs(1-l*l);if(h>0)if(A=l*u-c,o=s*h,(i=l*c-u)>=0)if(A>=-o)if(A<=o){var f=1/h;a=(i*=f)*(i+l*(A*=f)+2*u)+A*(l*i+A+2*c)+d}else A=s,a=-(i=Math.max(0,-(l*A+u)))*i+A*(A+2*c)+d;else A=-s,a=-(i=Math.max(0,-(l*A+u)))*i+A*(A+2*c)+d;else A<=-o?a=-(i=Math.max(0,-(-l*s+u)))*i+(A=i>0?-s:Math.min(Math.max(-s,-c),s))*(A+2*c)+d:A<=o?(i=0,a=(A=Math.min(Math.max(-s,-c),s))*(A+2*c)+d):a=-(i=Math.max(0,-(l*s+u)))*i+(A=i>0?s:Math.min(Math.max(-s,-c),s))*(A+2*c)+d;else A=l>0?-s:s,a=-(i=Math.max(0,-(l*A+u)))*i+A*(A+2*c)+d;return n&&n.copy(this.direction).multiplyScalar(i).add(this.origin),r&&r.copy(Nm).multiplyScalar(A).add(Pm),a}},{key:"intersectSphere",value:function(e,t){Hm.subVectors(e.center,this.origin);var n=Hm.dot(this.direction),r=Hm.dot(Hm)-n*n,i=e.radius*e.radius;if(r>i)return null;var A=Math.sqrt(i-r),a=n-A,o=n+A;return a<0&&o<0?null:a<0?this.at(o,t):this.at(a,t)}},{key:"intersectsSphere",value:function(e){return this.distanceSqToPoint(e.center)<=e.radius*e.radius}},{key:"distanceToPlane",value:function(e){var t=e.normal.dot(this.direction);if(0===t)return 0===e.distanceToPoint(this.origin)?0:null;var n=-(this.origin.dot(e.normal)+e.constant)/t;return n>=0?n:null}},{key:"intersectPlane",value:function(e,t){var n=this.distanceToPlane(e);return null===n?null:this.at(n,t)}},{key:"intersectsPlane",value:function(e){var t=e.distanceToPoint(this.origin);return 0===t||e.normal.dot(this.direction)*t<0}},{key:"intersectBox",value:function(e,t){var n,r,i,A,a,o,s=1/this.direction.x,l=1/this.direction.y,u=1/this.direction.z,c=this.origin;return s>=0?(n=(e.min.x-c.x)*s,r=(e.max.x-c.x)*s):(n=(e.max.x-c.x)*s,r=(e.min.x-c.x)*s),l>=0?(i=(e.min.y-c.y)*l,A=(e.max.y-c.y)*l):(i=(e.max.y-c.y)*l,A=(e.min.y-c.y)*l),n>A||i>r?null:((i>n||isNaN(n))&&(n=i),(A=0?(a=(e.min.z-c.z)*u,o=(e.max.z-c.z)*u):(a=(e.max.z-c.z)*u,o=(e.min.z-c.z)*u),n>o||a>r?null:((a>n||n!==n)&&(n=a),(o=0?n:r,t)))}},{key:"intersectsBox",value:function(e){return null!==this.intersectBox(e,Hm)}},{key:"intersectTriangle",value:function(e,t,n,r,i){Vm.subVectors(t,e),zm.subVectors(n,e),Gm.crossVectors(Vm,zm);var A,a=this.direction.dot(Gm);if(a>0){if(r)return null;A=1}else{if(!(a<0))return null;A=-1,a=-a}Om.subVectors(this.origin,e);var o=A*this.direction.dot(zm.crossVectors(Om,zm));if(o<0)return null;var s=A*this.direction.dot(Vm.cross(Om));if(s<0)return null;if(o+s>a)return null;var l=-A*Om.dot(Gm);return l<0?null:this.at(l/a,i)}},{key:"applyMatrix4",value:function(e){return this.origin.applyMatrix4(e),this.direction.transformDirection(e),this}},{key:"equals",value:function(e){return e.origin.equals(this.origin)&&e.direction.equals(this.direction)}},{key:"clone",value:function(){return(new this.constructor).copy(this)}}]),e}(),Wm=function(){function e(){B(this,e),e.prototype.isMatrix4=!0,this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]}return b(e,[{key:"set",value:function(e,t,n,r,i,A,a,o,s,l,u,c,d,h,f,p){var g=this.elements;return g[0]=e,g[4]=t,g[8]=n,g[12]=r,g[1]=i,g[5]=A,g[9]=a,g[13]=o,g[2]=s,g[6]=l,g[10]=u,g[14]=c,g[3]=d,g[7]=h,g[11]=f,g[15]=p,this}},{key:"identity",value:function(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}},{key:"clone",value:function(){return(new e).fromArray(this.elements)}},{key:"copy",value:function(e){var t=this.elements,n=e.elements;return t[0]=n[0],t[1]=n[1],t[2]=n[2],t[3]=n[3],t[4]=n[4],t[5]=n[5],t[6]=n[6],t[7]=n[7],t[8]=n[8],t[9]=n[9],t[10]=n[10],t[11]=n[11],t[12]=n[12],t[13]=n[13],t[14]=n[14],t[15]=n[15],this}},{key:"copyPosition",value:function(e){var t=this.elements,n=e.elements;return t[12]=n[12],t[13]=n[13],t[14]=n[14],this}},{key:"setFromMatrix3",value:function(e){var t=e.elements;return this.set(t[0],t[3],t[6],0,t[1],t[4],t[7],0,t[2],t[5],t[8],0,0,0,0,1),this}},{key:"extractBasis",value:function(e,t,n){return e.setFromMatrixColumn(this,0),t.setFromMatrixColumn(this,1),n.setFromMatrixColumn(this,2),this}},{key:"makeBasis",value:function(e,t,n){return this.set(e.x,t.x,n.x,0,e.y,t.y,n.y,0,e.z,t.z,n.z,0,0,0,0,1),this}},{key:"extractRotation",value:function(e){var t=this.elements,n=e.elements,r=1/jm.setFromMatrixColumn(e,0).length(),i=1/jm.setFromMatrixColumn(e,1).length(),A=1/jm.setFromMatrixColumn(e,2).length();return t[0]=n[0]*r,t[1]=n[1]*r,t[2]=n[2]*r,t[3]=0,t[4]=n[4]*i,t[5]=n[5]*i,t[6]=n[6]*i,t[7]=0,t[8]=n[8]*A,t[9]=n[9]*A,t[10]=n[10]*A,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}},{key:"makeRotationFromEuler",value:function(e){var t=this.elements,n=e.x,r=e.y,i=e.z,A=Math.cos(n),a=Math.sin(n),o=Math.cos(r),s=Math.sin(r),l=Math.cos(i),u=Math.sin(i);if("XYZ"===e.order){var c=A*l,d=A*u,h=a*l,f=a*u;t[0]=o*l,t[4]=-o*u,t[8]=s,t[1]=d+h*s,t[5]=c-f*s,t[9]=-a*o,t[2]=f-c*s,t[6]=h+d*s,t[10]=A*o}else if("YXZ"===e.order){var p=o*l,g=o*u,m=s*l,v=s*u;t[0]=p+v*a,t[4]=m*a-g,t[8]=A*s,t[1]=A*u,t[5]=A*l,t[9]=-a,t[2]=g*a-m,t[6]=v+p*a,t[10]=A*o}else if("ZXY"===e.order){var y=o*l,w=o*u,B=s*l,_=s*u;t[0]=y-_*a,t[4]=-A*u,t[8]=B+w*a,t[1]=w+B*a,t[5]=A*l,t[9]=_-y*a,t[2]=-A*s,t[6]=a,t[10]=A*o}else if("ZYX"===e.order){var b=A*l,x=A*u,C=a*l,S=a*u;t[0]=o*l,t[4]=C*s-x,t[8]=b*s+S,t[1]=o*u,t[5]=S*s+b,t[9]=x*s-C,t[2]=-s,t[6]=a*o,t[10]=A*o}else if("YZX"===e.order){var E=A*o,U=A*s,M=a*o,F=a*s;t[0]=o*l,t[4]=F-E*u,t[8]=M*u+U,t[1]=u,t[5]=A*l,t[9]=-a*l,t[2]=-s*l,t[6]=U*u+M,t[10]=E-F*u}else if("XZY"===e.order){var T=A*o,k=A*s,Q=a*o,L=a*s;t[0]=o*l,t[4]=-u,t[8]=s*l,t[1]=T*u+L,t[5]=A*l,t[9]=k*u-Q,t[2]=Q*u-k,t[6]=a*l,t[10]=L*u+T}return t[3]=0,t[7]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}},{key:"makeRotationFromQuaternion",value:function(e){return this.compose(qm,e,Ym)}},{key:"lookAt",value:function(e,t,n){var r=this.elements;return $m.subVectors(e,t),0===$m.lengthSq()&&($m.z=1),$m.normalize(),Jm.crossVectors(n,$m),0===Jm.lengthSq()&&(1===Math.abs(n.z)?$m.x+=1e-4:$m.z+=1e-4,$m.normalize(),Jm.crossVectors(n,$m)),Jm.normalize(),Zm.crossVectors($m,Jm),r[0]=Jm.x,r[4]=Zm.x,r[8]=$m.x,r[1]=Jm.y,r[5]=Zm.y,r[9]=$m.y,r[2]=Jm.z,r[6]=Zm.z,r[10]=$m.z,this}},{key:"multiply",value:function(e){return this.multiplyMatrices(this,e)}},{key:"premultiply",value:function(e){return this.multiplyMatrices(e,this)}},{key:"multiplyMatrices",value:function(e,t){var n=e.elements,r=t.elements,i=this.elements,A=n[0],a=n[4],o=n[8],s=n[12],l=n[1],u=n[5],c=n[9],d=n[13],h=n[2],f=n[6],p=n[10],g=n[14],m=n[3],v=n[7],y=n[11],w=n[15],B=r[0],_=r[4],b=r[8],x=r[12],C=r[1],S=r[5],E=r[9],U=r[13],M=r[2],F=r[6],T=r[10],k=r[14],Q=r[3],L=r[7],D=r[11],I=r[15];return i[0]=A*B+a*C+o*M+s*Q,i[4]=A*_+a*S+o*F+s*L,i[8]=A*b+a*E+o*T+s*D,i[12]=A*x+a*U+o*k+s*I,i[1]=l*B+u*C+c*M+d*Q,i[5]=l*_+u*S+c*F+d*L,i[9]=l*b+u*E+c*T+d*D,i[13]=l*x+u*U+c*k+d*I,i[2]=h*B+f*C+p*M+g*Q,i[6]=h*_+f*S+p*F+g*L,i[10]=h*b+f*E+p*T+g*D,i[14]=h*x+f*U+p*k+g*I,i[3]=m*B+v*C+y*M+w*Q,i[7]=m*_+v*S+y*F+w*L,i[11]=m*b+v*E+y*T+w*D,i[15]=m*x+v*U+y*k+w*I,this}},{key:"multiplyScalar",value:function(e){var t=this.elements;return t[0]*=e,t[4]*=e,t[8]*=e,t[12]*=e,t[1]*=e,t[5]*=e,t[9]*=e,t[13]*=e,t[2]*=e,t[6]*=e,t[10]*=e,t[14]*=e,t[3]*=e,t[7]*=e,t[11]*=e,t[15]*=e,this}},{key:"determinant",value:function(){var e=this.elements,t=e[0],n=e[4],r=e[8],i=e[12],A=e[1],a=e[5],o=e[9],s=e[13],l=e[2],u=e[6],c=e[10],d=e[14];return e[3]*(+i*o*u-r*s*u-i*a*c+n*s*c+r*a*d-n*o*d)+e[7]*(+t*o*d-t*s*c+i*A*c-r*A*d+r*s*l-i*o*l)+e[11]*(+t*s*u-t*a*d-i*A*u+n*A*d+i*a*l-n*s*l)+e[15]*(-r*a*l-t*o*u+t*a*c+r*A*u-n*A*c+n*o*l)}},{key:"transpose",value:function(){var e,t=this.elements;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}},{key:"setPosition",value:function(e,t,n){var r=this.elements;return e.isVector3?(r[12]=e.x,r[13]=e.y,r[14]=e.z):(r[12]=e,r[13]=t,r[14]=n),this}},{key:"invert",value:function(){var e=this.elements,t=e[0],n=e[1],r=e[2],i=e[3],A=e[4],a=e[5],o=e[6],s=e[7],l=e[8],u=e[9],c=e[10],d=e[11],h=e[12],f=e[13],p=e[14],g=e[15],m=u*p*s-f*c*s+f*o*d-a*p*d-u*o*g+a*c*g,v=h*c*s-l*p*s-h*o*d+A*p*d+l*o*g-A*c*g,y=l*f*s-h*u*s+h*a*d-A*f*d-l*a*g+A*u*g,w=h*u*o-l*f*o-h*a*c+A*f*c+l*a*p-A*u*p,B=t*m+n*v+r*y+i*w;if(0===B)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);var _=1/B;return e[0]=m*_,e[1]=(f*c*i-u*p*i-f*r*d+n*p*d+u*r*g-n*c*g)*_,e[2]=(a*p*i-f*o*i+f*r*s-n*p*s-a*r*g+n*o*g)*_,e[3]=(u*o*i-a*c*i-u*r*s+n*c*s+a*r*d-n*o*d)*_,e[4]=v*_,e[5]=(l*p*i-h*c*i+h*r*d-t*p*d-l*r*g+t*c*g)*_,e[6]=(h*o*i-A*p*i-h*r*s+t*p*s+A*r*g-t*o*g)*_,e[7]=(A*c*i-l*o*i+l*r*s-t*c*s-A*r*d+t*o*d)*_,e[8]=y*_,e[9]=(h*u*i-l*f*i-h*n*d+t*f*d+l*n*g-t*u*g)*_,e[10]=(A*f*i-h*a*i+h*n*s-t*f*s-A*n*g+t*a*g)*_,e[11]=(l*a*i-A*u*i-l*n*s+t*u*s+A*n*d-t*a*d)*_,e[12]=w*_,e[13]=(l*f*r-h*u*r+h*n*c-t*f*c-l*n*p+t*u*p)*_,e[14]=(h*a*r-A*f*r-h*n*o+t*f*o+A*n*p-t*a*p)*_,e[15]=(A*u*r-l*a*r+l*n*o-t*u*o-A*n*c+t*a*c)*_,this}},{key:"scale",value:function(e){var t=this.elements,n=e.x,r=e.y,i=e.z;return t[0]*=n,t[4]*=r,t[8]*=i,t[1]*=n,t[5]*=r,t[9]*=i,t[2]*=n,t[6]*=r,t[10]*=i,t[3]*=n,t[7]*=r,t[11]*=i,this}},{key:"getMaxScaleOnAxis",value:function(){var e=this.elements,t=e[0]*e[0]+e[1]*e[1]+e[2]*e[2],n=e[4]*e[4]+e[5]*e[5]+e[6]*e[6],r=e[8]*e[8]+e[9]*e[9]+e[10]*e[10];return Math.sqrt(Math.max(t,n,r))}},{key:"makeTranslation",value:function(e,t,n){return this.set(1,0,0,e,0,1,0,t,0,0,1,n,0,0,0,1),this}},{key:"makeRotationX",value:function(e){var t=Math.cos(e),n=Math.sin(e);return this.set(1,0,0,0,0,t,-n,0,0,n,t,0,0,0,0,1),this}},{key:"makeRotationY",value:function(e){var t=Math.cos(e),n=Math.sin(e);return this.set(t,0,n,0,0,1,0,0,-n,0,t,0,0,0,0,1),this}},{key:"makeRotationZ",value:function(e){var t=Math.cos(e),n=Math.sin(e);return this.set(t,-n,0,0,n,t,0,0,0,0,1,0,0,0,0,1),this}},{key:"makeRotationAxis",value:function(e,t){var n=Math.cos(t),r=Math.sin(t),i=1-n,A=e.x,a=e.y,o=e.z,s=i*A,l=i*a;return this.set(s*A+n,s*a-r*o,s*o+r*a,0,s*a+r*o,l*a+n,l*o-r*A,0,s*o-r*a,l*o+r*A,i*o*o+n,0,0,0,0,1),this}},{key:"makeScale",value:function(e,t,n){return this.set(e,0,0,0,0,t,0,0,0,0,n,0,0,0,0,1),this}},{key:"makeShear",value:function(e,t,n,r,i,A){return this.set(1,n,i,0,e,1,A,0,t,r,1,0,0,0,0,1),this}},{key:"compose",value:function(e,t,n){var r=this.elements,i=t._x,A=t._y,a=t._z,o=t._w,s=i+i,l=A+A,u=a+a,c=i*s,d=i*l,h=i*u,f=A*l,p=A*u,g=a*u,m=o*s,v=o*l,y=o*u,w=n.x,B=n.y,_=n.z;return r[0]=(1-(f+g))*w,r[1]=(d+y)*w,r[2]=(h-v)*w,r[3]=0,r[4]=(d-y)*B,r[5]=(1-(c+g))*B,r[6]=(p+m)*B,r[7]=0,r[8]=(h+v)*_,r[9]=(p-m)*_,r[10]=(1-(c+f))*_,r[11]=0,r[12]=e.x,r[13]=e.y,r[14]=e.z,r[15]=1,this}},{key:"decompose",value:function(e,t,n){var r=this.elements,i=jm.set(r[0],r[1],r[2]).length(),A=jm.set(r[4],r[5],r[6]).length(),a=jm.set(r[8],r[9],r[10]).length();this.determinant()<0&&(i=-i),e.x=r[12],e.y=r[13],e.z=r[14],Xm.copy(this);var o=1/i,s=1/A,l=1/a;return Xm.elements[0]*=o,Xm.elements[1]*=o,Xm.elements[2]*=o,Xm.elements[4]*=s,Xm.elements[5]*=s,Xm.elements[6]*=s,Xm.elements[8]*=l,Xm.elements[9]*=l,Xm.elements[10]*=l,t.setFromRotationMatrix(Xm),n.x=i,n.y=A,n.z=a,this}},{key:"makePerspective",value:function(e,t,n,r,i,A){var a=this.elements,o=2*i/(t-e),s=2*i/(n-r),l=(t+e)/(t-e),u=(n+r)/(n-r),c=-(A+i)/(A-i),d=-2*A*i/(A-i);return a[0]=o,a[4]=0,a[8]=l,a[12]=0,a[1]=0,a[5]=s,a[9]=u,a[13]=0,a[2]=0,a[6]=0,a[10]=c,a[14]=d,a[3]=0,a[7]=0,a[11]=-1,a[15]=0,this}},{key:"makeOrthographic",value:function(e,t,n,r,i,A){var a=this.elements,o=1/(t-e),s=1/(n-r),l=1/(A-i),u=(t+e)*o,c=(n+r)*s,d=(A+i)*l;return a[0]=2*o,a[4]=0,a[8]=0,a[12]=-u,a[1]=0,a[5]=2*s,a[9]=0,a[13]=-c,a[2]=0,a[6]=0,a[10]=-2*l,a[14]=-d,a[3]=0,a[7]=0,a[11]=0,a[15]=1,this}},{key:"equals",value:function(e){for(var t=this.elements,n=e.elements,r=0;r<16;r++)if(t[r]!==n[r])return!1;return!0}},{key:"fromArray",value:function(e){for(var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,n=0;n<16;n++)this.elements[n]=e[n+t];return this}},{key:"toArray",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,n=this.elements;return e[t]=n[0],e[t+1]=n[1],e[t+2]=n[2],e[t+3]=n[3],e[t+4]=n[4],e[t+5]=n[5],e[t+6]=n[6],e[t+7]=n[7],e[t+8]=n[8],e[t+9]=n[9],e[t+10]=n[10],e[t+11]=n[11],e[t+12]=n[12],e[t+13]=n[13],e[t+14]=n[14],e[t+15]=n[15],e}}]),e}(),jm=new gm,Xm=new Wm,qm=new gm(0,0,0),Ym=new gm(1,1,1),Jm=new gm,Zm=new gm,$m=new gm,ev=new Wm,tv=new pm,nv=function(e){function t(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:0,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0,i=arguments.length>3&&void 0!==arguments[3]?arguments[3]:t.DEFAULT_ORDER;B(this,t),this.isEuler=!0,this._x=e,this._y=n,this._z=r,this._order=i}return b(t,[{key:"x",get:function(){return this._x},set:function(e){this._x=e,this._onChangeCallback()}},{key:"y",get:function(){return this._y},set:function(e){this._y=e,this._onChangeCallback()}},{key:"z",get:function(){return this._z},set:function(e){this._z=e,this._onChangeCallback()}},{key:"order",get:function(){return this._order},set:function(e){this._order=e,this._onChangeCallback()}},{key:"set",value:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:this._order;return this._x=e,this._y=t,this._z=n,this._order=r,this._onChangeCallback(),this}},{key:"clone",value:function(){return new this.constructor(this._x,this._y,this._z,this._order)}},{key:"copy",value:function(e){return this._x=e._x,this._y=e._y,this._z=e._z,this._order=e._order,this._onChangeCallback(),this}},{key:"setFromRotationMatrix",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:this._order,n=!(arguments.length>2&&void 0!==arguments[2])||arguments[2],r=e.elements,i=r[0],A=r[4],a=r[8],o=r[1],s=r[5],l=r[9],u=r[2],c=r[6],d=r[10];switch(t){case"XYZ":this._y=Math.asin(Lg(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-l,d),this._z=Math.atan2(-A,i)):(this._x=Math.atan2(c,s),this._z=0);break;case"YXZ":this._x=Math.asin(-Lg(l,-1,1)),Math.abs(l)<.9999999?(this._y=Math.atan2(a,d),this._z=Math.atan2(o,s)):(this._y=Math.atan2(-u,i),this._z=0);break;case"ZXY":this._x=Math.asin(Lg(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(-u,d),this._z=Math.atan2(-A,s)):(this._y=0,this._z=Math.atan2(o,i));break;case"ZYX":this._y=Math.asin(-Lg(u,-1,1)),Math.abs(u)<.9999999?(this._x=Math.atan2(c,d),this._z=Math.atan2(o,i)):(this._x=0,this._z=Math.atan2(-A,s));break;case"YZX":this._z=Math.asin(Lg(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-l,s),this._y=Math.atan2(-u,i)):(this._x=0,this._y=Math.atan2(a,d));break;case"XZY":this._z=Math.asin(-Lg(A,-1,1)),Math.abs(A)<.9999999?(this._x=Math.atan2(c,s),this._y=Math.atan2(a,i)):(this._x=Math.atan2(-l,d),this._y=0);break;default:console.warn("THREE.Euler: .setFromRotationMatrix() encountered an unknown order: "+t)}return this._order=t,!0===n&&this._onChangeCallback(),this}},{key:"setFromQuaternion",value:function(e,t,n){return ev.makeRotationFromQuaternion(e),this.setFromRotationMatrix(ev,t,n)}},{key:"setFromVector3",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:this._order;return this.set(e.x,e.y,e.z,t)}},{key:"reorder",value:function(e){return tv.setFromEuler(this),this.setFromQuaternion(tv,e)}},{key:"equals",value:function(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._order===this._order}},{key:"fromArray",value:function(e){return this._x=e[0],this._y=e[1],this._z=e[2],void 0!==e[3]&&(this._order=e[3]),this._onChangeCallback(),this}},{key:"toArray",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._order,e}},{key:"_onChange",value:function(e){return this._onChangeCallback=e,this}},{key:"_onChangeCallback",value:function(){}},{key:Symbol.iterator,value:o().mark((function e(){return o().wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this._x;case 2:return e.next=4,this._y;case 4:return e.next=6,this._z;case 6:return e.next=8,this._order;case 8:case"end":return e.stop()}}),e,this)}))}]),t}();nv.DEFAULT_ORDER="XYZ";var rv=function(){function e(){B(this,e),this.mask=1}return b(e,[{key:"set",value:function(e){this.mask=(1<>>0}},{key:"enable",value:function(e){this.mask|=1<1){for(var t=0;t1){for(var t=0;t0&&(n=n.concat(A))}return n}},{key:"getWorldPosition",value:function(e){return this.updateWorldMatrix(!0,!1),e.setFromMatrixPosition(this.matrixWorld)}},{key:"getWorldQuaternion",value:function(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(lv,e,uv),e}},{key:"getWorldScale",value:function(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(lv,cv,e),e}},{key:"getWorldDirection",value:function(e){this.updateWorldMatrix(!0,!1);var t=this.matrixWorld.elements;return e.set(t[8],t[9],t[10]).normalize()}},{key:"raycast",value:function(){}},{key:"traverse",value:function(e){e(this);for(var t=this.children,n=0,r=t.length;n0&&(r.userData=this.userData),r.layers=this.layers.mask,r.matrix=this.matrix.toArray(),!1===this.matrixAutoUpdate&&(r.matrixAutoUpdate=!1),this.isInstancedMesh&&(r.type="InstancedMesh",r.count=this.count,r.instanceMatrix=this.instanceMatrix.toJSON(),null!==this.instanceColor&&(r.instanceColor=this.instanceColor.toJSON())),this.isScene)this.background&&(this.background.isColor?r.background=this.background.toJSON():this.background.isTexture&&(r.background=this.background.toJSON(e).uuid)),this.environment&&this.environment.isTexture&&!0!==this.environment.isRenderTargetTexture&&(r.environment=this.environment.toJSON(e).uuid);else if(this.isMesh||this.isLine||this.isPoints){r.geometry=i(e.geometries,this.geometry);var A=this.geometry.parameters;if(void 0!==A&&void 0!==A.shapes){var a=A.shapes;if(Array.isArray(a))for(var o=0,s=a.length;o0){r.children=[];for(var h=0;h0){r.animations=[];for(var f=0;f0&&(n.geometries=g),m.length>0&&(n.materials=m),v.length>0&&(n.textures=v),y.length>0&&(n.images=y),w.length>0&&(n.shapes=w),B.length>0&&(n.skeletons=B),_.length>0&&(n.animations=_),b.length>0&&(n.nodes=b)}return n.object=r,n;function x(e){var t=[];for(var n in e){var r=e[n];delete r.metadata,t.push(r)}return t}}},{key:"clone",value:function(e){return(new this.constructor).copy(this,e)}},{key:"copy",value:function(e){var t=!(arguments.length>1&&void 0!==arguments[1])||arguments[1];if(this.name=e.name,this.up.copy(e.up),this.position.copy(e.position),this.rotation.order=e.rotation.order,this.quaternion.copy(e.quaternion),this.scale.copy(e.scale),this.matrix.copy(e.matrix),this.matrixWorld.copy(e.matrixWorld),this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrixWorldNeedsUpdate=e.matrixWorldNeedsUpdate,this.matrixWorldAutoUpdate=e.matrixWorldAutoUpdate,this.layers.mask=e.layers.mask,this.visible=e.visible,this.castShadow=e.castShadow,this.receiveShadow=e.receiveShadow,this.frustumCulled=e.frustumCulled,this.renderOrder=e.renderOrder,this.userData=JSON.parse(JSON.stringify(e.userData)),!0===t)for(var n=0;n0&&void 0!==arguments[0]?arguments[0]:new gm,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:new gm,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:new gm;B(this,e),this.a=t,this.b=n,this.c=r}return b(e,[{key:"set",value:function(e,t,n){return this.a.copy(e),this.b.copy(t),this.c.copy(n),this}},{key:"setFromPointsAndIndices",value:function(e,t,n,r){return this.a.copy(e[t]),this.b.copy(e[n]),this.c.copy(e[r]),this}},{key:"setFromAttributeAndIndices",value:function(e,t,n,r){return this.a.fromBufferAttribute(e,t),this.b.fromBufferAttribute(e,n),this.c.fromBufferAttribute(e,r),this}},{key:"clone",value:function(){return(new this.constructor).copy(this)}},{key:"copy",value:function(e){return this.a.copy(e.a),this.b.copy(e.b),this.c.copy(e.c),this}},{key:"getArea",value:function(){return vv.subVectors(this.c,this.b),yv.subVectors(this.a,this.b),.5*vv.cross(yv).length()}},{key:"getMidpoint",value:function(e){return e.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}},{key:"getNormal",value:function(t){return e.getNormal(this.a,this.b,this.c,t)}},{key:"getPlane",value:function(e){return e.setFromCoplanarPoints(this.a,this.b,this.c)}},{key:"getBarycoord",value:function(t,n){return e.getBarycoord(t,this.a,this.b,this.c,n)}},{key:"getUV",value:function(t,n,r,i,A){return e.getUV(t,this.a,this.b,this.c,n,r,i,A)}},{key:"containsPoint",value:function(t){return e.containsPoint(t,this.a,this.b,this.c)}},{key:"isFrontFacing",value:function(t){return e.isFrontFacing(this.a,this.b,this.c,t)}},{key:"intersectsBox",value:function(e){return e.intersectsTriangle(this)}},{key:"closestPointToPoint",value:function(e,t){var n,r,i=this.a,A=this.b,a=this.c;_v.subVectors(A,i),bv.subVectors(a,i),Cv.subVectors(e,i);var o=_v.dot(Cv),s=bv.dot(Cv);if(o<=0&&s<=0)return t.copy(i);Sv.subVectors(e,A);var l=_v.dot(Sv),u=bv.dot(Sv);if(l>=0&&u<=l)return t.copy(A);var c=o*u-l*s;if(c<=0&&o>=0&&l<=0)return n=o/(o-l),t.copy(i).addScaledVector(_v,n);Ev.subVectors(e,a);var d=_v.dot(Ev),h=bv.dot(Ev);if(h>=0&&d<=h)return t.copy(a);var f=d*s-o*h;if(f<=0&&s>=0&&h<=0)return r=s/(s-h),t.copy(i).addScaledVector(bv,r);var p=l*h-d*u;if(p<=0&&u-l>=0&&d-h>=0)return xv.subVectors(a,A),r=(u-l)/(u-l+(d-h)),t.copy(A).addScaledVector(xv,r);var g=1/(p+f+c);return n=f*g,r=c*g,t.copy(i).addScaledVector(_v,n).addScaledVector(bv,r)}},{key:"equals",value:function(e){return e.a.equals(this.a)&&e.b.equals(this.b)&&e.c.equals(this.c)}}],[{key:"getNormal",value:function(e,t,n,r){r.subVectors(n,t),vv.subVectors(e,t),r.cross(vv);var i=r.lengthSq();return i>0?r.multiplyScalar(1/Math.sqrt(i)):r.set(0,0,0)}},{key:"getBarycoord",value:function(e,t,n,r,i){vv.subVectors(r,t),yv.subVectors(n,t),wv.subVectors(e,t);var A=vv.dot(vv),a=vv.dot(yv),o=vv.dot(wv),s=yv.dot(yv),l=yv.dot(wv),u=A*s-a*a;if(0===u)return i.set(-2,-1,-1);var c=1/u,d=(s*o-a*l)*c,h=(A*l-a*o)*c;return i.set(1-d-h,h,d)}},{key:"containsPoint",value:function(e,t,n,r){return this.getBarycoord(e,t,n,r,Bv),Bv.x>=0&&Bv.y>=0&&Bv.x+Bv.y<=1}},{key:"getUV",value:function(e,t,n,r,i,A,a,o){return this.getBarycoord(e,t,n,r,Bv),o.set(0,0),o.addScaledVector(i,Bv.x),o.addScaledVector(A,Bv.y),o.addScaledVector(a,Bv.z),o}},{key:"isFrontFacing",value:function(e,t,n,r){return vv.subVectors(n,t),yv.subVectors(e,t),vv.cross(yv).dot(r)<0}}]),e}(),Mv=0,Fv=function(e){C(n,e);var t=M(n);function n(){var e;return B(this,n),(e=t.call(this)).isMaterial=!0,Object.defineProperty(U(e),"id",{value:Mv++}),e.uuid=Qg(),e.name="",e.type="Material",e.blending=df,e.side=sf,e.vertexColors=!1,e.opacity=1,e.transparent=!1,e.blendSrc=Sf,e.blendDst=Ef,e.blendEquation=mf,e.blendSrcAlpha=null,e.blendDstAlpha=null,e.blendEquationAlpha=null,e.depthFunc=If,e.depthTest=!0,e.depthWrite=!0,e.stencilWriteMask=255,e.stencilFunc=xg,e.stencilRef=0,e.stencilFuncMask=255,e.stencilFail=bg,e.stencilZFail=bg,e.stencilZPass=bg,e.stencilWrite=!1,e.clippingPlanes=null,e.clipIntersection=!1,e.clipShadows=!1,e.shadowSide=null,e.colorWrite=!0,e.precision=null,e.polygonOffset=!1,e.polygonOffsetFactor=0,e.polygonOffsetUnits=0,e.dithering=!1,e.alphaToCoverage=!1,e.premultipliedAlpha=!1,e.forceSinglePass=!1,e.visible=!0,e.toneMapped=!0,e.userData={},e.version=0,e._alphaTest=0,e}return b(n,[{key:"alphaTest",get:function(){return this._alphaTest},set:function(e){this._alphaTest>0!==e>0&&this.version++,this._alphaTest=e}},{key:"onBuild",value:function(){}},{key:"onBeforeRender",value:function(){}},{key:"onBeforeCompile",value:function(){}},{key:"customProgramCacheKey",value:function(){return this.onBeforeCompile.toString()}},{key:"setValues",value:function(e){if(void 0!==e)for(var t in e){var n=e[t];if(void 0!==n){var r=this[t];void 0!==r?r&&r.isColor?r.set(n):r&&r.isVector3&&n&&n.isVector3?r.copy(n):this[t]=n:console.warn("THREE."+this.type+": '"+t+"' is not a property of this material.")}else console.warn("THREE.Material: '"+t+"' parameter is undefined.")}}},{key:"toJSON",value:function(e){var t=void 0===e||"string"===typeof e;t&&(e={textures:{},images:{}});var n={metadata:{version:4.5,type:"Material",generator:"Material.toJSON"}};function r(e){var t=[];for(var n in e){var r=e[n];delete r.metadata,t.push(r)}return t}if(n.uuid=this.uuid,n.type=this.type,""!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenColor&&this.sheenColor.isColor&&(n.sheenColor=this.sheenColor.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(n.specularColor=this.specularColor.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(e).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(e).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(e).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),void 0!==this.iridescence&&(n.iridescence=this.iridescence),void 0!==this.iridescenceIOR&&(n.iridescenceIOR=this.iridescenceIOR),void 0!==this.iridescenceThicknessRange&&(n.iridescenceThicknessRange=this.iridescenceThicknessRange),this.iridescenceMap&&this.iridescenceMap.isTexture&&(n.iridescenceMap=this.iridescenceMap.toJSON(e).uuid),this.iridescenceThicknessMap&&this.iridescenceThicknessMap.isTexture&&(n.iridescenceThicknessMap=this.iridescenceThicknessMap.toJSON(e).uuid),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(e).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(e).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(e).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(e).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(e).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(e).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(e).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(e).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(e).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(e).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(e).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(e).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(e).uuid),this.specularColorMap&&this.specularColorMap.isTexture&&(n.specularColorMap=this.specularColorMap.toJSON(e).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(e).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(e).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(e).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(e).uuid),void 0!==this.attenuationDistance&&this.attenuationDistance!==1/0&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationColor&&(n.attenuationColor=this.attenuationColor.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),this.blending!==df&&(n.blending=this.blending),this.side!==sf&&(n.side=this.side),this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),!0===this.transparent&&(n.transparent=this.transparent),n.depthFunc=this.depthFunc,n.depthTest=this.depthTest,n.depthWrite=this.depthWrite,n.colorWrite=this.colorWrite,n.stencilWrite=this.stencilWrite,n.stencilWriteMask=this.stencilWriteMask,n.stencilFunc=this.stencilFunc,n.stencilRef=this.stencilRef,n.stencilFuncMask=this.stencilFuncMask,n.stencilFail=this.stencilFail,n.stencilZFail=this.stencilZFail,n.stencilZPass=this.stencilZPass,void 0!==this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),void 0!==this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(n.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=this.premultipliedAlpha),!0===this.forceSinglePass&&(n.forceSinglePass=this.forceSinglePass),!0===this.wireframe&&(n.wireframe=this.wireframe),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),"round"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),"round"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=this.flatShading),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),!1===this.fog&&(n.fog=!1),Object.keys(this.userData).length>0&&(n.userData=this.userData),t){var i=r(e.textures),A=r(e.images);i.length>0&&(n.textures=i),A.length>0&&(n.images=A)}return n}},{key:"clone",value:function(){return(new this.constructor).copy(this)}},{key:"copy",value:function(e){this.name=e.name,this.blending=e.blending,this.side=e.side,this.vertexColors=e.vertexColors,this.opacity=e.opacity,this.transparent=e.transparent,this.blendSrc=e.blendSrc,this.blendDst=e.blendDst,this.blendEquation=e.blendEquation,this.blendSrcAlpha=e.blendSrcAlpha,this.blendDstAlpha=e.blendDstAlpha,this.blendEquationAlpha=e.blendEquationAlpha,this.depthFunc=e.depthFunc,this.depthTest=e.depthTest,this.depthWrite=e.depthWrite,this.stencilWriteMask=e.stencilWriteMask,this.stencilFunc=e.stencilFunc,this.stencilRef=e.stencilRef,this.stencilFuncMask=e.stencilFuncMask,this.stencilFail=e.stencilFail,this.stencilZFail=e.stencilZFail,this.stencilZPass=e.stencilZPass,this.stencilWrite=e.stencilWrite;var t=e.clippingPlanes,n=null;if(null!==t){var r=t.length;n=new Array(r);for(var i=0;i!==r;++i)n[i]=t[i].clone()}return this.clippingPlanes=n,this.clipIntersection=e.clipIntersection,this.clipShadows=e.clipShadows,this.shadowSide=e.shadowSide,this.colorWrite=e.colorWrite,this.precision=e.precision,this.polygonOffset=e.polygonOffset,this.polygonOffsetFactor=e.polygonOffsetFactor,this.polygonOffsetUnits=e.polygonOffsetUnits,this.dithering=e.dithering,this.alphaTest=e.alphaTest,this.alphaToCoverage=e.alphaToCoverage,this.premultipliedAlpha=e.premultipliedAlpha,this.forceSinglePass=e.forceSinglePass,this.visible=e.visible,this.toneMapped=e.toneMapped,this.userData=JSON.parse(JSON.stringify(e.userData)),this}},{key:"dispose",value:function(){this.dispatchEvent({type:"dispose"})}},{key:"needsUpdate",set:function(e){!0===e&&this.version++}}]),n}(Ug),Tv=function(e){C(n,e);var t=M(n);function n(e){var r;return B(this,n),(r=t.call(this)).isMeshBasicMaterial=!0,r.type="MeshBasicMaterial",r.color=new Am(16777215),r.map=null,r.lightMap=null,r.lightMapIntensity=1,r.aoMap=null,r.aoMapIntensity=1,r.specularMap=null,r.alphaMap=null,r.envMap=null,r.combine=Of,r.reflectivity=1,r.refractionRatio=.98,r.wireframe=!1,r.wireframeLinewidth=1,r.wireframeLinecap="round",r.wireframeLinejoin="round",r.fog=!0,r.setValues(e),r}return b(n,[{key:"copy",value:function(e){return jc(S(n.prototype),"copy",this).call(this,e),this.color.copy(e.color),this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}}]),n}(Fv),kv=new gm,Qv=new zg,Lv=function(){function e(t,n){var r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if(B(this,e),Array.isArray(t))throw new TypeError("THREE.BufferAttribute: array should be a Typed Array.");this.isBufferAttribute=!0,this.name="",this.array=t,this.itemSize=n,this.count=void 0!==t?t.length/n:0,this.normalized=r,this.usage=Cg,this.updateRange={offset:0,count:-1},this.version=0}return b(e,[{key:"onUploadCallback",value:function(){}},{key:"needsUpdate",set:function(e){!0===e&&this.version++}},{key:"setUsage",value:function(e){return this.usage=e,this}},{key:"copy",value:function(e){return this.name=e.name,this.array=new e.array.constructor(e.array),this.itemSize=e.itemSize,this.count=e.count,this.normalized=e.normalized,this.usage=e.usage,this}},{key:"copyAt",value:function(e,t,n){e*=this.itemSize,n*=t.itemSize;for(var r=0,i=this.itemSize;r1&&void 0!==arguments[1]?arguments[1]:0;return this.array.set(e,t),this}},{key:"getX",value:function(e){var t=this.array[e*this.itemSize];return this.normalized&&(t=Ng(t,this.array)),t}},{key:"setX",value:function(e,t){return this.normalized&&(t=Og(t,this.array)),this.array[e*this.itemSize]=t,this}},{key:"getY",value:function(e){var t=this.array[e*this.itemSize+1];return this.normalized&&(t=Ng(t,this.array)),t}},{key:"setY",value:function(e,t){return this.normalized&&(t=Og(t,this.array)),this.array[e*this.itemSize+1]=t,this}},{key:"getZ",value:function(e){var t=this.array[e*this.itemSize+2];return this.normalized&&(t=Ng(t,this.array)),t}},{key:"setZ",value:function(e,t){return this.normalized&&(t=Og(t,this.array)),this.array[e*this.itemSize+2]=t,this}},{key:"getW",value:function(e){var t=this.array[e*this.itemSize+3];return this.normalized&&(t=Ng(t,this.array)),t}},{key:"setW",value:function(e,t){return this.normalized&&(t=Og(t,this.array)),this.array[e*this.itemSize+3]=t,this}},{key:"setXY",value:function(e,t,n){return e*=this.itemSize,this.normalized&&(t=Og(t,this.array),n=Og(n,this.array)),this.array[e+0]=t,this.array[e+1]=n,this}},{key:"setXYZ",value:function(e,t,n,r){return e*=this.itemSize,this.normalized&&(t=Og(t,this.array),n=Og(n,this.array),r=Og(r,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=r,this}},{key:"setXYZW",value:function(e,t,n,r,i){return e*=this.itemSize,this.normalized&&(t=Og(t,this.array),n=Og(n,this.array),r=Og(r,this.array),i=Og(i,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=r,this.array[e+3]=i,this}},{key:"onUpload",value:function(e){return this.onUploadCallback=e,this}},{key:"clone",value:function(){return new this.constructor(this.array,this.itemSize).copy(this)}},{key:"toJSON",value:function(){var e={itemSize:this.itemSize,type:this.array.constructor.name,array:Array.from(this.array),normalized:this.normalized};return""!==this.name&&(e.name=this.name),this.usage!==Cg&&(e.usage=this.usage),0===this.updateRange.offset&&-1===this.updateRange.count||(e.updateRange=this.updateRange),e}},{key:"copyColorsArray",value:function(){console.error("THREE.BufferAttribute: copyColorsArray() was removed in r144.")}},{key:"copyVector2sArray",value:function(){console.error("THREE.BufferAttribute: copyVector2sArray() was removed in r144.")}},{key:"copyVector3sArray",value:function(){console.error("THREE.BufferAttribute: copyVector3sArray() was removed in r144.")}},{key:"copyVector4sArray",value:function(){console.error("THREE.BufferAttribute: copyVector4sArray() was removed in r144.")}}]),e}(),Dv=function(e){C(n,e);var t=M(n);function n(e,r,i){return B(this,n),t.call(this,new Uint16Array(e),r,i)}return b(n)}(Lv),Iv=function(e){C(n,e);var t=M(n);function n(e,r,i){return B(this,n),t.call(this,new Uint32Array(e),r,i)}return b(n)}(Lv),Rv=function(e){C(n,e);var t=M(n);function n(e,r,i){return B(this,n),t.call(this,new Float32Array(e),r,i)}return b(n)}(Lv),Hv=0,Pv=new Wm,Nv=new mv,Ov=new gm,Vv=new ym,zv=new ym,Gv=new gm,Kv=function(e){C(n,e);var t=M(n);function n(){var e;return B(this,n),(e=t.call(this)).isBufferGeometry=!0,Object.defineProperty(U(e),"id",{value:Hv++}),e.uuid=Qg(),e.name="",e.type="BufferGeometry",e.index=null,e.attributes={},e.morphAttributes={},e.morphTargetsRelative=!1,e.groups=[],e.boundingBox=null,e.boundingSphere=null,e.drawRange={start:0,count:1/0},e.userData={},e}return b(n,[{key:"getIndex",value:function(){return this.index}},{key:"setIndex",value:function(e){return Array.isArray(e)?this.index=new(Wg(e)?Iv:Dv)(e,1):this.index=e,this}},{key:"getAttribute",value:function(e){return this.attributes[e]}},{key:"setAttribute",value:function(e,t){return this.attributes[e]=t,this}},{key:"deleteAttribute",value:function(e){return delete this.attributes[e],this}},{key:"hasAttribute",value:function(e){return void 0!==this.attributes[e]}},{key:"addGroup",value:function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0;this.groups.push({start:e,count:t,materialIndex:n})}},{key:"clearGroups",value:function(){this.groups=[]}},{key:"setDrawRange",value:function(e,t){this.drawRange.start=e,this.drawRange.count=t}},{key:"applyMatrix4",value:function(e){var t=this.attributes.position;void 0!==t&&(t.applyMatrix4(e),t.needsUpdate=!0);var n=this.attributes.normal;if(void 0!==n){var r=(new Gg).getNormalMatrix(e);n.applyNormalMatrix(r),n.needsUpdate=!0}var i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(e),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}},{key:"applyQuaternion",value:function(e){return Pv.makeRotationFromQuaternion(e),this.applyMatrix4(Pv),this}},{key:"rotateX",value:function(e){return Pv.makeRotationX(e),this.applyMatrix4(Pv),this}},{key:"rotateY",value:function(e){return Pv.makeRotationY(e),this.applyMatrix4(Pv),this}},{key:"rotateZ",value:function(e){return Pv.makeRotationZ(e),this.applyMatrix4(Pv),this}},{key:"translate",value:function(e,t,n){return Pv.makeTranslation(e,t,n),this.applyMatrix4(Pv),this}},{key:"scale",value:function(e,t,n){return Pv.makeScale(e,t,n),this.applyMatrix4(Pv),this}},{key:"lookAt",value:function(e){return Nv.lookAt(e),Nv.updateMatrix(),this.applyMatrix4(Nv.matrix),this}},{key:"center",value:function(){return this.computeBoundingBox(),this.boundingBox.getCenter(Ov).negate(),this.translate(Ov.x,Ov.y,Ov.z),this}},{key:"setFromPoints",value:function(e){for(var t=[],n=0,r=e.length;n0&&(e.userData=this.userData),void 0!==this.parameters){var t=this.parameters;for(var n in t)void 0!==t[n]&&(e[n]=t[n]);return e}e.data={attributes:{}};var r=this.index;null!==r&&(e.data.index={type:r.array.constructor.name,array:Array.prototype.slice.call(r.array)});var i=this.attributes;for(var A in i){var a=i[A];e.data.attributes[A]=a.toJSON(e.data)}var o={},s=!1;for(var l in this.morphAttributes){for(var u=this.morphAttributes[l],c=[],d=0,h=u.length;d0&&(o[l]=c,s=!0)}s&&(e.data.morphAttributes=o,e.data.morphTargetsRelative=this.morphTargetsRelative);var p=this.groups;p.length>0&&(e.data.groups=JSON.parse(JSON.stringify(p)));var g=this.boundingSphere;return null!==g&&(e.data.boundingSphere={center:g.center.toArray(),radius:g.radius}),e}},{key:"clone",value:function(){return(new this.constructor).copy(this)}},{key:"copy",value:function(e){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;var t={};this.name=e.name;var n=e.index;null!==n&&this.setIndex(n.clone(t));var r=e.attributes;for(var i in r){var A=r[i];this.setAttribute(i,A.clone(t))}var a=e.morphAttributes;for(var o in a){for(var s=[],l=a[o],u=0,c=l.length;u0&&void 0!==arguments[0]?arguments[0]:new Kv,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:new Tv;return B(this,n),(e=t.call(this)).isMesh=!0,e.type="Mesh",e.geometry=r,e.material=i,e.updateMorphTargets(),e}return b(n,[{key:"copy",value:function(e,t){return jc(S(n.prototype),"copy",this).call(this,e,t),void 0!==e.morphTargetInfluences&&(this.morphTargetInfluences=e.morphTargetInfluences.slice()),void 0!==e.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},e.morphTargetDictionary)),this.material=e.material,this.geometry=e.geometry,this}},{key:"updateMorphTargets",value:function(){var e=this.geometry.morphAttributes,t=Object.keys(e);if(t.length>0){var n=e[t[0]];if(void 0!==n){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(var r=0,i=n.length;rn.far?null:{distance:s,point:iy.clone(),object:e}}(e,t,n,r,qv,Yv,Jv,ry);if(l){i&&(ey.fromBufferAttribute(i,a),ty.fromBufferAttribute(i,o),ny.fromBufferAttribute(i,s),l.uv=Uv.getUV(ry,qv,Yv,Jv,ey,ty,ny,new zg)),A&&(ey.fromBufferAttribute(A,a),ty.fromBufferAttribute(A,o),ny.fromBufferAttribute(A,s),l.uv2=Uv.getUV(ry,qv,Yv,Jv,ey,ty,ny,new zg));var u={a:a,b:o,c:s,normal:new gm,materialIndex:0};Uv.getNormal(qv,Yv,Jv,u.normal),l.face=u}return l}var oy=function(e){C(n,e);var t=M(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:1,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:1,a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1,o=arguments.length>4&&void 0!==arguments[4]?arguments[4]:1,s=arguments.length>5&&void 0!==arguments[5]?arguments[5]:1;B(this,n),(e=t.call(this)).type="BoxGeometry",e.parameters={width:r,height:i,depth:A,widthSegments:a,heightSegments:o,depthSegments:s};var l=U(e);a=Math.floor(a),o=Math.floor(o),s=Math.floor(s);var u=[],c=[],d=[],h=[],f=0,p=0;function g(e,t,n,r,i,A,a,o,s,g,m){for(var v=A/s,y=a/g,w=A/2,B=a/2,_=o/2,b=s+1,x=g+1,C=0,S=0,E=new gm,U=0;U0?1:-1,d.push(E.x,E.y,E.z),h.push(F/s),h.push(1-U/g),C+=1}for(var k=0;k0&&(t.defines=this.defines),t.vertexShader=this.vertexShader,t.fragmentShader=this.fragmentShader;var A={};for(var a in this.extensions)!0===this.extensions[a]&&(A[a]=!0);return Object.keys(A).length>0&&(t.extensions=A),t}}]),n}(Fv),py=function(e){C(n,e);var t=M(n);function n(){var e;return B(this,n),(e=t.call(this)).isCamera=!0,e.type="Camera",e.matrixWorldInverse=new Wm,e.projectionMatrix=new Wm,e.projectionMatrixInverse=new Wm,e}return b(n,[{key:"copy",value:function(e,t){return jc(S(n.prototype),"copy",this).call(this,e,t),this.matrixWorldInverse.copy(e.matrixWorldInverse),this.projectionMatrix.copy(e.projectionMatrix),this.projectionMatrixInverse.copy(e.projectionMatrixInverse),this}},{key:"getWorldDirection",value:function(e){this.updateWorldMatrix(!0,!1);var t=this.matrixWorld.elements;return e.set(-t[8],-t[9],-t[10]).normalize()}},{key:"updateMatrixWorld",value:function(e){jc(S(n.prototype),"updateMatrixWorld",this).call(this,e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}},{key:"updateWorldMatrix",value:function(e,t){jc(S(n.prototype),"updateWorldMatrix",this).call(this,e,t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}},{key:"clone",value:function(){return(new this.constructor).copy(this)}}]),n}(mv),gy=function(e){C(n,e);var t=M(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:50,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:.1,a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:2e3;return B(this,n),(e=t.call(this)).isPerspectiveCamera=!0,e.type="PerspectiveCamera",e.fov=r,e.zoom=1,e.near=A,e.far=a,e.focus=10,e.aspect=i,e.view=null,e.filmGauge=35,e.filmOffset=0,e.updateProjectionMatrix(),e}return b(n,[{key:"copy",value:function(e,t){return jc(S(n.prototype),"copy",this).call(this,e,t),this.fov=e.fov,this.zoom=e.zoom,this.near=e.near,this.far=e.far,this.focus=e.focus,this.aspect=e.aspect,this.view=null===e.view?null:Object.assign({},e.view),this.filmGauge=e.filmGauge,this.filmOffset=e.filmOffset,this}},{key:"setFocalLength",value:function(e){var t=.5*this.getFilmHeight()/e;this.fov=2*kg*Math.atan(t),this.updateProjectionMatrix()}},{key:"getFocalLength",value:function(){var e=Math.tan(.5*Tg*this.fov);return.5*this.getFilmHeight()/e}},{key:"getEffectiveFOV",value:function(){return 2*kg*Math.atan(Math.tan(.5*Tg*this.fov)/this.zoom)}},{key:"getFilmWidth",value:function(){return this.filmGauge*Math.min(this.aspect,1)}},{key:"getFilmHeight",value:function(){return this.filmGauge/Math.max(this.aspect,1)}},{key:"setViewOffset",value:function(e,t,n,r,i,A){this.aspect=e/t,null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=n,this.view.offsetY=r,this.view.width=i,this.view.height=A,this.updateProjectionMatrix()}},{key:"clearViewOffset",value:function(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}},{key:"updateProjectionMatrix",value:function(){var e=this.near,t=e*Math.tan(.5*Tg*this.fov)/this.zoom,n=2*t,r=this.aspect*n,i=-.5*r,A=this.view;if(null!==this.view&&this.view.enabled){var a=A.fullWidth,o=A.fullHeight;i+=A.offsetX*r/a,t-=A.offsetY*n/o,r*=A.width/a,n*=A.height/o}var s=this.filmOffset;0!==s&&(i+=e*s/this.getFilmWidth()),this.projectionMatrix.makePerspective(i,i+r,t,t-n,e,this.far),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}},{key:"toJSON",value:function(e){var t=jc(S(n.prototype),"toJSON",this).call(this,e);return t.object.fov=this.fov,t.object.zoom=this.zoom,t.object.near=this.near,t.object.far=this.far,t.object.focus=this.focus,t.object.aspect=this.aspect,null!==this.view&&(t.object.view=Object.assign({},this.view)),t.object.filmGauge=this.filmGauge,t.object.filmOffset=this.filmOffset,t}}]),n}(py),my=-90,vy=1,yy=function(e){C(n,e);var t=M(n);function n(e,r,i){var A;B(this,n),(A=t.call(this)).type="CubeCamera",A.renderTarget=i;var a=new gy(my,vy,e,r);a.layers=A.layers,a.up.set(0,1,0),a.lookAt(1,0,0),A.add(a);var o=new gy(my,vy,e,r);o.layers=A.layers,o.up.set(0,1,0),o.lookAt(-1,0,0),A.add(o);var s=new gy(my,vy,e,r);s.layers=A.layers,s.up.set(0,0,-1),s.lookAt(0,1,0),A.add(s);var l=new gy(my,vy,e,r);l.layers=A.layers,l.up.set(0,0,1),l.lookAt(0,-1,0),A.add(l);var u=new gy(my,vy,e,r);u.layers=A.layers,u.up.set(0,1,0),u.lookAt(0,0,1),A.add(u);var c=new gy(my,vy,e,r);return c.layers=A.layers,c.up.set(0,1,0),c.lookAt(0,0,-1),A.add(c),A}return b(n,[{key:"update",value:function(e,t){null===this.parent&&this.updateMatrixWorld();var n=this.renderTarget,r=v(this.children,6),i=r[0],A=r[1],a=r[2],o=r[3],s=r[4],l=r[5],u=e.getRenderTarget(),c=e.toneMapping,d=e.xr.enabled;e.toneMapping=Gf,e.xr.enabled=!1;var h=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,e.setRenderTarget(n,0),e.render(t,i),e.setRenderTarget(n,1),e.render(t,A),e.setRenderTarget(n,2),e.render(t,a),e.setRenderTarget(n,3),e.render(t,o),e.setRenderTarget(n,4),e.render(t,s),n.texture.generateMipmaps=h,e.setRenderTarget(n,5),e.render(t,l),e.setRenderTarget(u),e.toneMapping=c,e.xr.enabled=d,n.texture.needsPMREMUpdate=!0}}]),n}(mv),wy=function(e){C(n,e);var t=M(n);function n(e,r,i,A,a,o,s,l,u,c){var d;return B(this,n),e=void 0!==e?e:[],r=void 0!==r?r:Yf,(d=t.call(this,e,r,i,A,a,o,s,l,u,c)).isCubeTexture=!0,d.flipY=!1,d}return b(n,[{key:"images",get:function(){return this.image},set:function(e){this.image=e}}]),n}(um),By=function(e){C(n,e);var t=M(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:1,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};B(this,n),(e=t.call(this,r,r,i)).isWebGLCubeRenderTarget=!0;var A={width:r,height:r,depth:1},a=[A,A,A,A,A,A];return e.texture=new wy(a,i.mapping,i.wrapS,i.wrapT,i.magFilter,i.minFilter,i.format,i.type,i.anisotropy,i.encoding),e.texture.isRenderTargetTexture=!0,e.texture.generateMipmaps=void 0!==i.generateMipmaps&&i.generateMipmaps,e.texture.minFilter=void 0!==i.minFilter?i.minFilter:op,e}return b(n,[{key:"fromEquirectangularTexture",value:function(e,t){this.texture.type=t.type,this.texture.encoding=t.encoding,this.texture.generateMipmaps=t.generateMipmaps,this.texture.minFilter=t.minFilter,this.texture.magFilter=t.magFilter;var n={tEquirect:{value:null}},r="\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\n\t\t\t\t\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n\n\t\t\t\t}\n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvWorldDirection = transformDirection( position, modelMatrix );\n\n\t\t\t\t\t#include \n\t\t\t\t\t#include \n\n\t\t\t\t}\n\t\t\t",i="\n\n\t\t\t\tuniform sampler2D tEquirect;\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\t#include \n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvec3 direction = normalize( vWorldDirection );\n\n\t\t\t\t\tvec2 sampleUV = equirectUv( direction );\n\n\t\t\t\t\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\n\t\t\t\t}\n\t\t\t",A=new oy(5,5,5),a=new fy({name:"CubemapFromEquirect",uniforms:sy(n),vertexShader:r,fragmentShader:i,side:lf,blending:cf});a.uniforms.tEquirect.value=t;var o=new Ay(A,a),s=t.minFilter;return t.minFilter===lp&&(t.minFilter=op),new yy(1,10,this).update(e,o),t.minFilter=s,o.geometry.dispose(),o.material.dispose(),this}},{key:"clear",value:function(e,t,n,r){for(var i=e.getRenderTarget(),A=0;A<6;A++)e.setRenderTarget(this,A),e.clear(t,n,r);e.setRenderTarget(i)}}]),n}(dm),_y=new gm,by=new gm,xy=new Gg,Cy=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:new gm(1,0,0),n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0;B(this,e),this.isPlane=!0,this.normal=t,this.constant=n}return b(e,[{key:"set",value:function(e,t){return this.normal.copy(e),this.constant=t,this}},{key:"setComponents",value:function(e,t,n,r){return this.normal.set(e,t,n),this.constant=r,this}},{key:"setFromNormalAndCoplanarPoint",value:function(e,t){return this.normal.copy(e),this.constant=-t.dot(this.normal),this}},{key:"setFromCoplanarPoints",value:function(e,t,n){var r=_y.subVectors(n,t).cross(by.subVectors(e,t)).normalize();return this.setFromNormalAndCoplanarPoint(r,e),this}},{key:"copy",value:function(e){return this.normal.copy(e.normal),this.constant=e.constant,this}},{key:"normalize",value:function(){var e=1/this.normal.length();return this.normal.multiplyScalar(e),this.constant*=e,this}},{key:"negate",value:function(){return this.constant*=-1,this.normal.negate(),this}},{key:"distanceToPoint",value:function(e){return this.normal.dot(e)+this.constant}},{key:"distanceToSphere",value:function(e){return this.distanceToPoint(e.center)-e.radius}},{key:"projectPoint",value:function(e,t){return t.copy(this.normal).multiplyScalar(-this.distanceToPoint(e)).add(e)}},{key:"intersectLine",value:function(e,t){var n=e.delta(_y),r=this.normal.dot(n);if(0===r)return 0===this.distanceToPoint(e.start)?t.copy(e.start):null;var i=-(e.start.dot(this.normal)+this.constant)/r;return i<0||i>1?null:t.copy(n).multiplyScalar(i).add(e.start)}},{key:"intersectsLine",value:function(e){var t=this.distanceToPoint(e.start),n=this.distanceToPoint(e.end);return t<0&&n>0||n<0&&t>0}},{key:"intersectsBox",value:function(e){return e.intersectsPlane(this)}},{key:"intersectsSphere",value:function(e){return e.intersectsPlane(this)}},{key:"coplanarPoint",value:function(e){return e.copy(this.normal).multiplyScalar(-this.constant)}},{key:"applyMatrix4",value:function(e,t){var n=t||xy.getNormalMatrix(e),r=this.coplanarPoint(_y).applyMatrix4(e),i=this.normal.applyMatrix3(n).normalize();return this.constant=-r.dot(i),this}},{key:"translate",value:function(e){return this.constant-=e.dot(this.normal),this}},{key:"equals",value:function(e){return e.normal.equals(this.normal)&&e.constant===this.constant}},{key:"clone",value:function(){return(new this.constructor).copy(this)}}]),e}(),Sy=new Rm,Ey=new gm,Uy=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:new Cy,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:new Cy,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:new Cy,i=arguments.length>3&&void 0!==arguments[3]?arguments[3]:new Cy,A=arguments.length>4&&void 0!==arguments[4]?arguments[4]:new Cy,a=arguments.length>5&&void 0!==arguments[5]?arguments[5]:new Cy;B(this,e),this.planes=[t,n,r,i,A,a]}return b(e,[{key:"set",value:function(e,t,n,r,i,A){var a=this.planes;return a[0].copy(e),a[1].copy(t),a[2].copy(n),a[3].copy(r),a[4].copy(i),a[5].copy(A),this}},{key:"copy",value:function(e){for(var t=this.planes,n=0;n<6;n++)t[n].copy(e.planes[n]);return this}},{key:"setFromProjectionMatrix",value:function(e){var t=this.planes,n=e.elements,r=n[0],i=n[1],A=n[2],a=n[3],o=n[4],s=n[5],l=n[6],u=n[7],c=n[8],d=n[9],h=n[10],f=n[11],p=n[12],g=n[13],m=n[14],v=n[15];return t[0].setComponents(a-r,u-o,f-c,v-p).normalize(),t[1].setComponents(a+r,u+o,f+c,v+p).normalize(),t[2].setComponents(a+i,u+s,f+d,v+g).normalize(),t[3].setComponents(a-i,u-s,f-d,v-g).normalize(),t[4].setComponents(a-A,u-l,f-h,v-m).normalize(),t[5].setComponents(a+A,u+l,f+h,v+m).normalize(),this}},{key:"intersectsObject",value:function(e){var t=e.geometry;return null===t.boundingSphere&&t.computeBoundingSphere(),Sy.copy(t.boundingSphere).applyMatrix4(e.matrixWorld),this.intersectsSphere(Sy)}},{key:"intersectsSprite",value:function(e){return Sy.center.set(0,0,0),Sy.radius=.7071067811865476,Sy.applyMatrix4(e.matrixWorld),this.intersectsSphere(Sy)}},{key:"intersectsSphere",value:function(e){for(var t=this.planes,n=e.center,r=-e.radius,i=0;i<6;i++){if(t[i].distanceToPoint(n)0?e.max.x:e.min.x,Ey.y=r.normal.y>0?e.max.y:e.min.y,Ey.z=r.normal.z>0?e.max.z:e.min.z,r.distanceToPoint(Ey)<0)return!1}return!0}},{key:"containsPoint",value:function(e){for(var t=this.planes,n=0;n<6;n++)if(t[n].distanceToPoint(e)<0)return!1;return!0}},{key:"clone",value:function(){return(new this.constructor).copy(this)}}]),e}();function My(){var e=null,t=!1,n=null,r=null;function i(t,A){n(t,A),r=e.requestAnimationFrame(i)}return{start:function(){!0!==t&&null!==n&&(r=e.requestAnimationFrame(i),t=!0)},stop:function(){e.cancelAnimationFrame(r),t=!1},setAnimationLoop:function(e){n=e},setContext:function(t){e=t}}}function Fy(e,t){var n=t.isWebGL2,r=new WeakMap;return{get:function(e){return e.isInterleavedBufferAttribute&&(e=e.data),r.get(e)},remove:function(t){t.isInterleavedBufferAttribute&&(t=t.data);var n=r.get(t);n&&(e.deleteBuffer(n.buffer),r.delete(t))},update:function(t,i){if(t.isGLBufferAttribute){var A=r.get(t);(!A||A.version0&&void 0!==arguments[0]?arguments[0]:1,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,A=arguments.length>2&&void 0!==arguments[2]?arguments[2]:1,a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1;B(this,n),(e=t.call(this)).type="PlaneGeometry",e.parameters={width:r,height:i,widthSegments:A,heightSegments:a};for(var o=r/2,s=i/2,l=Math.floor(A),u=Math.floor(a),c=l+1,d=u+1,h=r/l,f=i/u,p=[],g=[],m=[],v=[],y=0;y 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\n\treturn cross( v1, v2 ) * theta_sintheta;\n}\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\n\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\n\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\n\tvec3 lightNormal = cross( v1, v2 );\n\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\n\tvec3 T1, T2;\n\tT1 = normalize( V - N * dot( V, N ) );\n\tT2 = - cross( N, T1 );\n\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\n\tvec3 coords[ 4 ];\n\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\n\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\n\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\n\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\n\tcoords[ 0 ] = normalize( coords[ 0 ] );\n\tcoords[ 1 ] = normalize( coords[ 1 ] );\n\tcoords[ 2 ] = normalize( coords[ 2 ] );\n\tcoords[ 3 ] = normalize( coords[ 3 ] );\n\tvec3 vectorFormFactor = vec3( 0.0 );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\n\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\n\treturn vec3( result );\n}\nfloat G_BlinnPhong_Implicit( ) {\n\treturn 0.25;\n}\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\n\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\n}\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\n\tfloat G = G_BlinnPhong_Implicit( );\n\tfloat D = D_BlinnPhong( shininess, dotNH );\n\treturn F * ( G * D );\n}\n#if defined( USE_SHEEN )\nfloat D_Charlie( float roughness, float dotNH ) {\n\tfloat alpha = pow2( roughness );\n\tfloat invAlpha = 1.0 / alpha;\n\tfloat cos2h = dotNH * dotNH;\n\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 );\n\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\n}\nfloat V_Neubelt( float dotNV, float dotNL ) {\n\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\n}\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenColor, const in float sheenRoughness ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat D = D_Charlie( sheenRoughness, dotNH );\n\tfloat V = V_Neubelt( dotNV, dotNL );\n\treturn sheenColor * ( D * V );\n}\n#endif",iridescence_fragment:"#ifdef USE_IRIDESCENCE\n\tconst mat3 XYZ_TO_REC709 = mat3(\n\t\t 3.2404542, -0.9692660, 0.0556434,\n\t\t-1.5371385, 1.8760108, -0.2040259,\n\t\t-0.4985314, 0.0415560, 1.0572252\n\t);\n\tvec3 Fresnel0ToIor( vec3 fresnel0 ) {\n\t\tvec3 sqrtF0 = sqrt( fresnel0 );\n\t\treturn ( vec3( 1.0 ) + sqrtF0 ) / ( vec3( 1.0 ) - sqrtF0 );\n\t}\n\tvec3 IorToFresnel0( vec3 transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - vec3( incidentIor ) ) / ( transmittedIor + vec3( incidentIor ) ) );\n\t}\n\tfloat IorToFresnel0( float transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - incidentIor ) / ( transmittedIor + incidentIor ));\n\t}\n\tvec3 evalSensitivity( float OPD, vec3 shift ) {\n\t\tfloat phase = 2.0 * PI * OPD * 1.0e-9;\n\t\tvec3 val = vec3( 5.4856e-13, 4.4201e-13, 5.2481e-13 );\n\t\tvec3 pos = vec3( 1.6810e+06, 1.7953e+06, 2.2084e+06 );\n\t\tvec3 var = vec3( 4.3278e+09, 9.3046e+09, 6.6121e+09 );\n\t\tvec3 xyz = val * sqrt( 2.0 * PI * var ) * cos( pos * phase + shift ) * exp( - pow2( phase ) * var );\n\t\txyz.x += 9.7470e-14 * sqrt( 2.0 * PI * 4.5282e+09 ) * cos( 2.2399e+06 * phase + shift[ 0 ] ) * exp( - 4.5282e+09 * pow2( phase ) );\n\t\txyz /= 1.0685e-7;\n\t\tvec3 rgb = XYZ_TO_REC709 * xyz;\n\t\treturn rgb;\n\t}\n\tvec3 evalIridescence( float outsideIOR, float eta2, float cosTheta1, float thinFilmThickness, vec3 baseF0 ) {\n\t\tvec3 I;\n\t\tfloat iridescenceIOR = mix( outsideIOR, eta2, smoothstep( 0.0, 0.03, thinFilmThickness ) );\n\t\tfloat sinTheta2Sq = pow2( outsideIOR / iridescenceIOR ) * ( 1.0 - pow2( cosTheta1 ) );\n\t\tfloat cosTheta2Sq = 1.0 - sinTheta2Sq;\n\t\tif ( cosTheta2Sq < 0.0 ) {\n\t\t\t return vec3( 1.0 );\n\t\t}\n\t\tfloat cosTheta2 = sqrt( cosTheta2Sq );\n\t\tfloat R0 = IorToFresnel0( iridescenceIOR, outsideIOR );\n\t\tfloat R12 = F_Schlick( R0, 1.0, cosTheta1 );\n\t\tfloat R21 = R12;\n\t\tfloat T121 = 1.0 - R12;\n\t\tfloat phi12 = 0.0;\n\t\tif ( iridescenceIOR < outsideIOR ) phi12 = PI;\n\t\tfloat phi21 = PI - phi12;\n\t\tvec3 baseIOR = Fresnel0ToIor( clamp( baseF0, 0.0, 0.9999 ) );\t\tvec3 R1 = IorToFresnel0( baseIOR, iridescenceIOR );\n\t\tvec3 R23 = F_Schlick( R1, 1.0, cosTheta2 );\n\t\tvec3 phi23 = vec3( 0.0 );\n\t\tif ( baseIOR[ 0 ] < iridescenceIOR ) phi23[ 0 ] = PI;\n\t\tif ( baseIOR[ 1 ] < iridescenceIOR ) phi23[ 1 ] = PI;\n\t\tif ( baseIOR[ 2 ] < iridescenceIOR ) phi23[ 2 ] = PI;\n\t\tfloat OPD = 2.0 * iridescenceIOR * thinFilmThickness * cosTheta2;\n\t\tvec3 phi = vec3( phi21 ) + phi23;\n\t\tvec3 R123 = clamp( R12 * R23, 1e-5, 0.9999 );\n\t\tvec3 r123 = sqrt( R123 );\n\t\tvec3 Rs = pow2( T121 ) * R23 / ( vec3( 1.0 ) - R123 );\n\t\tvec3 C0 = R12 + Rs;\n\t\tI = C0;\n\t\tvec3 Cm = Rs - T121;\n\t\tfor ( int m = 1; m <= 2; ++ m ) {\n\t\t\tCm *= r123;\n\t\t\tvec3 Sm = 2.0 * evalSensitivity( float( m ) * OPD, float( m ) * phi );\n\t\t\tI += Cm * Sm;\n\t\t}\n\t\treturn max( I, vec3( 0.0 ) );\n\t}\n#endif",bumpmap_pars_fragment:"#ifdef USE_BUMPMAP\n\tuniform sampler2D bumpMap;\n\tuniform float bumpScale;\n\tvec2 dHdxy_fwd() {\n\t\tvec2 dSTdx = dFdx( vUv );\n\t\tvec2 dSTdy = dFdy( vUv );\n\t\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\n\t\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\n\t\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\n\t\treturn vec2( dBx, dBy );\n\t}\n\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\n\t\tvec3 vSigmaX = dFdx( surf_pos.xyz );\n\t\tvec3 vSigmaY = dFdy( surf_pos.xyz );\n\t\tvec3 vN = surf_norm;\n\t\tvec3 R1 = cross( vSigmaY, vN );\n\t\tvec3 R2 = cross( vN, vSigmaX );\n\t\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\n\t\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\n\t\treturn normalize( abs( fDet ) * surf_norm - vGrad );\n\t}\n#endif",clipping_planes_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvec4 plane;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\tplane = clippingPlanes[ i ];\n\t\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\n\t}\n\t#pragma unroll_loop_end\n\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\tbool clipped = true;\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\tif ( clipped ) discard;\n\t#endif\n#endif",clipping_planes_pars_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\n#endif",clipping_planes_pars_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n#endif",clipping_planes_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvClipPosition = - mvPosition.xyz;\n#endif",color_fragment:"#if defined( USE_COLOR_ALPHA )\n\tdiffuseColor *= vColor;\n#elif defined( USE_COLOR )\n\tdiffuseColor.rgb *= vColor;\n#endif",color_pars_fragment:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR )\n\tvarying vec3 vColor;\n#endif",color_pars_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\n\tvarying vec3 vColor;\n#endif",color_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvColor = vec4( 1.0 );\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\n\tvColor = vec3( 1.0 );\n#endif\n#ifdef USE_COLOR\n\tvColor *= color;\n#endif\n#ifdef USE_INSTANCING_COLOR\n\tvColor.xyz *= instanceColor.xyz;\n#endif",common:"#define PI 3.141592653589793\n#define PI2 6.283185307179586\n#define PI_HALF 1.5707963267948966\n#define RECIPROCAL_PI 0.3183098861837907\n#define RECIPROCAL_PI2 0.15915494309189535\n#define EPSILON 1e-6\n#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\nfloat pow2( const in float x ) { return x*x; }\nvec3 pow2( const in vec3 x ) { return x*x; }\nfloat pow3( const in float x ) { return x*x*x; }\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\nfloat average( const in vec3 v ) { return dot( v, vec3( 0.3333333 ) ); }\nhighp float rand( const in vec2 uv ) {\n\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\n\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\n\treturn fract( sin( sn ) * c );\n}\n#ifdef HIGH_PRECISION\n\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\n#else\n\tfloat precisionSafeLength( vec3 v ) {\n\t\tfloat maxComponent = max3( abs( v ) );\n\t\treturn length( v / maxComponent ) * maxComponent;\n\t}\n#endif\nstruct IncidentLight {\n\tvec3 color;\n\tvec3 direction;\n\tbool visible;\n};\nstruct ReflectedLight {\n\tvec3 directDiffuse;\n\tvec3 directSpecular;\n\tvec3 indirectDiffuse;\n\tvec3 indirectSpecular;\n};\nstruct GeometricContext {\n\tvec3 position;\n\tvec3 normal;\n\tvec3 viewDir;\n#ifdef USE_CLEARCOAT\n\tvec3 clearcoatNormal;\n#endif\n};\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n}\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\n}\nmat3 transposeMat3( const in mat3 m ) {\n\tmat3 tmp;\n\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\n\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\n\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\n\treturn tmp;\n}\nfloat luminance( const in vec3 rgb ) {\n\tconst vec3 weights = vec3( 0.2126729, 0.7151522, 0.0721750 );\n\treturn dot( weights, rgb );\n}\nbool isPerspectiveMatrix( mat4 m ) {\n\treturn m[ 2 ][ 3 ] == - 1.0;\n}\nvec2 equirectUv( in vec3 dir ) {\n\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\n\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\n\treturn vec2( u, v );\n}",cube_uv_reflection_fragment:"#ifdef ENVMAP_TYPE_CUBE_UV\n\t#define cubeUV_minMipLevel 4.0\n\t#define cubeUV_minTileSize 16.0\n\tfloat getFace( vec3 direction ) {\n\t\tvec3 absDirection = abs( direction );\n\t\tfloat face = - 1.0;\n\t\tif ( absDirection.x > absDirection.z ) {\n\t\t\tif ( absDirection.x > absDirection.y )\n\t\t\t\tface = direction.x > 0.0 ? 0.0 : 3.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t} else {\n\t\t\tif ( absDirection.z > absDirection.y )\n\t\t\t\tface = direction.z > 0.0 ? 2.0 : 5.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t}\n\t\treturn face;\n\t}\n\tvec2 getUV( vec3 direction, float face ) {\n\t\tvec2 uv;\n\t\tif ( face == 0.0 ) {\n\t\t\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 1.0 ) {\n\t\t\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\n\t\t} else if ( face == 2.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\n\t\t} else if ( face == 3.0 ) {\n\t\t\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 4.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\n\t\t} else {\n\t\t\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\n\t\t}\n\t\treturn 0.5 * ( uv + 1.0 );\n\t}\n\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\n\t\tfloat face = getFace( direction );\n\t\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\n\t\tmipInt = max( mipInt, cubeUV_minMipLevel );\n\t\tfloat faceSize = exp2( mipInt );\n\t\thighp vec2 uv = getUV( direction, face ) * ( faceSize - 2.0 ) + 1.0;\n\t\tif ( face > 2.0 ) {\n\t\t\tuv.y += faceSize;\n\t\t\tface -= 3.0;\n\t\t}\n\t\tuv.x += face * faceSize;\n\t\tuv.x += filterInt * 3.0 * cubeUV_minTileSize;\n\t\tuv.y += 4.0 * ( exp2( CUBEUV_MAX_MIP ) - faceSize );\n\t\tuv.x *= CUBEUV_TEXEL_WIDTH;\n\t\tuv.y *= CUBEUV_TEXEL_HEIGHT;\n\t\t#ifdef texture2DGradEXT\n\t\t\treturn texture2DGradEXT( envMap, uv, vec2( 0.0 ), vec2( 0.0 ) ).rgb;\n\t\t#else\n\t\t\treturn texture2D( envMap, uv ).rgb;\n\t\t#endif\n\t}\n\t#define cubeUV_r0 1.0\n\t#define cubeUV_v0 0.339\n\t#define cubeUV_m0 - 2.0\n\t#define cubeUV_r1 0.8\n\t#define cubeUV_v1 0.276\n\t#define cubeUV_m1 - 1.0\n\t#define cubeUV_r4 0.4\n\t#define cubeUV_v4 0.046\n\t#define cubeUV_m4 2.0\n\t#define cubeUV_r5 0.305\n\t#define cubeUV_v5 0.016\n\t#define cubeUV_m5 3.0\n\t#define cubeUV_r6 0.21\n\t#define cubeUV_v6 0.0038\n\t#define cubeUV_m6 4.0\n\tfloat roughnessToMip( float roughness ) {\n\t\tfloat mip = 0.0;\n\t\tif ( roughness >= cubeUV_r1 ) {\n\t\t\tmip = ( cubeUV_r0 - roughness ) * ( cubeUV_m1 - cubeUV_m0 ) / ( cubeUV_r0 - cubeUV_r1 ) + cubeUV_m0;\n\t\t} else if ( roughness >= cubeUV_r4 ) {\n\t\t\tmip = ( cubeUV_r1 - roughness ) * ( cubeUV_m4 - cubeUV_m1 ) / ( cubeUV_r1 - cubeUV_r4 ) + cubeUV_m1;\n\t\t} else if ( roughness >= cubeUV_r5 ) {\n\t\t\tmip = ( cubeUV_r4 - roughness ) * ( cubeUV_m5 - cubeUV_m4 ) / ( cubeUV_r4 - cubeUV_r5 ) + cubeUV_m4;\n\t\t} else if ( roughness >= cubeUV_r6 ) {\n\t\t\tmip = ( cubeUV_r5 - roughness ) * ( cubeUV_m6 - cubeUV_m5 ) / ( cubeUV_r5 - cubeUV_r6 ) + cubeUV_m5;\n\t\t} else {\n\t\t\tmip = - 2.0 * log2( 1.16 * roughness );\t\t}\n\t\treturn mip;\n\t}\n\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\n\t\tfloat mip = clamp( roughnessToMip( roughness ), cubeUV_m0, CUBEUV_MAX_MIP );\n\t\tfloat mipF = fract( mip );\n\t\tfloat mipInt = floor( mip );\n\t\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\n\t\tif ( mipF == 0.0 ) {\n\t\t\treturn vec4( color0, 1.0 );\n\t\t} else {\n\t\t\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\n\t\t\treturn vec4( mix( color0, color1, mipF ), 1.0 );\n\t\t}\n\t}\n#endif",defaultnormal_vertex:"vec3 transformedNormal = objectNormal;\n#ifdef USE_INSTANCING\n\tmat3 m = mat3( instanceMatrix );\n\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\n\ttransformedNormal = m * transformedNormal;\n#endif\ntransformedNormal = normalMatrix * transformedNormal;\n#ifdef FLIP_SIDED\n\ttransformedNormal = - transformedNormal;\n#endif\n#ifdef USE_TANGENT\n\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#ifdef FLIP_SIDED\n\t\ttransformedTangent = - transformedTangent;\n\t#endif\n#endif",displacementmap_pars_vertex:"#ifdef USE_DISPLACEMENTMAP\n\tuniform sampler2D displacementMap;\n\tuniform float displacementScale;\n\tuniform float displacementBias;\n#endif",displacementmap_vertex:"#ifdef USE_DISPLACEMENTMAP\n\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\n#endif",emissivemap_fragment:"#ifdef USE_EMISSIVEMAP\n\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\n\ttotalEmissiveRadiance *= emissiveColor.rgb;\n#endif",emissivemap_pars_fragment:"#ifdef USE_EMISSIVEMAP\n\tuniform sampler2D emissiveMap;\n#endif",encodings_fragment:"gl_FragColor = linearToOutputTexel( gl_FragColor );",encodings_pars_fragment:"vec4 LinearToLinear( in vec4 value ) {\n\treturn value;\n}\nvec4 LinearTosRGB( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\n}",envmap_fragment:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvec3 cameraToFrag;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\n\t\t#else\n\t\t\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\n\t\t#endif\n\t#else\n\t\tvec3 reflectVec = vReflect;\n\t#endif\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\n\t#else\n\t\tvec4 envColor = vec4( 0.0 );\n\t#endif\n\t#ifdef ENVMAP_BLENDING_MULTIPLY\n\t\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_MIX )\n\t\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_ADD )\n\t\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\n\t#endif\n#endif",envmap_common_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float envMapIntensity;\n\tuniform float flipEnvMap;\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tuniform samplerCube envMap;\n\t#else\n\t\tuniform sampler2D envMap;\n\t#endif\n\t\n#endif",envmap_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float reflectivity;\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\tvarying vec3 vWorldPosition;\n\t\tuniform float refractionRatio;\n\t#else\n\t\tvarying vec3 vReflect;\n\t#endif\n#endif",envmap_pars_vertex:"#ifdef USE_ENVMAP\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\t\n\t\tvarying vec3 vWorldPosition;\n\t#else\n\t\tvarying vec3 vReflect;\n\t\tuniform float refractionRatio;\n\t#endif\n#endif",envmap_physical_pars_fragment:"#if defined( USE_ENVMAP )\n\tvec3 getIBLIrradiance( const in vec3 normal ) {\n\t\t#if defined( ENVMAP_TYPE_CUBE_UV )\n\t\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\n\t\t\treturn PI * envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\n\t\t#if defined( ENVMAP_TYPE_CUBE_UV )\n\t\t\tvec3 reflectVec = reflect( - viewDir, normal );\n\t\t\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\n\t\t\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\n\t\t\treturn envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n#endif",envmap_vertex:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvWorldPosition = worldPosition.xyz;\n\t#else\n\t\tvec3 cameraToVertex;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvReflect = reflect( cameraToVertex, worldNormal );\n\t\t#else\n\t\t\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\n\t\t#endif\n\t#endif\n#endif",fog_vertex:"#ifdef USE_FOG\n\tvFogDepth = - mvPosition.z;\n#endif",fog_pars_vertex:"#ifdef USE_FOG\n\tvarying float vFogDepth;\n#endif",fog_fragment:"#ifdef USE_FOG\n\t#ifdef FOG_EXP2\n\t\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\n\t#else\n\t\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\n\t#endif\n\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\n#endif",fog_pars_fragment:"#ifdef USE_FOG\n\tuniform vec3 fogColor;\n\tvarying float vFogDepth;\n\t#ifdef FOG_EXP2\n\t\tuniform float fogDensity;\n\t#else\n\t\tuniform float fogNear;\n\t\tuniform float fogFar;\n\t#endif\n#endif",gradientmap_pars_fragment:"#ifdef USE_GRADIENTMAP\n\tuniform sampler2D gradientMap;\n#endif\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\n\tfloat dotNL = dot( normal, lightDirection );\n\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\n\t#ifdef USE_GRADIENTMAP\n\t\treturn vec3( texture2D( gradientMap, coord ).r );\n\t#else\n\t\tvec2 fw = fwidth( coord ) * 0.5;\n\t\treturn mix( vec3( 0.7 ), vec3( 1.0 ), smoothstep( 0.7 - fw.x, 0.7 + fw.x, coord.x ) );\n\t#endif\n}",lightmap_fragment:"#ifdef USE_LIGHTMAP\n\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\n\tvec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;\n\treflectedLight.indirectDiffuse += lightMapIrradiance;\n#endif",lightmap_pars_fragment:"#ifdef USE_LIGHTMAP\n\tuniform sampler2D lightMap;\n\tuniform float lightMapIntensity;\n#endif",lights_lambert_fragment:"LambertMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularStrength = specularStrength;",lights_lambert_pars_fragment:"varying vec3 vViewPosition;\nstruct LambertMaterial {\n\tvec3 diffuseColor;\n\tfloat specularStrength;\n};\nvoid RE_Direct_Lambert( const in IncidentLight directLight, const in GeometricContext geometry, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Lambert( const in vec3 irradiance, const in GeometricContext geometry, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Lambert\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Lambert",lights_pars_begin:"uniform bool receiveShadow;\nuniform vec3 ambientLightColor;\nuniform vec3 lightProbe[ 9 ];\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\n\tfloat x = normal.x, y = normal.y, z = normal.z;\n\tvec3 result = shCoefficients[ 0 ] * 0.886227;\n\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\n\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\n\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\n\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\n\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\n\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\n\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\n\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\n\treturn result;\n}\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\n\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\n\treturn irradiance;\n}\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\n\tvec3 irradiance = ambientLightColor;\n\treturn irradiance;\n}\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\n\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\n\t\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\n\t\tif ( cutoffDistance > 0.0 ) {\n\t\t\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\n\t\t}\n\t\treturn distanceFalloff;\n\t#else\n\t\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\n\t\t\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\n\t\t}\n\t\treturn 1.0;\n\t#endif\n}\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\n\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\n}\n#if NUM_DIR_LIGHTS > 0\n\tstruct DirectionalLight {\n\t\tvec3 direction;\n\t\tvec3 color;\n\t};\n\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\n\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\n\t\tlight.color = directionalLight.color;\n\t\tlight.direction = directionalLight.direction;\n\t\tlight.visible = true;\n\t}\n#endif\n#if NUM_POINT_LIGHTS > 0\n\tstruct PointLight {\n\t\tvec3 position;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t};\n\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\n\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\n\t\tvec3 lVector = pointLight.position - geometry.position;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat lightDistance = length( lVector );\n\t\tlight.color = pointLight.color;\n\t\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\n\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t}\n#endif\n#if NUM_SPOT_LIGHTS > 0\n\tstruct SpotLight {\n\t\tvec3 position;\n\t\tvec3 direction;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t\tfloat coneCos;\n\t\tfloat penumbraCos;\n\t};\n\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\n\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\n\t\tvec3 lVector = spotLight.position - geometry.position;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat angleCos = dot( light.direction, spotLight.direction );\n\t\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\n\t\tif ( spotAttenuation > 0.0 ) {\n\t\t\tfloat lightDistance = length( lVector );\n\t\t\tlight.color = spotLight.color * spotAttenuation;\n\t\t\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\n\t\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t\t} else {\n\t\t\tlight.color = vec3( 0.0 );\n\t\t\tlight.visible = false;\n\t\t}\n\t}\n#endif\n#if NUM_RECT_AREA_LIGHTS > 0\n\tstruct RectAreaLight {\n\t\tvec3 color;\n\t\tvec3 position;\n\t\tvec3 halfWidth;\n\t\tvec3 halfHeight;\n\t};\n\tuniform sampler2D ltc_1;\tuniform sampler2D ltc_2;\n\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\n#endif\n#if NUM_HEMI_LIGHTS > 0\n\tstruct HemisphereLight {\n\t\tvec3 direction;\n\t\tvec3 skyColor;\n\t\tvec3 groundColor;\n\t};\n\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\n\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\n\t\tfloat dotNL = dot( normal, hemiLight.direction );\n\t\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\n\t\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\n\t\treturn irradiance;\n\t}\n#endif",lights_toon_fragment:"ToonMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;",lights_toon_pars_fragment:"varying vec3 vViewPosition;\nstruct ToonMaterial {\n\tvec3 diffuseColor;\n};\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Toon\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Toon",lights_phong_fragment:"BlinnPhongMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularColor = specular;\nmaterial.specularShininess = shininess;\nmaterial.specularStrength = specularStrength;",lights_phong_pars_fragment:"varying vec3 vViewPosition;\nstruct BlinnPhongMaterial {\n\tvec3 diffuseColor;\n\tvec3 specularColor;\n\tfloat specularShininess;\n\tfloat specularStrength;\n};\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\n}\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_BlinnPhong\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_BlinnPhong",lights_physical_fragment:"PhysicalMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\nmaterial.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;\nmaterial.roughness = min( material.roughness, 1.0 );\n#ifdef IOR\n\tmaterial.ior = ior;\n\t#ifdef SPECULAR\n\t\tfloat specularIntensityFactor = specularIntensity;\n\t\tvec3 specularColorFactor = specularColor;\n\t\t#ifdef USE_SPECULARINTENSITYMAP\n\t\t\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\n\t\t#endif\n\t\t#ifdef USE_SPECULARCOLORMAP\n\t\t\tspecularColorFactor *= texture2D( specularColorMap, vUv ).rgb;\n\t\t#endif\n\t\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\n\t#else\n\t\tfloat specularIntensityFactor = 1.0;\n\t\tvec3 specularColorFactor = vec3( 1.0 );\n\t\tmaterial.specularF90 = 1.0;\n\t#endif\n\tmaterial.specularColor = mix( min( pow2( ( material.ior - 1.0 ) / ( material.ior + 1.0 ) ) * specularColorFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\n#else\n\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\n\tmaterial.specularF90 = 1.0;\n#endif\n#ifdef USE_CLEARCOAT\n\tmaterial.clearcoat = clearcoat;\n\tmaterial.clearcoatRoughness = clearcoatRoughness;\n\tmaterial.clearcoatF0 = vec3( 0.04 );\n\tmaterial.clearcoatF90 = 1.0;\n\t#ifdef USE_CLEARCOATMAP\n\t\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\n\t#endif\n\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\t\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\n\t#endif\n\tmaterial.clearcoat = saturate( material.clearcoat );\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\n\tmaterial.clearcoatRoughness += geometryRoughness;\n\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\n#endif\n#ifdef USE_IRIDESCENCE\n\tmaterial.iridescence = iridescence;\n\tmaterial.iridescenceIOR = iridescenceIOR;\n\t#ifdef USE_IRIDESCENCEMAP\n\t\tmaterial.iridescence *= texture2D( iridescenceMap, vUv ).r;\n\t#endif\n\t#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\t\tmaterial.iridescenceThickness = (iridescenceThicknessMaximum - iridescenceThicknessMinimum) * texture2D( iridescenceThicknessMap, vUv ).g + iridescenceThicknessMinimum;\n\t#else\n\t\tmaterial.iridescenceThickness = iridescenceThicknessMaximum;\n\t#endif\n#endif\n#ifdef USE_SHEEN\n\tmaterial.sheenColor = sheenColor;\n\t#ifdef USE_SHEENCOLORMAP\n\t\tmaterial.sheenColor *= texture2D( sheenColorMap, vUv ).rgb;\n\t#endif\n\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\n\t#ifdef USE_SHEENROUGHNESSMAP\n\t\tmaterial.sheenRoughness *= texture2D( sheenRoughnessMap, vUv ).a;\n\t#endif\n#endif",lights_physical_pars_fragment:"struct PhysicalMaterial {\n\tvec3 diffuseColor;\n\tfloat roughness;\n\tvec3 specularColor;\n\tfloat specularF90;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat clearcoat;\n\t\tfloat clearcoatRoughness;\n\t\tvec3 clearcoatF0;\n\t\tfloat clearcoatF90;\n\t#endif\n\t#ifdef USE_IRIDESCENCE\n\t\tfloat iridescence;\n\t\tfloat iridescenceIOR;\n\t\tfloat iridescenceThickness;\n\t\tvec3 iridescenceFresnel;\n\t\tvec3 iridescenceF0;\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tvec3 sheenColor;\n\t\tfloat sheenRoughness;\n\t#endif\n\t#ifdef IOR\n\t\tfloat ior;\n\t#endif\n\t#ifdef USE_TRANSMISSION\n\t\tfloat transmission;\n\t\tfloat transmissionAlpha;\n\t\tfloat thickness;\n\t\tfloat attenuationDistance;\n\t\tvec3 attenuationColor;\n\t#endif\n};\nvec3 clearcoatSpecular = vec3( 0.0 );\nvec3 sheenSpecular = vec3( 0.0 );\nfloat IBLSheenBRDF( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat r2 = roughness * roughness;\n\tfloat a = roughness < 0.25 ? -339.2 * r2 + 161.4 * roughness - 25.9 : -8.48 * r2 + 14.3 * roughness - 9.95;\n\tfloat b = roughness < 0.25 ? 44.0 * r2 - 23.7 * roughness + 3.26 : 1.97 * r2 - 3.27 * roughness + 0.72;\n\tfloat DG = exp( a * dotNV + b ) + ( roughness < 0.25 ? 0.0 : 0.1 * ( roughness - 0.25 ) );\n\treturn saturate( DG * RECIPROCAL_PI );\n}\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\n\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\n\tvec4 r = roughness * c0 + c1;\n\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\n\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\n\treturn fab;\n}\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\treturn specularColor * fab.x + specularF90 * fab.y;\n}\n#ifdef USE_IRIDESCENCE\nvoid computeMultiscatteringIridescence( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float iridescence, const in vec3 iridescenceF0, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#else\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#endif\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\t#ifdef USE_IRIDESCENCE\n\t\tvec3 Fr = mix( specularColor, iridescenceF0, iridescence );\n\t#else\n\t\tvec3 Fr = specularColor;\n\t#endif\n\tvec3 FssEss = Fr * fab.x + specularF90 * fab.y;\n\tfloat Ess = fab.x + fab.y;\n\tfloat Ems = 1.0 - Ess;\n\tvec3 Favg = Fr + ( 1.0 - Fr ) * 0.047619;\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\n\tsingleScatter += FssEss;\n\tmultiScatter += Fms * Ems;\n}\n#if NUM_RECT_AREA_LIGHTS > 0\n\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\t\tvec3 normal = geometry.normal;\n\t\tvec3 viewDir = geometry.viewDir;\n\t\tvec3 position = geometry.position;\n\t\tvec3 lightPos = rectAreaLight.position;\n\t\tvec3 halfWidth = rectAreaLight.halfWidth;\n\t\tvec3 halfHeight = rectAreaLight.halfHeight;\n\t\tvec3 lightColor = rectAreaLight.color;\n\t\tfloat roughness = material.roughness;\n\t\tvec3 rectCoords[ 4 ];\n\t\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\t\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\n\t\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\n\t\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\n\t\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\n\t\tvec4 t1 = texture2D( ltc_1, uv );\n\t\tvec4 t2 = texture2D( ltc_2, uv );\n\t\tmat3 mInv = mat3(\n\t\t\tvec3( t1.x, 0, t1.y ),\n\t\t\tvec3( 0, 1, 0 ),\n\t\t\tvec3( t1.z, 0, t1.w )\n\t\t);\n\t\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\n\t\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\n\t\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\n\t}\n#endif\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\n\t\tvec3 ccIrradiance = dotNLcc * directLight.color;\n\t\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenColor, material.sheenRoughness );\n\t#endif\n\t#ifdef USE_IRIDESCENCE\n\t\treflectedLight.directSpecular += irradiance * BRDF_GGX_Iridescence( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnel, material.roughness );\n\t#else\n\t\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\n\t#endif\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecular += irradiance * material.sheenColor * IBLSheenBRDF( geometry.normal, geometry.viewDir, material.sheenRoughness );\n\t#endif\n\tvec3 singleScattering = vec3( 0.0 );\n\tvec3 multiScattering = vec3( 0.0 );\n\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\n\t#ifdef USE_IRIDESCENCE\n\t\tcomputeMultiscatteringIridescence( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnel, material.roughness, singleScattering, multiScattering );\n\t#else\n\t\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\n\t#endif\n\tvec3 totalScattering = singleScattering + multiScattering;\n\tvec3 diffuse = material.diffuseColor * ( 1.0 - max( max( totalScattering.r, totalScattering.g ), totalScattering.b ) );\n\treflectedLight.indirectSpecular += radiance * singleScattering;\n\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\n\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\n}\n#define RE_Direct\t\t\t\tRE_Direct_Physical\n#define RE_Direct_RectArea\t\tRE_Direct_RectArea_Physical\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Physical\n#define RE_IndirectSpecular\t\tRE_IndirectSpecular_Physical\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\n\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\n}",lights_fragment_begin:"\nGeometricContext geometry;\ngeometry.position = - vViewPosition;\ngeometry.normal = normal;\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\n#ifdef USE_CLEARCOAT\n\tgeometry.clearcoatNormal = clearcoatNormal;\n#endif\n#ifdef USE_IRIDESCENCE\n\tfloat dotNVi = saturate( dot( normal, geometry.viewDir ) );\n\tif ( material.iridescenceThickness == 0.0 ) {\n\t\tmaterial.iridescence = 0.0;\n\t} else {\n\t\tmaterial.iridescence = saturate( material.iridescence );\n\t}\n\tif ( material.iridescence > 0.0 ) {\n\t\tmaterial.iridescenceFresnel = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor );\n\t\tmaterial.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi );\n\t}\n#endif\nIncidentLight directLight;\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\n\tPointLight pointLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\n\t\tpointLight = pointLights[ i ];\n\t\tgetPointLightInfo( pointLight, geometry, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\n\t\tpointLightShadow = pointLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\n\tSpotLight spotLight;\n\tvec4 spotColor;\n\tvec3 spotLightCoord;\n\tbool inSpotLightMap;\n\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\n\t\tspotLight = spotLights[ i ];\n\t\tgetSpotLightInfo( spotLight, geometry, directLight );\n\t\t#if ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#define SPOT_LIGHT_MAP_INDEX UNROLLED_LOOP_INDEX\n\t\t#elif ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t#define SPOT_LIGHT_MAP_INDEX NUM_SPOT_LIGHT_MAPS\n\t\t#else\n\t\t#define SPOT_LIGHT_MAP_INDEX ( UNROLLED_LOOP_INDEX - NUM_SPOT_LIGHT_SHADOWS + NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#endif\n\t\t#if ( SPOT_LIGHT_MAP_INDEX < NUM_SPOT_LIGHT_MAPS )\n\t\t\tspotLightCoord = vSpotLightCoord[ i ].xyz / vSpotLightCoord[ i ].w;\n\t\t\tinSpotLightMap = all( lessThan( abs( spotLightCoord * 2. - 1. ), vec3( 1.0 ) ) );\n\t\t\tspotColor = texture2D( spotLightMap[ SPOT_LIGHT_MAP_INDEX ], spotLightCoord.xy );\n\t\t\tdirectLight.color = inSpotLightMap ? directLight.color * spotColor.rgb : directLight.color;\n\t\t#endif\n\t\t#undef SPOT_LIGHT_MAP_INDEX\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\tspotLightShadow = spotLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\n\tDirectionalLight directionalLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\n\t\tdirectionalLight = directionalLights[ i ];\n\t\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\n\t\tdirectionalLightShadow = directionalLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\n\tRectAreaLight rectAreaLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\n\t\trectAreaLight = rectAreaLights[ i ];\n\t\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if defined( RE_IndirectDiffuse )\n\tvec3 iblIrradiance = vec3( 0.0 );\n\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\n\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\n\t#if ( NUM_HEMI_LIGHTS > 0 )\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\n\t\t\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if defined( RE_IndirectSpecular )\n\tvec3 radiance = vec3( 0.0 );\n\tvec3 clearcoatRadiance = vec3( 0.0 );\n#endif",lights_fragment_maps:"#if defined( RE_IndirectDiffuse )\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\n\t\tvec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;\n\t\tirradiance += lightMapIrradiance;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\n\t\tiblIrradiance += getIBLIrradiance( geometry.normal );\n\t#endif\n#endif\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\n\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\n\t#endif\n#endif",lights_fragment_end:"#if defined( RE_IndirectDiffuse )\n\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\n#endif\n#if defined( RE_IndirectSpecular )\n\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\n#endif",logdepthbuf_fragment:"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\n\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\n#endif",logdepthbuf_pars_fragment:"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\n\tuniform float logDepthBufFC;\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif",logdepthbuf_pars_vertex:"#ifdef USE_LOGDEPTHBUF\n\t#ifdef USE_LOGDEPTHBUF_EXT\n\t\tvarying float vFragDepth;\n\t\tvarying float vIsPerspective;\n\t#else\n\t\tuniform float logDepthBufFC;\n\t#endif\n#endif",logdepthbuf_vertex:"#ifdef USE_LOGDEPTHBUF\n\t#ifdef USE_LOGDEPTHBUF_EXT\n\t\tvFragDepth = 1.0 + gl_Position.w;\n\t\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\n\t#else\n\t\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\n\t\t\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\n\t\t\tgl_Position.z *= gl_Position.w;\n\t\t}\n\t#endif\n#endif",map_fragment:"#ifdef USE_MAP\n\tvec4 sampledDiffuseColor = texture2D( map, vUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\tsampledDiffuseColor = vec4( mix( pow( sampledDiffuseColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), sampledDiffuseColor.rgb * 0.0773993808, vec3( lessThanEqual( sampledDiffuseColor.rgb, vec3( 0.04045 ) ) ) ), sampledDiffuseColor.w );\n\t#endif\n\tdiffuseColor *= sampledDiffuseColor;\n#endif",map_pars_fragment:"#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif",map_particle_fragment:"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\n#endif\n#ifdef USE_MAP\n\tdiffuseColor *= texture2D( map, uv );\n#endif\n#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\n#endif",map_particle_pars_fragment:"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\tuniform mat3 uvTransform;\n#endif\n#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif",metalnessmap_fragment:"float metalnessFactor = metalness;\n#ifdef USE_METALNESSMAP\n\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\n\tmetalnessFactor *= texelMetalness.b;\n#endif",metalnessmap_pars_fragment:"#ifdef USE_METALNESSMAP\n\tuniform sampler2D metalnessMap;\n#endif",morphcolor_vertex:"#if defined( USE_MORPHCOLORS ) && defined( MORPHTARGETS_TEXTURE )\n\tvColor *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\t#if defined( USE_COLOR_ALPHA )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ) * morphTargetInfluences[ i ];\n\t\t#elif defined( USE_COLOR )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ).rgb * morphTargetInfluences[ i ];\n\t\t#endif\n\t}\n#endif",morphnormal_vertex:"#ifdef USE_MORPHNORMALS\n\tobjectNormal *= morphTargetBaseInfluence;\n\t#ifdef MORPHTARGETS_TEXTURE\n\t\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1 ).xyz * morphTargetInfluences[ i ];\n\t\t}\n\t#else\n\t\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\n\t\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\n\t\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\n\t\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\n\t#endif\n#endif",morphtarget_pars_vertex:"#ifdef USE_MORPHTARGETS\n\tuniform float morphTargetBaseInfluence;\n\t#ifdef MORPHTARGETS_TEXTURE\n\t\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\t\tuniform sampler2DArray morphTargetsTexture;\n\t\tuniform ivec2 morphTargetsTextureSize;\n\t\tvec4 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset ) {\n\t\t\tint texelIndex = vertexIndex * MORPHTARGETS_TEXTURE_STRIDE + offset;\n\t\t\tint y = texelIndex / morphTargetsTextureSize.x;\n\t\t\tint x = texelIndex - y * morphTargetsTextureSize.x;\n\t\t\tivec3 morphUV = ivec3( x, y, morphTargetIndex );\n\t\t\treturn texelFetch( morphTargetsTexture, morphUV, 0 );\n\t\t}\n\t#else\n\t\t#ifndef USE_MORPHNORMALS\n\t\t\tuniform float morphTargetInfluences[ 8 ];\n\t\t#else\n\t\t\tuniform float morphTargetInfluences[ 4 ];\n\t\t#endif\n\t#endif\n#endif",morphtarget_vertex:"#ifdef USE_MORPHTARGETS\n\ttransformed *= morphTargetBaseInfluence;\n\t#ifdef MORPHTARGETS_TEXTURE\n\t\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) transformed += getMorph( gl_VertexID, i, 0 ).xyz * morphTargetInfluences[ i ];\n\t\t}\n\t#else\n\t\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\n\t\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\n\t\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\n\t\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\n\t\t#ifndef USE_MORPHNORMALS\n\t\t\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\n\t\t\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\n\t\t\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\n\t\t\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\n\t\t#endif\n\t#endif\n#endif",normal_fragment_begin:"float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\n#ifdef FLAT_SHADED\n\tvec3 fdx = dFdx( vViewPosition );\n\tvec3 fdy = dFdy( vViewPosition );\n\tvec3 normal = normalize( cross( fdx, fdy ) );\n#else\n\tvec3 normal = normalize( vNormal );\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\t#ifdef USE_TANGENT\n\t\tvec3 tangent = normalize( vTangent );\n\t\tvec3 bitangent = normalize( vBitangent );\n\t\t#ifdef DOUBLE_SIDED\n\t\t\ttangent = tangent * faceDirection;\n\t\t\tbitangent = bitangent * faceDirection;\n\t\t#endif\n\t\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\n\t\t\tmat3 vTBN = mat3( tangent, bitangent, normal );\n\t\t#endif\n\t#endif\n#endif\nvec3 geometryNormal = normal;",normal_fragment_maps:"#ifdef OBJECTSPACE_NORMALMAP\n\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\n\t#ifdef FLIP_SIDED\n\t\tnormal = - normal;\n\t#endif\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\tnormal = normalize( normalMatrix * normal );\n#elif defined( TANGENTSPACE_NORMALMAP )\n\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\n\tmapN.xy *= normalScale;\n\t#ifdef USE_TANGENT\n\t\tnormal = normalize( vTBN * mapN );\n\t#else\n\t\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\n\t#endif\n#elif defined( USE_BUMPMAP )\n\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\n#endif",normal_pars_fragment:"#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif",normal_pars_vertex:"#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif",normal_vertex:"#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n\t#ifdef USE_TANGENT\n\t\tvTangent = normalize( transformedTangent );\n\t\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\n\t#endif\n#endif",normalmap_pars_fragment:"#ifdef USE_NORMALMAP\n\tuniform sampler2D normalMap;\n\tuniform vec2 normalScale;\n#endif\n#ifdef OBJECTSPACE_NORMALMAP\n\tuniform mat3 normalMatrix;\n#endif\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\n\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\n\t\tvec3 q0 = dFdx( eye_pos.xyz );\n\t\tvec3 q1 = dFdy( eye_pos.xyz );\n\t\tvec2 st0 = dFdx( vUv.st );\n\t\tvec2 st1 = dFdy( vUv.st );\n\t\tvec3 N = surf_norm;\n\t\tvec3 q1perp = cross( q1, N );\n\t\tvec3 q0perp = cross( N, q0 );\n\t\tvec3 T = q1perp * st0.x + q0perp * st1.x;\n\t\tvec3 B = q1perp * st0.y + q0perp * st1.y;\n\t\tfloat det = max( dot( T, T ), dot( B, B ) );\n\t\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\n\t\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\n\t}\n#endif",clearcoat_normal_fragment_begin:"#ifdef USE_CLEARCOAT\n\tvec3 clearcoatNormal = geometryNormal;\n#endif",clearcoat_normal_fragment_maps:"#ifdef USE_CLEARCOAT_NORMALMAP\n\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\n\tclearcoatMapN.xy *= clearcoatNormalScale;\n\t#ifdef USE_TANGENT\n\t\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\n\t#else\n\t\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\n\t#endif\n#endif",clearcoat_pars_fragment:"#ifdef USE_CLEARCOATMAP\n\tuniform sampler2D clearcoatMap;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform sampler2D clearcoatRoughnessMap;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform sampler2D clearcoatNormalMap;\n\tuniform vec2 clearcoatNormalScale;\n#endif",iridescence_pars_fragment:"#ifdef USE_IRIDESCENCEMAP\n\tuniform sampler2D iridescenceMap;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform sampler2D iridescenceThicknessMap;\n#endif",output_fragment:"#ifdef OPAQUE\ndiffuseColor.a = 1.0;\n#endif\n#ifdef USE_TRANSMISSION\ndiffuseColor.a *= material.transmissionAlpha + 0.1;\n#endif\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );",packing:"vec3 packNormalToRGB( const in vec3 normal ) {\n\treturn normalize( normal ) * 0.5 + 0.5;\n}\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\n\treturn 2.0 * rgb.xyz - 1.0;\n}\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\nconst float ShiftRight8 = 1. / 256.;\nvec4 packDepthToRGBA( const in float v ) {\n\tvec4 r = vec4( fract( v * PackFactors ), v );\n\tr.yzw -= r.xyz * ShiftRight8;\treturn r * PackUpscale;\n}\nfloat unpackRGBAToDepth( const in vec4 v ) {\n\treturn dot( v, UnpackFactors );\n}\nvec2 packDepthToRG( in highp float v ) {\n\treturn packDepthToRGBA( v ).yx;\n}\nfloat unpackRGToDepth( const in highp vec2 v ) {\n\treturn unpackRGBAToDepth( vec4( v.xy, 0.0, 0.0 ) );\n}\nvec4 pack2HalfToRGBA( vec2 v ) {\n\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\n\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\n}\nvec2 unpackRGBATo2Half( vec4 v ) {\n\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\n}\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( viewZ + near ) / ( near - far );\n}\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\n\treturn linearClipZ * ( near - far ) - near;\n}\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\n}\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\n\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\n}",premultiplied_alpha_fragment:"#ifdef PREMULTIPLIED_ALPHA\n\tgl_FragColor.rgb *= gl_FragColor.a;\n#endif",project_vertex:"vec4 mvPosition = vec4( transformed, 1.0 );\n#ifdef USE_INSTANCING\n\tmvPosition = instanceMatrix * mvPosition;\n#endif\nmvPosition = modelViewMatrix * mvPosition;\ngl_Position = projectionMatrix * mvPosition;",dithering_fragment:"#ifdef DITHERING\n\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\n#endif",dithering_pars_fragment:"#ifdef DITHERING\n\tvec3 dithering( vec3 color ) {\n\t\tfloat grid_position = rand( gl_FragCoord.xy );\n\t\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\n\t\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\n\t\treturn color + dither_shift_RGB;\n\t}\n#endif",roughnessmap_fragment:"float roughnessFactor = roughness;\n#ifdef USE_ROUGHNESSMAP\n\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\n\troughnessFactor *= texelRoughness.g;\n#endif",roughnessmap_pars_fragment:"#ifdef USE_ROUGHNESSMAP\n\tuniform sampler2D roughnessMap;\n#endif",shadowmap_pars_fragment:"#if NUM_SPOT_LIGHT_COORDS > 0\n varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#if NUM_SPOT_LIGHT_MAPS > 0\n uniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\n\t\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\n\t}\n\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\n\t\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\n\t}\n\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\n\t\tfloat occlusion = 1.0;\n\t\tvec2 distribution = texture2DDistribution( shadow, uv );\n\t\tfloat hard_shadow = step( compare , distribution.x );\n\t\tif (hard_shadow != 1.0 ) {\n\t\t\tfloat distance = compare - distribution.x ;\n\t\t\tfloat variance = max( 0.00000, distribution.y * distribution.y );\n\t\t\tfloat softness_probability = variance / (variance + distance * distance );\t\t\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\t\t\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\n\t\t}\n\t\treturn occlusion;\n\t}\n\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\n\t\tfloat shadow = 1.0;\n\t\tshadowCoord.xyz /= shadowCoord.w;\n\t\tshadowCoord.z += shadowBias;\n\t\tbool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;\n\t\tbool frustumTest = inFrustum && shadowCoord.z <= 1.0;\n\t\tif ( frustumTest ) {\n\t\t#if defined( SHADOWMAP_TYPE_PCF )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx0 = - texelSize.x * shadowRadius;\n\t\t\tfloat dy0 = - texelSize.y * shadowRadius;\n\t\t\tfloat dx1 = + texelSize.x * shadowRadius;\n\t\t\tfloat dy1 = + texelSize.y * shadowRadius;\n\t\t\tfloat dx2 = dx0 / 2.0;\n\t\t\tfloat dy2 = dy0 / 2.0;\n\t\t\tfloat dx3 = dx1 / 2.0;\n\t\t\tfloat dy3 = dy1 / 2.0;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\n\t\t\t) * ( 1.0 / 17.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx = texelSize.x;\n\t\t\tfloat dy = texelSize.y;\n\t\t\tvec2 uv = shadowCoord.xy;\n\t\t\tvec2 f = fract( uv * shadowMapSize + 0.5 );\n\t\t\tuv -= f * texelSize;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t f.x ),\n\t\t\t\t\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t f.x ),\n\t\t\t\t\t f.y )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_VSM )\n\t\t\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#else\n\t\t\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#endif\n\t\t}\n\t\treturn shadow;\n\t}\n\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\n\t\tvec3 absV = abs( v );\n\t\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\n\t\tabsV *= scaleToCube;\n\t\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\n\t\tvec2 planar = v.xy;\n\t\tfloat almostATexel = 1.5 * texelSizeY;\n\t\tfloat almostOne = 1.0 - almostATexel;\n\t\tif ( absV.z >= almostOne ) {\n\t\t\tif ( v.z > 0.0 )\n\t\t\t\tplanar.x = 4.0 - v.x;\n\t\t} else if ( absV.x >= almostOne ) {\n\t\t\tfloat signX = sign( v.x );\n\t\t\tplanar.x = v.z * signX + 2.0 * signX;\n\t\t} else if ( absV.y >= almostOne ) {\n\t\t\tfloat signY = sign( v.y );\n\t\t\tplanar.x = v.x + 2.0 * signY + 2.0;\n\t\t\tplanar.y = v.z * signY - 2.0;\n\t\t}\n\t\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\n\t}\n\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\n\t\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\n\t\tvec3 lightToPosition = shadowCoord.xyz;\n\t\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\t\tdp += shadowBias;\n\t\tvec3 bd3D = normalize( lightToPosition );\n\t\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\n\t\t\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\n\t\t\treturn (\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#else\n\t\t\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\n\t\t#endif\n\t}\n#endif",shadowmap_pars_vertex:"#if NUM_SPOT_LIGHT_COORDS > 0\n uniform mat4 spotLightMatrix[ NUM_SPOT_LIGHT_COORDS ];\n varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n#endif",shadowmap_vertex:"#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 )\n\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\tvec4 shadowWorldPosition;\n#endif\n#if defined( USE_SHADOWMAP )\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if NUM_SPOT_LIGHT_COORDS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_COORDS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition;\n\t\t#if ( defined( USE_SHADOWMAP ) && UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t\tshadowWorldPosition.xyz += shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias;\n\t\t#endif\n\t\tvSpotLightCoord[ i ] = spotLightMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n#endif",shadowmask_pars_fragment:"float getShadowMask() {\n\tfloat shadow = 1.0;\n\t#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\tdirectionalLight = directionalLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\n\t\tspotLight = spotLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\tpointLight = pointLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#endif\n\treturn shadow;\n}",skinbase_vertex:"#ifdef USE_SKINNING\n\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\n\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\n\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\n\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\n#endif",skinning_pars_vertex:"#ifdef USE_SKINNING\n\tuniform mat4 bindMatrix;\n\tuniform mat4 bindMatrixInverse;\n\tuniform highp sampler2D boneTexture;\n\tuniform int boneTextureSize;\n\tmat4 getBoneMatrix( const in float i ) {\n\t\tfloat j = i * 4.0;\n\t\tfloat x = mod( j, float( boneTextureSize ) );\n\t\tfloat y = floor( j / float( boneTextureSize ) );\n\t\tfloat dx = 1.0 / float( boneTextureSize );\n\t\tfloat dy = 1.0 / float( boneTextureSize );\n\t\ty = dy * ( y + 0.5 );\n\t\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\n\t\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\n\t\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\n\t\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\n\t\tmat4 bone = mat4( v1, v2, v3, v4 );\n\t\treturn bone;\n\t}\n#endif",skinning_vertex:"#ifdef USE_SKINNING\n\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\n\tvec4 skinned = vec4( 0.0 );\n\tskinned += boneMatX * skinVertex * skinWeight.x;\n\tskinned += boneMatY * skinVertex * skinWeight.y;\n\tskinned += boneMatZ * skinVertex * skinWeight.z;\n\tskinned += boneMatW * skinVertex * skinWeight.w;\n\ttransformed = ( bindMatrixInverse * skinned ).xyz;\n#endif",skinnormal_vertex:"#ifdef USE_SKINNING\n\tmat4 skinMatrix = mat4( 0.0 );\n\tskinMatrix += skinWeight.x * boneMatX;\n\tskinMatrix += skinWeight.y * boneMatY;\n\tskinMatrix += skinWeight.z * boneMatZ;\n\tskinMatrix += skinWeight.w * boneMatW;\n\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\n\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\n\t#ifdef USE_TANGENT\n\t\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#endif\n#endif",specularmap_fragment:"float specularStrength;\n#ifdef USE_SPECULARMAP\n\tvec4 texelSpecular = texture2D( specularMap, vUv );\n\tspecularStrength = texelSpecular.r;\n#else\n\tspecularStrength = 1.0;\n#endif",specularmap_pars_fragment:"#ifdef USE_SPECULARMAP\n\tuniform sampler2D specularMap;\n#endif",tonemapping_fragment:"#if defined( TONE_MAPPING )\n\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\n#endif",tonemapping_pars_fragment:"#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\nuniform float toneMappingExposure;\nvec3 LinearToneMapping( vec3 color ) {\n\treturn toneMappingExposure * color;\n}\nvec3 ReinhardToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\treturn saturate( color / ( vec3( 1.0 ) + color ) );\n}\nvec3 OptimizedCineonToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\tcolor = max( vec3( 0.0 ), color - 0.004 );\n\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\n}\nvec3 RRTAndODTFit( vec3 v ) {\n\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\n\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\n\treturn a / b;\n}\nvec3 ACESFilmicToneMapping( vec3 color ) {\n\tconst mat3 ACESInputMat = mat3(\n\t\tvec3( 0.59719, 0.07600, 0.02840 ),\t\tvec3( 0.35458, 0.90834, 0.13383 ),\n\t\tvec3( 0.04823, 0.01566, 0.83777 )\n\t);\n\tconst mat3 ACESOutputMat = mat3(\n\t\tvec3( 1.60475, -0.10208, -0.00327 ),\t\tvec3( -0.53108, 1.10813, -0.07276 ),\n\t\tvec3( -0.07367, -0.00605, 1.07602 )\n\t);\n\tcolor *= toneMappingExposure / 0.6;\n\tcolor = ACESInputMat * color;\n\tcolor = RRTAndODTFit( color );\n\tcolor = ACESOutputMat * color;\n\treturn saturate( color );\n}\nvec3 CustomToneMapping( vec3 color ) { return color; }",transmission_fragment:"#ifdef USE_TRANSMISSION\n\tmaterial.transmission = transmission;\n\tmaterial.transmissionAlpha = 1.0;\n\tmaterial.thickness = thickness;\n\tmaterial.attenuationDistance = attenuationDistance;\n\tmaterial.attenuationColor = attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tmaterial.transmission *= texture2D( transmissionMap, vUv ).r;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tmaterial.thickness *= texture2D( thicknessMap, vUv ).g;\n\t#endif\n\tvec3 pos = vWorldPosition;\n\tvec3 v = normalize( cameraPosition - pos );\n\tvec3 n = inverseTransformDirection( normal, viewMatrix );\n\tvec4 transmission = getIBLVolumeRefraction(\n\t\tn, v, material.roughness, material.diffuseColor, material.specularColor, material.specularF90,\n\t\tpos, modelMatrix, viewMatrix, projectionMatrix, material.ior, material.thickness,\n\t\tmaterial.attenuationColor, material.attenuationDistance );\n\tmaterial.transmissionAlpha = mix( material.transmissionAlpha, transmission.a, material.transmission );\n\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, material.transmission );\n#endif",transmission_pars_fragment:"#ifdef USE_TRANSMISSION\n\tuniform float transmission;\n\tuniform float thickness;\n\tuniform float attenuationDistance;\n\tuniform vec3 attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tuniform sampler2D transmissionMap;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tuniform sampler2D thicknessMap;\n\t#endif\n\tuniform vec2 transmissionSamplerSize;\n\tuniform sampler2D transmissionSamplerMap;\n\tuniform mat4 modelMatrix;\n\tuniform mat4 projectionMatrix;\n\tvarying vec3 vWorldPosition;\n\tvec3 getVolumeTransmissionRay( const in vec3 n, const in vec3 v, const in float thickness, const in float ior, const in mat4 modelMatrix ) {\n\t\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\n\t\tvec3 modelScale;\n\t\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\n\t\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\n\t\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\n\t\treturn normalize( refractionVector ) * thickness * modelScale;\n\t}\n\tfloat applyIorToRoughness( const in float roughness, const in float ior ) {\n\t\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\n\t}\n\tvec4 getTransmissionSample( const in vec2 fragCoord, const in float roughness, const in float ior ) {\n\t\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\n\t\t#ifdef texture2DLodEXT\n\t\t\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\n\t\t#else\n\t\t\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\n\t\t#endif\n\t}\n\tvec3 applyVolumeAttenuation( const in vec3 radiance, const in float transmissionDistance, const in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tif ( isinf( attenuationDistance ) ) {\n\t\t\treturn radiance;\n\t\t} else {\n\t\t\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\n\t\t\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );\t\t\treturn transmittance * radiance;\n\t\t}\n\t}\n\tvec4 getIBLVolumeRefraction( const in vec3 n, const in vec3 v, const in float roughness, const in vec3 diffuseColor,\n\t\tconst in vec3 specularColor, const in float specularF90, const in vec3 position, const in mat4 modelMatrix,\n\t\tconst in mat4 viewMatrix, const in mat4 projMatrix, const in float ior, const in float thickness,\n\t\tconst in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\n\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\trefractionCoords += 1.0;\n\t\trefractionCoords /= 2.0;\n\t\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\n\t\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\n\t\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\n\t\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\n\t}\n#endif",uv_pars_fragment:"#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\n\tvarying vec2 vUv;\n#endif",uv_pars_vertex:"#ifdef USE_UV\n\t#ifdef UVS_VERTEX_ONLY\n\t\tvec2 vUv;\n\t#else\n\t\tvarying vec2 vUv;\n\t#endif\n\tuniform mat3 uvTransform;\n#endif",uv_vertex:"#ifdef USE_UV\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n#endif",uv2_pars_fragment:"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\n\tvarying vec2 vUv2;\n#endif",uv2_pars_vertex:"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\n\tattribute vec2 uv2;\n\tvarying vec2 vUv2;\n\tuniform mat3 uv2Transform;\n#endif",uv2_vertex:"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\n\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\n#endif",worldpos_vertex:"#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION ) || NUM_SPOT_LIGHT_COORDS > 0\n\tvec4 worldPosition = vec4( transformed, 1.0 );\n\t#ifdef USE_INSTANCING\n\t\tworldPosition = instanceMatrix * worldPosition;\n\t#endif\n\tworldPosition = modelMatrix * worldPosition;\n#endif",background_vert:"varying vec2 vUv;\nuniform mat3 uvTransform;\nvoid main() {\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\tgl_Position = vec4( position.xy, 1.0, 1.0 );\n}",background_frag:"uniform sampler2D t2D;\nuniform float backgroundIntensity;\nvarying vec2 vUv;\nvoid main() {\n\tvec4 texColor = texture2D( t2D, vUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\ttexColor = vec4( mix( pow( texColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), texColor.rgb * 0.0773993808, vec3( lessThanEqual( texColor.rgb, vec3( 0.04045 ) ) ) ), texColor.w );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include \n\t#include \n}",backgroundCube_vert:"varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n\tgl_Position.z = gl_Position.w;\n}",backgroundCube_frag:"#ifdef ENVMAP_TYPE_CUBE\n\tuniform samplerCube envMap;\n#elif defined( ENVMAP_TYPE_CUBE_UV )\n\tuniform sampler2D envMap;\n#endif\nuniform float flipEnvMap;\nuniform float backgroundBlurriness;\nuniform float backgroundIntensity;\nvarying vec3 vWorldDirection;\n#include \nvoid main() {\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 texColor = textureCube( envMap, vec3( flipEnvMap * vWorldDirection.x, vWorldDirection.yz ) );\n\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\tvec4 texColor = textureCubeUV( envMap, vWorldDirection, backgroundBlurriness );\n\t#else\n\t\tvec4 texColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include \n\t#include \n}",cube_vert:"varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n\tgl_Position.z = gl_Position.w;\n}",cube_frag:"uniform samplerCube tCube;\nuniform float tFlip;\nuniform float opacity;\nvarying vec3 vWorldDirection;\nvoid main() {\n\tvec4 texColor = textureCube( tCube, vec3( tFlip * vWorldDirection.x, vWorldDirection.yz ) );\n\tgl_FragColor = texColor;\n\tgl_FragColor.a *= opacity;\n\t#include \n\t#include \n}",depth_vert:"#include \n#include \n#include \n#include \n#include \n#include \n#include \nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include \n\t#include \n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include \n\t\t#include \n\t\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvHighPrecisionZW = gl_Position.zw;\n}",depth_frag:"#if DEPTH_PACKING == 3200\n\tuniform float opacity;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( 1.0 );\n\t#if DEPTH_PACKING == 3200\n\t\tdiffuseColor.a = opacity;\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\n\t#if DEPTH_PACKING == 3200\n\t\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\n\t#elif DEPTH_PACKING == 3201\n\t\tgl_FragColor = packDepthToRGBA( fragCoordZ );\n\t#endif\n}",distanceRGBA_vert:"#define DISTANCE\nvarying vec3 vWorldPosition;\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include
- 
- 
- 
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- 
- - diff --git a/spaces/AIConsultant/MusicGen/tests/models/test_multibanddiffusion.py b/spaces/AIConsultant/MusicGen/tests/models/test_multibanddiffusion.py deleted file mode 100644 index 2702a3cb5fe402bf96911dbc992d2749cb18a4c0..0000000000000000000000000000000000000000 --- a/spaces/AIConsultant/MusicGen/tests/models/test_multibanddiffusion.py +++ /dev/null @@ -1,53 +0,0 @@ -# Copyright (c) Meta Platforms, Inc. and affiliates. -# All rights reserved. -# -# This source code is licensed under the license found in the -# LICENSE file in the root directory of this source tree. - -import random - -import numpy as np -import torch -from audiocraft.models.multibanddiffusion import MultiBandDiffusion, DiffusionProcess -from audiocraft.models import EncodecModel, DiffusionUnet -from audiocraft.modules import SEANetEncoder, SEANetDecoder -from audiocraft.modules.diffusion_schedule import NoiseSchedule -from audiocraft.quantization import DummyQuantizer - - -class TestMBD: - - def _create_mbd(self, - sample_rate: int, - channels: int, - n_filters: int = 3, - n_residual_layers: int = 1, - ratios: list = [5, 4, 3, 2], - num_steps: int = 1000, - codec_dim: int = 128, - **kwargs): - frame_rate = np.prod(ratios) - encoder = SEANetEncoder(channels=channels, dimension=codec_dim, n_filters=n_filters, - n_residual_layers=n_residual_layers, ratios=ratios) - decoder = SEANetDecoder(channels=channels, dimension=codec_dim, n_filters=n_filters, - n_residual_layers=n_residual_layers, ratios=ratios) - quantizer = DummyQuantizer() - compression_model = EncodecModel(encoder, decoder, quantizer, frame_rate=frame_rate, - sample_rate=sample_rate, channels=channels, **kwargs) - diffusion_model = DiffusionUnet(chin=channels, num_steps=num_steps, codec_dim=codec_dim) - schedule = NoiseSchedule(device='cpu', num_steps=num_steps) - DP = DiffusionProcess(model=diffusion_model, noise_schedule=schedule) - mbd = MultiBandDiffusion(DPs=[DP], codec_model=compression_model) - return mbd - - def test_model(self): - random.seed(1234) - sample_rate = 24_000 - channels = 1 - codec_dim = 128 - mbd = self._create_mbd(sample_rate=sample_rate, channels=channels, codec_dim=codec_dim) - for _ in range(10): - length = random.randrange(1, 10_000) - x = torch.randn(2, channels, length) - res = mbd.regenerate(x, sample_rate) - assert res.shape == x.shape diff --git a/spaces/AIGText/GlyphControl/ldm/util.py b/spaces/AIGText/GlyphControl/ldm/util.py deleted file mode 100644 index 2abc0791d7e60d3fbc05ff006385abfc6d534fea..0000000000000000000000000000000000000000 --- a/spaces/AIGText/GlyphControl/ldm/util.py +++ /dev/null @@ -1,203 +0,0 @@ -import importlib - -import torch -from torch import optim -import numpy as np - -from inspect import isfunction -from PIL import Image, ImageDraw, ImageFont - - -def log_txt_as_img(wh, xc, size=10): - # wh a tuple of (width, height) - # xc a list of captions to plot - b = len(xc) - txts = list() - for bi in range(b): - txt = Image.new("RGB", wh, color="white") - draw = ImageDraw.Draw(txt) - font = ImageFont.truetype('data/DejaVuSans.ttf', size=size) - nc = int(40 * (wh[0] / 256)) - lines = "\n".join(xc[bi][start:start + nc] for start in range(0, len(xc[bi]), nc)) - - try: - draw.text((0, 0), lines, fill="black", font=font) - except UnicodeEncodeError: - print("Cant encode string for logging. Skipping.") - - txt = np.array(txt).transpose(2, 0, 1) / 127.5 - 1.0 - txts.append(txt) - txts = np.stack(txts) - txts = torch.tensor(txts) - return txts - - -def ismap(x): - if not isinstance(x, torch.Tensor): - return False - return (len(x.shape) == 4) and (x.shape[1] > 3) - - -def isimage(x): - if not isinstance(x,torch.Tensor): - return False - return (len(x.shape) == 4) and (x.shape[1] == 3 or x.shape[1] == 1) - - -def exists(x): - return x is not None - - -def default(val, d): - if exists(val): - return val - return d() if isfunction(d) else d - - -def mean_flat(tensor): - """ - https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/nn.py#L86 - Take the mean over all non-batch dimensions. - """ - return tensor.mean(dim=list(range(1, len(tensor.shape)))) - - -def count_params(model, verbose=False): - total_params = sum(p.numel() for p in model.parameters()) - if verbose: - print(f"{model.__class__.__name__} has {total_params*1.e-6:.2f} M params.") - return total_params - - -def instantiate_from_config(config): - if not "target" in config: - if config == '__is_first_stage__': - return None - elif config == "__is_unconditional__": - return None - raise KeyError("Expected key `target` to instantiate.") - return get_obj_from_str(config["target"])(**config.get("params", dict())) - - -def get_obj_from_str(string, reload=False): - module, cls = string.rsplit(".", 1) - if reload: - module_imp = importlib.import_module(module) - importlib.reload(module_imp) - return getattr(importlib.import_module(module, package=None), cls) - - -class AdamWwithEMAandWings(optim.Optimizer): - # credit to https://gist.github.com/crowsonkb/65f7265353f403714fce3b2595e0b298 - def __init__(self, params, lr=1.e-3, betas=(0.9, 0.999), eps=1.e-8, # TODO: check hyperparameters before using - weight_decay=1.e-2, amsgrad=False, ema_decay=0.9999, # ema decay to match previous code - ema_power=1., param_names=()): - """AdamW that saves EMA versions of the parameters.""" - if not 0.0 <= lr: - raise ValueError("Invalid learning rate: {}".format(lr)) - if not 0.0 <= eps: - raise ValueError("Invalid epsilon value: {}".format(eps)) - if not 0.0 <= betas[0] < 1.0: - raise ValueError("Invalid beta parameter at index 0: {}".format(betas[0])) - if not 0.0 <= betas[1] < 1.0: - raise ValueError("Invalid beta parameter at index 1: {}".format(betas[1])) - if not 0.0 <= weight_decay: - raise ValueError("Invalid weight_decay value: {}".format(weight_decay)) - if not 0.0 <= ema_decay <= 1.0: - raise ValueError("Invalid ema_decay value: {}".format(ema_decay)) - defaults = dict(lr=lr, betas=betas, eps=eps, - weight_decay=weight_decay, amsgrad=amsgrad, ema_decay=ema_decay, - ema_power=ema_power, param_names=param_names) - super().__init__(params, defaults) - - def __setstate__(self, state): - super().__setstate__(state) - for group in self.param_groups: - group.setdefault('amsgrad', False) - - @torch.no_grad() - def step(self, closure=None): - """Performs a single optimization step. - Args: - closure (callable, optional): A closure that reevaluates the model - and returns the loss. - """ - loss = None - if closure is not None: - with torch.enable_grad(): - loss = closure() - - for group in self.param_groups: - params_with_grad = [] - grads = [] - exp_avgs = [] - exp_avg_sqs = [] - ema_params_with_grad = [] - state_sums = [] - max_exp_avg_sqs = [] - state_steps = [] - amsgrad = group['amsgrad'] - beta1, beta2 = group['betas'] - ema_decay = group['ema_decay'] - ema_power = group['ema_power'] - - for p in group['params']: - if p.grad is None: - continue - params_with_grad.append(p) - if p.grad.is_sparse: - raise RuntimeError('AdamW does not support sparse gradients') - grads.append(p.grad) - - state = self.state[p] - - # State initialization - if len(state) == 0: - state['step'] = 0 - # Exponential moving average of gradient values - state['exp_avg'] = torch.zeros_like(p, memory_format=torch.preserve_format) - # Exponential moving average of squared gradient values - state['exp_avg_sq'] = torch.zeros_like(p, memory_format=torch.preserve_format) - if amsgrad: - # Maintains max of all exp. moving avg. of sq. grad. values - state['max_exp_avg_sq'] = torch.zeros_like(p, memory_format=torch.preserve_format) - # Exponential moving average of parameter values - state['param_exp_avg'] = p.detach().float().clone() - - exp_avgs.append(state['exp_avg']) - exp_avg_sqs.append(state['exp_avg_sq']) - ema_params_with_grad.append(state['param_exp_avg']) - - if amsgrad: - max_exp_avg_sqs.append(state['max_exp_avg_sq']) - - # update the steps for each param group update - state['step'] += 1 - # record the step after step update - state_steps.append(state['step']) - - optim._functional.adamw(params_with_grad, - grads, - exp_avgs, - exp_avg_sqs, - max_exp_avg_sqs, - state_steps, - amsgrad=amsgrad, - beta1=beta1, - beta2=beta2, - lr=group['lr'], - weight_decay=group['weight_decay'], - eps=group['eps'], - maximize=False) - - cur_ema_decay = min(ema_decay, 1 - state['step'] ** -ema_power) - for param, ema_param in zip(params_with_grad, ema_params_with_grad): - ema_param.mul_(cur_ema_decay).add_(param.float(), alpha=1 - cur_ema_decay) - - return loss - -def islistortuple(item): - if isinstance(item, list) or isinstance(item, tuple): - return True - else: - return False \ No newline at end of file diff --git a/spaces/AILab-CVC/EvalCrafter/README.md b/spaces/AILab-CVC/EvalCrafter/README.md deleted file mode 100644 index 02a3a516af49e9dc413a23442df4e5e577c7f726..0000000000000000000000000000000000000000 --- a/spaces/AILab-CVC/EvalCrafter/README.md +++ /dev/null @@ -1,12 +0,0 @@ ---- -title: EvalCrafter -emoji: ⚡ -colorFrom: yellow -colorTo: gray -sdk: gradio -sdk_version: 3.27.0 -app_file: app.py -pinned: false ---- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference diff --git a/spaces/AISuperheroes/07GR-NLP-Seq2Seq-AutoQA/app.py b/spaces/AISuperheroes/07GR-NLP-Seq2Seq-AutoQA/app.py deleted file mode 100644 index c1cd92499cf1c7d2a91b4dc226bf2d558ff67661..0000000000000000000000000000000000000000 --- a/spaces/AISuperheroes/07GR-NLP-Seq2Seq-AutoQA/app.py +++ /dev/null @@ -1,51 +0,0 @@ -import gradio as gr -from qasrl_model_pipeline import QASRL_Pipeline - -models = ["kleinay/qanom-seq2seq-model-baseline", - "kleinay/qanom-seq2seq-model-joint"] -pipelines = {model: QASRL_Pipeline(model) for model in models} - - -description = f"""Using Seq2Seq T5 model which takes a sequence of items and outputs another sequence this model generates Questions and Answers (QA) with focus on Semantic Role Labeling (SRL)""" -title="Seq2Seq T5 Questions and Answers (QA) with Semantic Role Labeling (SRL)" -examples = [[models[0], "In March and April the patient
ChatGPT Academic Optimization
-
-**Если вам понравился этот проект, пожалуйста, поставьте ему звезду. Если вы придумали более полезные академические ярлыки или функциональные плагины, не стесняйтесь создавать запросы на изменение или пул-запросы. Мы также имеем [README на английском языке](docs/README_EN.md), переведенный этим же проектом.
-
-> **Примечание**
->
-> 1. Пожалуйста, обратите внимание, что только функциonal plugins (buttons) с **красным цветом** могут читать файлы, некоторые из которых находятся в **выпадающем меню** плагинов. Кроме того, мы приветствуем и обрабатываем любые новые плагины с **наивысшим приоритетом**!
->
-> 2. Функции каждого файла в этом проекте подробно описаны в собственном анализе [`self_analysis.md`](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A) . При повторных итерациях вы также можете вызывать обновленный отчет функций проекта, щелкнув соответствующий функциональный плагин GPT. Часто задаваемые вопросы собраны в [`wiki`](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98) .
-
-- -Функция | Описание ---- | --- -Редактирование одним кликом | Поддержка редактирования одним кликом, поиск грамматических ошибок в академических статьях -Переключение языков "Английский-Китайский" одним кликом | Одним кликом переключайте языки "Английский-Китайский" -Разъяснение программного кода одним кликом | Вы можете правильно отобразить и объяснить программный код. -[Настраиваемые сочетания клавиш](https://www.bilibili.com/video/BV14s4y1E7jN) | Поддержка настраиваемых сочетаний клавиш -[Настройка сервера-прокси](https://www.bilibili.com/video/BV1rc411W7Dr) | Поддержка настройки сервера-прокси -Модульный дизайн | Поддержка настраиваемых функциональных плагинов высших порядков и функциональных плагинов, поддерживающих [горячее обновление](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97) -[Автоанализ программы](https://www.bilibili.com/video/BV1cj411A7VW) | [Функциональный плагин] [Прочтение в один клик](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A) кода программы проекта -[Анализ программы](https://www.bilibili.com/video/BV1cj411A7VW) | [Функциональный плагин] Один клик для проанализирования дерева других проектов Python/C/C++/Java/Lua/... -Чтение статей| [Функциональный плагин] Одним кликом прочитайте весь латех (LaTex) текст статьи и сгенерируйте краткое описание -Перевод и редактирование всех статей из LaTex | [Функциональный плагин] Перевод или редактирование LaTex-статьи всего одним нажатием кнопки -Генерация комментариев в пакетном режиме | [Функциональный плагин] Одним кликом сгенерируйте комментарии к функциям в пакетном режиме -Генерация отчетов пакета CHAT | [Функциональный плагин] Автоматически создавайте сводные отчеты после выполнения -[Помощник по arxiv](https://www.bilibili.com/video/BV1LM4y1279X) | [Функциональный плагин] Введите URL статьи arxiv, чтобы легко перевести резюме и загрузить PDF-файл -[Перевод полного текста статьи в формате PDF](https://www.bilibili.com/video/BV1KT411x7Wn) | [Функциональный плагин] Извлеките заголовок статьи, резюме и переведите весь текст статьи (многопоточно) -[Помощник интеграции Google Scholar](https://www.bilibili.com/video/BV19L411U7ia) | [Функциональный плагин] Дайте GPT выбрать для вас интересные статьи на любой странице поиска Google Scholar. -Отображение формул/изображений/таблиц | Одновременно отображается tex-форма и рендер-форма формул, поддержка формул, высокоскоростных кодов -Поддержка функциональных плагинов многопоточности | Поддержка многопоточной работы с плагинами, обрабатывайте огромные объемы текста или программы одним кликом -Запуск темной темы gradio[подробнее](https://github.com/binary-husky/chatgpt_academic/issues/173) | Добавьте / ?__dark-theme=true в конец URL браузера, чтобы переключиться на темную тему. -[Поддержка нескольких моделей LLM](https://www.bilibili.com/video/BV1wT411p7yf), поддержка API2D | Находиться между GPT3.5, GPT4 и [清华ChatGLM](https://github.com/THUDM/ChatGLM-6B) должно быть очень приятно, не так ли? -Альтернатива huggingface без использования научной сети [Онлайн-эксперимент](https://huggingface.co/spaces/qingxu98/gpt-academic) | Войдите в систему, скопируйте пространство [этот пространственный URL](https://huggingface.co/spaces/qingxu98/gpt-academic) -…… | …… - - -- -- Новый интерфейс (вы можете изменить настройку LAYOUT в config.py, чтобы переключаться между "горизонтальным расположением" и "вертикальным расположением") --- - -Вы профессиональный переводчик научных статей. - -- Все кнопки генерируются динамически путем чтения functional.py и могут быть легко настроены под пользовательские потребности, освобождая буфер обмена. -
--- -- Редактирование/корректирование -
--- -- Если вывод содержит формулы, они отображаются одновременно как в формате tex, так и в рендеринговом формате для удобства копирования и чтения. -
--- -- Лень смотреть код проекта? Просто покажите chatgpt. -
--- -- Несколько моделей больших языковых моделей смешиваются (ChatGLM + OpenAI-GPT3.5 + [API2D] (https://api2d.com/) -GPT4) -
--- -Несколько моделей больших языковых моделей смешиваются в [бета-версии huggingface] (https://huggingface.co/spaces/qingxu98/academic-chatgpt-beta) (huggingface-версия не поддерживает chatglm). - - ---- - -## Установка - Метод 1: Запуск (Windows, Linux или MacOS) - -1. Скачайте проект -```sh -git clone https://github.com/binary-husky/chatgpt_academic.git -cd chatgpt_academic -``` - -2. Настройка API_KEY и настройки прокси - -В файле `config.py` настройте зарубежный прокси и OpenAI API KEY, пояснения ниже -``` -1. Если вы находитесь в Китае, вам нужно настроить зарубежный прокси, чтобы использовать OpenAI API. Пожалуйста, внимательно прочитайте config.py для получения инструкций (1. Измените USE_PROXY на True; 2. Измените прокси в соответствии с инструкциями). -2. Настройка API KEY OpenAI. Вам необходимо зарегистрироваться на сайте OpenAI и получить API KEY. После получения API KEY настройте его в файле config.py. -3. Вопросы, связанные с сетевыми проблемами (тайм-аут сети, прокси не работает), можно найти здесь: https://github.com/binary-husky/chatgpt_academic/issues/1 -``` -(Примечание: при запуске программы будет проверяться наличие конфиденциального файла конфигурации с именем `config_private.py` и использоваться в нем конфигурация параметров, которая перезаписывает параметры с такими же именами в `config.py`. Поэтому, если вы понимаете логику чтения нашей конфигурации, мы настоятельно рекомендуем вам создать новый файл конфигурации с именем `config_private.py` рядом с `config.py` и переместить (скопировать) настройки из `config.py` в `config_private.py`. `config_private.py` не подвергается контролю git, что делает конфиденциальную информацию более безопасной.) - - -3. Установить зависимости -```sh -# (Выбор 1) Рекомендуется -python -m pip install -r requirements.txt - -# (Выбор 2) Если вы используете anaconda, то шаги будут аналогичны: -# (Шаг 2.1) conda create -n gptac_venv python=3.11 -# (Шаг 2.2) conda activate gptac_venv -# (Шаг 2.3) python -m pip install -r requirements.txt - -# Примечание: используйте официальный источник pip или источник pip.aliyun.com. Другие источники pip могут вызывать проблемы. временный метод замены источника: -# python -m pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ -``` - -Если требуется поддержка TUNA ChatGLM, необходимо установить дополнительные зависимости (если вы неудобны с python, необходимо иметь хорошую конфигурацию компьютера): -```sh -python -m pip install -r request_llm/requirements_chatglm.txt -``` - -4. Запустите -```sh -python main.py -``` - -5. Тестовые функции плагина -``` -- Тестирвоание анализа проекта Python - В основной области введите `./crazy_functions/test_project/python/dqn` , а затем нажмите "Анализировать весь проект Python" -- Тестирование самостоятельного чтения кода - Щелкните " [Демонстрационный режим многопоточности] Проанализируйте сам проект (расшифровка источника кода)" -- Тестирование функций шаблонного плагина (вы можете использовать эту функцию как шаблон для более сложных функций, требующих ответа от gpt в связи с тем, что произошло сегодня в истории) - Щелкните " [Функции шаблонного плагина] День в истории" -- На нижней панели дополнительные функции для выбора -``` - -## Установка - Метод 2: Использование docker (Linux) - - -1. Только ChatGPT (рекомендуется для большинства пользователей): -``` sh -# Скачать проект -git clone https://github.com/binary-husky/chatgpt_academic.git -cd chatgpt_academic -# Настроить прокси за границей и OpenAI API KEY -Отредактируйте файл config.py в любом текстовом редакторе. -# Установка -docker build -t gpt-academic . -# Запустить -docker run --rm -it --net=host gpt-academic - -# Проверка функциональности плагина -## Проверка шаблонной функции плагина (требуется, чтобы gpt ответил, что произошло "в истории на этот день"), вы можете использовать эту функцию в качестве шаблона для реализации более сложных функций. -Нажмите "[Шаблонный демонстрационный плагин] История на этот день". -## Тест абстрактного резюме для проекта на Latex -В области ввода введите ./crazy_functions/test_project/latex/attention, а затем нажмите "Чтение реферата о тезисах статьи на LaTeX". -## Тестовый анализ проекта на Python -Введите в область ввода ./crazy_functions/test_project/python/dqn, затем нажмите "Проанализировать весь проект на Python". - -Выбирайте больше функциональных плагинов в нижнем выпадающем меню. -``` - -2. ChatGPT + ChatGLM (требуется глубокое знание Docker и достаточно мощное компьютерное оборудование): - -``` sh -# Изменение Dockerfile -cd docs && nano Dockerfile+ChatGLM -# Как построить | Как запустить (Dockerfile+ChatGLM в пути docs, сначала перейдите в папку с помощью cd docs) -docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM . -# Как запустить | Как запустить (2) я хочу войти в контейнер и сделать какие-то настройки до запуска: -docker run --rm -it --net=host --gpus=all gpt-academic bash -``` - - -## Установка-Метод 3: Другие способы развертывания - -1. Развертывание на удаленном облачном сервере -Пожалуйста, посетите [Deploy Wiki-1] (https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BA%91%E6%9C%8D%E5%8A%A1%E5%99%A8%E8%BF%9C%E7%A8%8B%E9%83%A8%E7%BD%B2%E6%8C%87%E5%8D%97) - -2. Использование WSL2 (Windows Subsystem for Linux) -Пожалуйста, посетите [Deploy Wiki-2] (https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BD%BF%E7%94%A8WSL2%EF%BC%88Windows-Subsystem-for-Linux-%E5%AD%90%E7%B3%BB%E7%BB%9F%EF%BC%89%E9%83%A8%E7%BD%B2) - - -## Установка-Настройки прокси -### Метод 1: Обычный способ -[Конфигурация прокси] (https://github.com/binary-husky/chatgpt_academic/issues/1) - -### Метод 2: Руководство новичка -[Руководство новичка] (https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BB%A3%E7%90%86%E8%BD%AF%E4%BB%B6%E9%97%AE%E9%A2%98%E7%9A%84%E6%96%B0%E6%89%8B%E8%A7%A3%E5%86%B3%E6%96%B9%E6%B3%95%EF%BC%88%E6%96%B9%E6%B3%95%E5%8F%AA%E9%80%82%E7%94%A8%E4%BA%8E%E6%96%B0%E6%89%8B%EF%BC%89) - - ---- - -## Настройка новой удобной кнопки (настройка быстрой клавиши для научной работы) -Откройте `core_functional.py` любым текстовым редактором, добавьте элементы, как показано ниже, затем перезапустите программу. (Если кнопка уже успешно добавлена и видна, то префикс и суффикс поддерживают горячее изменение, чтобы они оказались в действии, не нужно перезапускать программу.) -например -``` -"Супер анг-рус": { - # Префикс, будет добавлен перед вашим вводом. Например, используется для описания ваших потребностей, таких как перевод, кодинг, редактирование и т. д. - "Prefix": "Пожалуйста, переведите этот фрагмент на русский язык, а затем создайте пошаговую таблицу в markdown, чтобы объяснить все специализированные термины, которые встречаются в тексте:\n\n", - - # Суффикс, будет добавлен после вашего ввода. Например, совместно с префиксом можно обрамить ваш ввод в кавычки. - "Suffix": "", -}, -``` -
--- ---- - - -## Демонстрация некоторых возможностей - -### Отображение изображений: - -
--- - -### Если программа может понимать и разбирать сама себя: - -
--- -
--- - -### Анализ других проектов на Python/Cpp: -
--- -
--- -### Автоматическое создание отчетов -
--- -### Модульный дизайн функций -
-
-
--- - -### Трансляция исходного кода на английский язык - -
-
--- -## Todo и планирование версий: -- version 3.2+ (todo): функция плагины поддерживают более многочисленные интерфейсы параметров -- version 3.1: поддержка одновременного опроса нескольких моделей gpt! Поддержка api2d, поддержка балансировки нагрузки множества apikey. -- version 3.0: поддержка chatglm и других маленьких llm -- version 2.6: реструктурировал структуру плагинов, повысил интерактивность, добавил больше плагинов -- version 2.5: само обновление, решение проблемы слишком длинного текста и переполнения токена при переводе всего проекта исходного кода -- version 2.4: (1) добавлена функция перевода всего PDF-документа; (2) добавлена функция изменения положения входной области; (3) добавлена опция вертикального макета; (4) оптимизация функций многопоточности плагина. -- version 2.3: улучшение многопоточной интерактивности -- version 2.2: функция плагинов поддерживает горячую перезагрузку -- version 2.1: блочная раскладка -- version 2.0: модульный дизайн функций плагина -- version 1.0: основные функции - -## Ссылки на изучение и обучение - -``` -В коде использовано много хороших дизайнерских решений из других отличных проектов, в том числе: - -# Project1: использование многих приемов из ChuanhuChatGPT -https://github.com/GaiZhenbiao/ChuanhuChatGPT - -# Project2: ChatGLM-6B в Тхуде: -https://github.com/THUDM/ChatGLM-6B -``` - diff --git "a/spaces/Amon1/ChatGPTForAcadamic/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py" "b/spaces/Amon1/ChatGPTForAcadamic/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py" deleted file mode 100644 index 38f00c41c444cce62c27a235c239e25bbf0a2461..0000000000000000000000000000000000000000 --- "a/spaces/Amon1/ChatGPTForAcadamic/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py" +++ /dev/null @@ -1,186 +0,0 @@ -from predict import predict_no_ui -from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down, get_conf -import re, requests, unicodedata, os - -def download_arxiv_(url_pdf): - if 'arxiv.org' not in url_pdf: - if ('.' in url_pdf) and ('/' not in url_pdf): - new_url = 'https://arxiv.org/abs/'+url_pdf - print('下载编号：', url_pdf, '自动定位：', new_url) - # download_arxiv_(new_url) - return download_arxiv_(new_url) - else: - print('不能识别的URL！') - return None - if 'abs' in url_pdf: - url_pdf = url_pdf.replace('abs', 'pdf') - url_pdf = url_pdf + '.pdf' - - url_abs = url_pdf.replace('.pdf', '').replace('pdf', 'abs') - title, other_info = get_name(_url_=url_abs) - - paper_id = title.split()[0] # '[1712.00559]' - if '2' in other_info['year']: - title = other_info['year'] + ' ' + title - - known_conf = ['NeurIPS', 'NIPS', 'Nature', 'Science', 'ICLR', 'AAAI'] - for k in known_conf: - if k in other_info['comment']: - title = k + ' ' + title - - download_dir = './gpt_log/arxiv/' - os.makedirs(download_dir, exist_ok=True) - - title_str = title.replace('?', '？')\ - .replace(':', '：')\ - .replace('\"', '“')\ - .replace('\n', '')\ - .replace(' ', ' ')\ - .replace(' ', ' ') - - requests_pdf_url = url_pdf - file_path = download_dir+title_str - # if os.path.exists(file_path): - # print('返回缓存文件') - # return './gpt_log/arxiv/'+title_str - - print('下载中') - proxies, = get_conf('proxies') - r = requests.get(requests_pdf_url, proxies=proxies) - with open(file_path, 'wb+') as f: - f.write(r.content) - print('下载完成') - - # print('输出下载命令：','aria2c -o \"%s\" %s'%(title_str,url_pdf)) - # subprocess.call('aria2c --all-proxy=\"172.18.116.150:11084\" -o \"%s\" %s'%(download_dir+title_str,url_pdf), shell=True) - - x = "%s %s %s.bib" % (paper_id, other_info['year'], other_info['authors']) - x = x.replace('?', '？')\ - .replace(':', '：')\ - .replace('\"', '“')\ - .replace('\n', '')\ - .replace(' ', ' ')\ - .replace(' ', ' ') - return './gpt_log/arxiv/'+title_str, other_info - - -def get_name(_url_): - import os - from bs4 import BeautifulSoup - print('正在获取文献名！') - print(_url_) - - # arxiv_recall = {} - # if os.path.exists('./arxiv_recall.pkl'): - # with open('./arxiv_recall.pkl', 'rb') as f: - # arxiv_recall = pickle.load(f) - - # if _url_ in arxiv_recall: - # print('在缓存中') - # return arxiv_recall[_url_] - - proxies, = get_conf('proxies') - res = requests.get(_url_, proxies=proxies) - - bs = BeautifulSoup(res.text, 'html.parser') - other_details = {} - - # get year - try: - year = bs.find_all(class_='dateline')[0].text - year = re.search(r'(\d{4})', year, re.M | re.I).group(1) - other_details['year'] = year - abstract = bs.find_all(class_='abstract mathjax')[0].text - other_details['abstract'] = abstract - except: - other_details['year'] = '' - print('年份获取失败') - - # get author - try: - authors = bs.find_all(class_='authors')[0].text - authors = authors.split('Authors:')[1] - other_details['authors'] = authors - except: - other_details['authors'] = '' - print('authors获取失败') - - # get comment - try: - comment = bs.find_all(class_='metatable')[0].text - real_comment = None - for item in comment.replace('\n', ' ').split(' '): - if 'Comments' in item: - real_comment = item - if real_comment is not None: - other_details['comment'] = real_comment - else: - other_details['comment'] = '' - except: - other_details['comment'] = '' - print('年份获取失败') - - title_str = BeautifulSoup( - res.text, 'html.parser').find('title').contents[0] - print('获取成功：', title_str) - # arxiv_recall[_url_] = (title_str+'.pdf', other_details) - # with open('./arxiv_recall.pkl', 'wb') as f: - # pickle.dump(arxiv_recall, f) - - return title_str+'.pdf', other_details - - - -@CatchException -def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): - - CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要，函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……" - import glob - import os - - # 基本信息：功能、贡献者 - chatbot.append(["函数插件功能？", CRAZY_FUNCTION_INFO]) - yield chatbot, history, '正常' - - # 尝试导入依赖，如果缺少依赖，则给出安装建议 - try: - import pdfminer, bs4 - except: - report_execption(chatbot, history, - a = f"解析项目: {txt}", - b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pdfminer beautifulsoup4```。") - yield chatbot, history, '正常' - return - - # 清空历史，以免输入溢出 - history = [] - - # 提取摘要，下载PDF文档 - try: - pdf_path, info = download_arxiv_(txt) - except: - report_execption(chatbot, history, - a = f"解析项目: {txt}", - b = f"下载pdf文件未成功") - yield chatbot, history, '正常' - return - - # 翻译摘要等 - i_say = f"请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。材料如下：{str(info)}" - i_say_show_user = f'请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。论文：{pdf_path}' - chatbot.append((i_say_show_user, "[Local Message] waiting gpt response.")) - yield chatbot, history, '正常' - msg = '正常' - # ** gpt request ** - gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时 - chatbot[-1] = (i_say_show_user, gpt_say) - history.append(i_say_show_user); history.append(gpt_say) - yield chatbot, history, msg - # 写入文件 - import shutil - # 重置文件的创建时间 - shutil.copyfile(pdf_path, f'./gpt_log/{os.path.basename(pdf_path)}'); os.remove(pdf_path) - res = write_results_to_file(history) - chatbot.append(("完成了吗？", res + "\n\nPDF文件也已经下载")) - yield chatbot, history, msg - diff --git a/spaces/Andy1621/uniformer_image_detection/configs/guided_anchoring/ga_retinanet_r50_caffe_fpn_1x_coco.py b/spaces/Andy1621/uniformer_image_detection/configs/guided_anchoring/ga_retinanet_r50_caffe_fpn_1x_coco.py deleted file mode 100644 index 33512011abb612ff5c762e75ee4492b382902fa4..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_detection/configs/guided_anchoring/ga_retinanet_r50_caffe_fpn_1x_coco.py +++ /dev/null @@ -1,62 +0,0 @@ -_base_ = '../retinanet/retinanet_r50_caffe_fpn_1x_coco.py' -model = dict( - bbox_head=dict( - _delete_=True, - type='GARetinaHead', - num_classes=80, - in_channels=256, - stacked_convs=4, - feat_channels=256, - approx_anchor_generator=dict( - type='AnchorGenerator', - octave_base_scale=4, - scales_per_octave=3, - ratios=[0.5, 1.0, 2.0], - strides=[8, 16, 32, 64, 128]), - square_anchor_generator=dict( - type='AnchorGenerator', - ratios=[1.0], - scales=[4], - strides=[8, 16, 32, 64, 128]), - anchor_coder=dict( - type='DeltaXYWHBBoxCoder', - target_means=[.0, .0, .0, .0], - target_stds=[1.0, 1.0, 1.0, 1.0]), - bbox_coder=dict( - type='DeltaXYWHBBoxCoder', - target_means=[.0, .0, .0, .0], - target_stds=[1.0, 1.0, 1.0, 1.0]), - loc_filter_thr=0.01, - loss_loc=dict( - type='FocalLoss', - use_sigmoid=True, - gamma=2.0, - alpha=0.25, - loss_weight=1.0), - loss_shape=dict(type='BoundedIoULoss', beta=0.2, loss_weight=1.0), - loss_cls=dict( - type='FocalLoss', - use_sigmoid=True, - gamma=2.0, - alpha=0.25, - loss_weight=1.0), - loss_bbox=dict(type='SmoothL1Loss', beta=0.04, loss_weight=1.0)), - # training and testing settings - train_cfg=dict( - ga_assigner=dict( - type='ApproxMaxIoUAssigner', - pos_iou_thr=0.5, - neg_iou_thr=0.4, - min_pos_iou=0.4, - ignore_iof_thr=-1), - ga_sampler=dict( - type='RandomSampler', - num=256, - pos_fraction=0.5, - neg_pos_ub=-1, - add_gt_as_proposals=False), - assigner=dict(neg_iou_thr=0.5, min_pos_iou=0.0), - center_ratio=0.2, - ignore_ratio=0.5)) -optimizer_config = dict( - _delete_=True, grad_clip=dict(max_norm=35, norm_type=2)) diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/region_assigner.py b/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/region_assigner.py deleted file mode 100644 index 2e8464b97c8d8f44488d7bb781ca2e733a258e55..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/region_assigner.py +++ /dev/null @@ -1,221 +0,0 @@ -import torch - -from mmdet.core import anchor_inside_flags -from ..builder import BBOX_ASSIGNERS -from .assign_result import AssignResult -from .base_assigner import BaseAssigner - - -def calc_region(bbox, ratio, stride, featmap_size=None): - """Calculate region of the box defined by the ratio, the ratio is from the - center of the box to every edge.""" - # project bbox on the feature - f_bbox = bbox / stride - x1 = torch.round((1 - ratio) * f_bbox[0] + ratio * f_bbox[2]) - y1 = torch.round((1 - ratio) * f_bbox[1] + ratio * f_bbox[3]) - x2 = torch.round(ratio * f_bbox[0] + (1 - ratio) * f_bbox[2]) - y2 = torch.round(ratio * f_bbox[1] + (1 - ratio) * f_bbox[3]) - if featmap_size is not None: - x1 = x1.clamp(min=0, max=featmap_size[1]) - y1 = y1.clamp(min=0, max=featmap_size[0]) - x2 = x2.clamp(min=0, max=featmap_size[1]) - y2 = y2.clamp(min=0, max=featmap_size[0]) - return (x1, y1, x2, y2) - - -def anchor_ctr_inside_region_flags(anchors, stride, region): - """Get the flag indicate whether anchor centers are inside regions.""" - x1, y1, x2, y2 = region - f_anchors = anchors / stride - x = (f_anchors[:, 0] + f_anchors[:, 2]) * 0.5 - y = (f_anchors[:, 1] + f_anchors[:, 3]) * 0.5 - flags = (x >= x1) & (x <= x2) & (y >= y1) & (y <= y2) - return flags - - -@BBOX_ASSIGNERS.register_module() -class RegionAssigner(BaseAssigner): - """Assign a corresponding gt bbox or background to each bbox. - - Each proposals will be assigned with `-1`, `0`, or a positive integer - indicating the ground truth index. - - - -1: don't care - - 0: negative sample, no assigned gt - - positive integer: positive sample, index (1-based) of assigned gt - - Args: - center_ratio: ratio of the region in the center of the bbox to - define positive sample. - ignore_ratio: ratio of the region to define ignore samples. - """ - - def __init__(self, center_ratio=0.2, ignore_ratio=0.5): - self.center_ratio = center_ratio - self.ignore_ratio = ignore_ratio - - def assign(self, - mlvl_anchors, - mlvl_valid_flags, - gt_bboxes, - img_meta, - featmap_sizes, - anchor_scale, - anchor_strides, - gt_bboxes_ignore=None, - gt_labels=None, - allowed_border=0): - """Assign gt to anchors. - - This method assign a gt bbox to every bbox (proposal/anchor), each bbox - will be assigned with -1, 0, or a positive number. -1 means don't care, - 0 means negative sample, positive number is the index (1-based) of - assigned gt. - The assignment is done in following steps, the order matters. - - 1. Assign every anchor to 0 (negative) - For each gt_bboxes: - 2. Compute ignore flags based on ignore_region then - assign -1 to anchors w.r.t. ignore flags - 3. Compute pos flags based on center_region then - assign gt_bboxes to anchors w.r.t. pos flags - 4. Compute ignore flags based on adjacent anchor lvl then - assign -1 to anchors w.r.t. ignore flags - 5. Assign anchor outside of image to -1 - - Args: - mlvl_anchors (list[Tensor]): Multi level anchors. - mlvl_valid_flags (list[Tensor]): Multi level valid flags. - gt_bboxes (Tensor): Ground truth bboxes of image - img_meta (dict): Meta info of image. - featmap_sizes (list[Tensor]): Feature mapsize each level - anchor_scale (int): Scale of the anchor. - anchor_strides (list[int]): Stride of the anchor. - gt_bboxes (Tensor): Groundtruth boxes, shape (k, 4). - gt_bboxes_ignore (Tensor, optional): Ground truth bboxes that are - labelled as `ignored`, e.g., crowd boxes in COCO. - gt_labels (Tensor, optional): Label of gt_bboxes, shape (k, ). - allowed_border (int, optional): The border to allow the valid - anchor. Defaults to 0. - - Returns: - :obj:`AssignResult`: The assign result. - """ - if gt_bboxes_ignore is not None: - raise NotImplementedError - - num_gts = gt_bboxes.shape[0] - num_bboxes = sum(x.shape[0] for x in mlvl_anchors) - - if num_gts == 0 or num_bboxes == 0: - # No ground truth or boxes, return empty assignment - max_overlaps = gt_bboxes.new_zeros((num_bboxes, )) - assigned_gt_inds = gt_bboxes.new_zeros((num_bboxes, ), - dtype=torch.long) - if gt_labels is None: - assigned_labels = None - else: - assigned_labels = gt_bboxes.new_full((num_bboxes, ), - -1, - dtype=torch.long) - return AssignResult( - num_gts, - assigned_gt_inds, - max_overlaps, - labels=assigned_labels) - - num_lvls = len(mlvl_anchors) - r1 = (1 - self.center_ratio) / 2 - r2 = (1 - self.ignore_ratio) / 2 - - scale = torch.sqrt((gt_bboxes[:, 2] - gt_bboxes[:, 0]) * - (gt_bboxes[:, 3] - gt_bboxes[:, 1])) - min_anchor_size = scale.new_full( - (1, ), float(anchor_scale * anchor_strides[0])) - target_lvls = torch.floor( - torch.log2(scale) - torch.log2(min_anchor_size) + 0.5) - target_lvls = target_lvls.clamp(min=0, max=num_lvls - 1).long() - - # 1. assign 0 (negative) by default - mlvl_assigned_gt_inds = [] - mlvl_ignore_flags = [] - for lvl in range(num_lvls): - h, w = featmap_sizes[lvl] - assert h * w == mlvl_anchors[lvl].shape[0] - assigned_gt_inds = gt_bboxes.new_full((h * w, ), - 0, - dtype=torch.long) - ignore_flags = torch.zeros_like(assigned_gt_inds) - mlvl_assigned_gt_inds.append(assigned_gt_inds) - mlvl_ignore_flags.append(ignore_flags) - - for gt_id in range(num_gts): - lvl = target_lvls[gt_id].item() - featmap_size = featmap_sizes[lvl] - stride = anchor_strides[lvl] - anchors = mlvl_anchors[lvl] - gt_bbox = gt_bboxes[gt_id, :4] - - # Compute regions - ignore_region = calc_region(gt_bbox, r2, stride, featmap_size) - ctr_region = calc_region(gt_bbox, r1, stride, featmap_size) - - # 2. Assign -1 to ignore flags - ignore_flags = anchor_ctr_inside_region_flags( - anchors, stride, ignore_region) - mlvl_assigned_gt_inds[lvl][ignore_flags] = -1 - - # 3. Assign gt_bboxes to pos flags - pos_flags = anchor_ctr_inside_region_flags(anchors, stride, - ctr_region) - mlvl_assigned_gt_inds[lvl][pos_flags] = gt_id + 1 - - # 4. Assign -1 to ignore adjacent lvl - if lvl > 0: - d_lvl = lvl - 1 - d_anchors = mlvl_anchors[d_lvl] - d_featmap_size = featmap_sizes[d_lvl] - d_stride = anchor_strides[d_lvl] - d_ignore_region = calc_region(gt_bbox, r2, d_stride, - d_featmap_size) - ignore_flags = anchor_ctr_inside_region_flags( - d_anchors, d_stride, d_ignore_region) - mlvl_ignore_flags[d_lvl][ignore_flags] = 1 - if lvl < num_lvls - 1: - u_lvl = lvl + 1 - u_anchors = mlvl_anchors[u_lvl] - u_featmap_size = featmap_sizes[u_lvl] - u_stride = anchor_strides[u_lvl] - u_ignore_region = calc_region(gt_bbox, r2, u_stride, - u_featmap_size) - ignore_flags = anchor_ctr_inside_region_flags( - u_anchors, u_stride, u_ignore_region) - mlvl_ignore_flags[u_lvl][ignore_flags] = 1 - - # 4. (cont.) Assign -1 to ignore adjacent lvl - for lvl in range(num_lvls): - ignore_flags = mlvl_ignore_flags[lvl] - mlvl_assigned_gt_inds[lvl][ignore_flags] = -1 - - # 5. Assign -1 to anchor outside of image - flat_assigned_gt_inds = torch.cat(mlvl_assigned_gt_inds) - flat_anchors = torch.cat(mlvl_anchors) - flat_valid_flags = torch.cat(mlvl_valid_flags) - assert (flat_assigned_gt_inds.shape[0] == flat_anchors.shape[0] == - flat_valid_flags.shape[0]) - inside_flags = anchor_inside_flags(flat_anchors, flat_valid_flags, - img_meta['img_shape'], - allowed_border) - outside_flags = ~inside_flags - flat_assigned_gt_inds[outside_flags] = -1 - - if gt_labels is not None: - assigned_labels = torch.zeros_like(flat_assigned_gt_inds) - pos_flags = assigned_gt_inds > 0 - assigned_labels[pos_flags] = gt_labels[ - flat_assigned_gt_inds[pos_flags] - 1] - else: - assigned_labels = None - - return AssignResult( - num_gts, flat_assigned_gt_inds, None, labels=assigned_labels) diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/hrnet/fcn_hr18_480x480_80k_pascal_context_59.py b/spaces/Andy1621/uniformer_image_segmentation/configs/hrnet/fcn_hr18_480x480_80k_pascal_context_59.py deleted file mode 100644 index 9cbf4100d1f91161a4e8549d6b74799fc27ea35e..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_segmentation/configs/hrnet/fcn_hr18_480x480_80k_pascal_context_59.py +++ /dev/null @@ -1,8 +0,0 @@ -_base_ = [ - '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context_59.py', - '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' -] -model = dict( - decode_head=dict(num_classes=59), - test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) -optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) diff --git a/spaces/AngoHF/ANGO-Leaderboard/results/__init__.py b/spaces/AngoHF/ANGO-Leaderboard/results/__init__.py deleted file mode 100644 index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000 diff --git a/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/cmd_linux.sh b/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/cmd_linux.sh deleted file mode 100644 index 1685050aff7b270ae42e295c0b947d576e2653a3..0000000000000000000000000000000000000000 --- a/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/cmd_linux.sh +++ /dev/null @@ -1,22 +0,0 @@ -#!/bin/bash - -cd "$(dirname "${BASH_SOURCE[0]}")" - -if [[ "$(pwd)" =~ " " ]]; then echo This script relies on Miniconda which can not be silently installed under a path with spaces. && exit; fi - -# deactivate existing conda envs as needed to avoid conflicts -{ conda deactivate && conda deactivate && conda deactivate; } 2> /dev/null - -# config -CONDA_ROOT_PREFIX="$(pwd)/installer_files/conda" -INSTALL_ENV_DIR="$(pwd)/installer_files/env" - -# environment isolation -export PYTHONNOUSERSITE=1 -unset PYTHONPATH -unset PYTHONHOME -export CUDA_PATH="$INSTALL_ENV_DIR" -export CUDA_HOME="$CUDA_PATH" - -# activate env -bash --init-file <(echo "source \"$CONDA_ROOT_PREFIX/etc/profile.d/conda.sh\" && conda activate \"$INSTALL_ENV_DIR\"") diff --git a/spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/utils/visualization.py b/spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/utils/visualization.py deleted file mode 100644 index 0c23d4b58a93f72a44ffba79d208f8a10ceb8db1..0000000000000000000000000000000000000000 --- a/spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/utils/visualization.py +++ /dev/null @@ -1,78 +0,0 @@ -from pathlib import Path -from numpy.core.shape_base import block -import torch -import matplotlib.pyplot as plt -from torchvision.transforms import functional as TF - -from typing import Optional, Union - -import matplotlib.pyplot as plt -import numpy as np -from PIL.Image import Image - - -def show_tensor_image(tensor: torch.Tensor, range_zero_one: bool = False): - """Show a tensor of an image - - Args: - tensor (torch.Tensor): Tensor of shape [N, 3, H, W] in range [-1, 1] or in range [0, 1] - """ - if not range_zero_one: - tensor = (tensor + 1) / 2 - tensor.clamp(0, 1) - - batch_size = tensor.shape[0] - for i in range(batch_size): - plt.title(f"Fig_{i}") - pil_image = TF.to_pil_image(tensor[i]) - plt.imshow(pil_image) - plt.show(block=True) - - -def show_editied_masked_image( - title: str, - source_image: Image, - edited_image: Image, - mask: Optional[Image] = None, - path: Optional[Union[str, Path]] = None, - distance: Optional[str] = None, -): - fig_idx = 1 - rows = 1 - cols = 3 if mask is not None else 2 - - fig = plt.figure(figsize=(12, 5)) - figure_title = f'Prompt: "{title}"' - if distance is not None: - figure_title += f" ({distance})" - plt.title(figure_title) - plt.axis("off") - - fig.add_subplot(rows, cols, fig_idx) - fig_idx += 1 - _set_image_plot_name("Source Image") - plt.imshow(source_image) - - if mask is not None: - fig.add_subplot(rows, cols, fig_idx) - _set_image_plot_name("Mask") - plt.imshow(mask) - plt.gray() - fig_idx += 1 - - fig.add_subplot(rows, cols, fig_idx) - _set_image_plot_name("Edited Image") - plt.imshow(edited_image) - - if path is not None: - plt.savefig(path, bbox_inches="tight") - else: - plt.show(block=True) - - plt.close() - - -def _set_image_plot_name(name): - plt.title(name) - plt.xticks([]) - plt.yticks([]) diff --git a/spaces/AnthonyTruchetPoC/persistent-docker/scripts/build-local-docker.sh b/spaces/AnthonyTruchetPoC/persistent-docker/scripts/build-local-docker.sh deleted file mode 100644 index 68aedd13ce0657edf615c9249ffec6d5819dd63c..0000000000000000000000000000000000000000 --- a/spaces/AnthonyTruchetPoC/persistent-docker/scripts/build-local-docker.sh +++ /dev/null @@ -1,11 +0,0 @@ -#!/usr/bin/env bash -source $(dirname $0)/common_header.sh - -# Export the dependencies managed by Poetry in the requirements.txt format for pip -poetry export -f requirements.txt -o requirements.txt --without-hashes --with=jupyter - -# Re-build the docker image. -docker build -f $ROOT_DIRECTORY/Dockerfile --label tests -t $CONTAINER_NAME . - - - diff --git a/spaces/AriaMei/TTSdemo/text/mandarin.py b/spaces/AriaMei/TTSdemo/text/mandarin.py deleted file mode 100644 index a9ce0c4b223cd7fbb00e8332d2dd53de4c7cea09..0000000000000000000000000000000000000000 --- a/spaces/AriaMei/TTSdemo/text/mandarin.py +++ /dev/null @@ -1,328 +0,0 @@ -import os -import sys -import re -from pypinyin import lazy_pinyin, BOPOMOFO -import jieba -import cn2an - - -# List of (Latin alphabet, bopomofo) pairs: -_latin_to_bopomofo = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [ - ('a', 'ㄟˉ'), - ('b', 'ㄅㄧˋ'), - ('c', 'ㄙㄧˉ'), - ('d', 'ㄉㄧˋ'), - ('e', 'ㄧˋ'), - ('f', 'ㄝˊㄈㄨˋ'), - ('g', 'ㄐㄧˋ'), - ('h', 'ㄝˇㄑㄩˋ'), - ('i', 'ㄞˋ'), - ('j', 'ㄐㄟˋ'), - ('k', 'ㄎㄟˋ'), - ('l', 'ㄝˊㄛˋ'), - ('m', 'ㄝˊㄇㄨˋ'), - ('n', 'ㄣˉ'), - ('o', 'ㄡˉ'), - ('p', 'ㄆㄧˉ'), - ('q', 'ㄎㄧㄡˉ'), - ('r', 'ㄚˋ'), - ('s', 'ㄝˊㄙˋ'), - ('t', 'ㄊㄧˋ'), - ('u', 'ㄧㄡˉ'), - ('v', 'ㄨㄧˉ'), - ('w', 'ㄉㄚˋㄅㄨˋㄌㄧㄡˋ'), - ('x', 'ㄝˉㄎㄨˋㄙˋ'), - ('y', 'ㄨㄞˋ'), - ('z', 'ㄗㄟˋ') -]] - -# List of (bopomofo, romaji) pairs: -_bopomofo_to_romaji = [(re.compile('%s' % x[0]), x[1]) for x in [ - ('ㄅㄛ', 'p⁼wo'), - ('ㄆㄛ', 'pʰwo'), - ('ㄇㄛ', 'mwo'), - ('ㄈㄛ', 'fwo'), - ('ㄅ', 'p⁼'), - ('ㄆ', 'pʰ'), - ('ㄇ', 'm'), - ('ㄈ', 'f'), - ('ㄉ', 't⁼'), - ('ㄊ', 'tʰ'), - ('ㄋ', 'n'), - ('ㄌ', 'l'), - ('ㄍ', 'k⁼'), - ('ㄎ', 'kʰ'), - ('ㄏ', 'h'), - ('ㄐ', 'ʧ⁼'), - ('ㄑ', 'ʧʰ'), - ('ㄒ', 'ʃ'), - ('ㄓ', 'ʦ`⁼'), - ('ㄔ', 'ʦ`ʰ'), - ('ㄕ', 's`'), - ('ㄖ', 'ɹ`'), - ('ㄗ', 'ʦ⁼'), - ('ㄘ', 'ʦʰ'), - ('ㄙ', 's'), - ('ㄚ', 'a'), - ('ㄛ', 'o'), - ('ㄜ', 'ə'), - ('ㄝ', 'e'), - ('ㄞ', 'ai'), - ('ㄟ', 'ei'), - ('ㄠ', 'au'), - ('ㄡ', 'ou'), - ('ㄧㄢ', 'yeNN'), - ('ㄢ', 'aNN'), - ('ㄧㄣ', 'iNN'), - ('ㄣ', 'əNN'), - ('ㄤ', 'aNg'), - ('ㄧㄥ', 'iNg'), - ('ㄨㄥ', 'uNg'), - ('ㄩㄥ', 'yuNg'), - ('ㄥ', 'əNg'), - ('ㄦ', 'əɻ'), - ('ㄧ', 'i'), - ('ㄨ', 'u'), - ('ㄩ', 'ɥ'), - ('ˉ', '→'), - ('ˊ', '↑'), - ('ˇ', '↓↑'), - ('ˋ', '↓'), - ('˙', ''), - ('，', ','), - ('。', '.'), - ('！', '!'), - ('？', '?'), - ('—', '-') -]] - -# List of (romaji, ipa) pairs: -_romaji_to_ipa = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [ - ('ʃy', 'ʃ'), - ('ʧʰy', 'ʧʰ'), - ('ʧ⁼y', 'ʧ⁼'), - ('NN', 'n'), - ('Ng', 'ŋ'), - ('y', 'j'), - ('h', 'x') -]] - -# List of (bopomofo, ipa) pairs: -_bopomofo_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [ - ('ㄅㄛ', 'p⁼wo'), - ('ㄆㄛ', 'pʰwo'), - ('ㄇㄛ', 'mwo'), - ('ㄈㄛ', 'fwo'), - ('ㄅ', 'p⁼'), - ('ㄆ', 'pʰ'), - ('ㄇ', 'm'), - ('ㄈ', 'f'), - ('ㄉ', 't⁼'), - ('ㄊ', 'tʰ'), - ('ㄋ', 'n'), - ('ㄌ', 'l'), - ('ㄍ', 'k⁼'), - ('ㄎ', 'kʰ'), - ('ㄏ', 'x'), - ('ㄐ', 'tʃ⁼'), - ('ㄑ', 'tʃʰ'), - ('ㄒ', 'ʃ'), - ('ㄓ', 'ts`⁼'), - ('ㄔ', 'ts`ʰ'), - ('ㄕ', 's`'), - ('ㄖ', 'ɹ`'), - ('ㄗ', 'ts⁼'), - ('ㄘ', 'tsʰ'), - ('ㄙ', 's'), - ('ㄚ', 'a'), - ('ㄛ', 'o'), - ('ㄜ', 'ə'), - ('ㄝ', 'ɛ'), - ('ㄞ', 'aɪ'), - ('ㄟ', 'eɪ'), - ('ㄠ', 'ɑʊ'), - ('ㄡ', 'oʊ'), - ('ㄧㄢ', 'jɛn'), - ('ㄩㄢ', 'ɥæn'), - ('ㄢ', 'an'), - ('ㄧㄣ', 'in'), - ('ㄩㄣ', 'ɥn'), - ('ㄣ', 'ən'), - ('ㄤ', 'ɑŋ'), - ('ㄧㄥ', 'iŋ'), - ('ㄨㄥ', 'ʊŋ'), - ('ㄩㄥ', 'jʊŋ'), - ('ㄥ', 'əŋ'), - ('ㄦ', 'əɻ'), - ('ㄧ', 'i'), - ('ㄨ', 'u'), - ('ㄩ', 'ɥ'), - ('ˉ', '→'), - ('ˊ', '↑'), - ('ˇ', '↓↑'), - ('ˋ', '↓'), - ('˙', ''), - ('，', ','), - ('。', '.'), - ('！', '!'), - ('？', '?'), - ('—', '-') -]] - -# List of (bopomofo, ipa2) pairs: -_bopomofo_to_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [ - ('ㄅㄛ', 'pwo'), - ('ㄆㄛ', 'pʰwo'), - ('ㄇㄛ', 'mwo'), - ('ㄈㄛ', 'fwo'), - ('ㄅ', 'p'), - ('ㄆ', 'pʰ'), - ('ㄇ', 'm'), - ('ㄈ', 'f'), - ('ㄉ', 't'), - ('ㄊ', 'tʰ'), - ('ㄋ', 'n'), - ('ㄌ', 'l'), - ('ㄍ', 'k'), - ('ㄎ', 'kʰ'), - ('ㄏ', 'h'), - ('ㄐ', 'tɕ'), - ('ㄑ', 'tɕʰ'), - ('ㄒ', 'ɕ'), - ('ㄓ', 'tʂ'), - ('ㄔ', 'tʂʰ'), - ('ㄕ', 'ʂ'), - ('ㄖ', 'ɻ'), - ('ㄗ', 'ts'), - ('ㄘ', 'tsʰ'), - ('ㄙ', 's'), - ('ㄚ', 'a'), - ('ㄛ', 'o'), - ('ㄜ', 'ɤ'), - ('ㄝ', 'ɛ'), - ('ㄞ', 'aɪ'), - ('ㄟ', 'eɪ'), - ('ㄠ', 'ɑʊ'), - ('ㄡ', 'oʊ'), - ('ㄧㄢ', 'jɛn'), - ('ㄩㄢ', 'yæn'), - ('ㄢ', 'an'), - ('ㄧㄣ', 'in'), - ('ㄩㄣ', 'yn'), - ('ㄣ', 'ən'), - ('ㄤ', 'ɑŋ'), - ('ㄧㄥ', 'iŋ'), - ('ㄨㄥ', 'ʊŋ'), - ('ㄩㄥ', 'jʊŋ'), - ('ㄥ', 'ɤŋ'), - ('ㄦ', 'əɻ'), - ('ㄧ', 'i'), - ('ㄨ', 'u'), - ('ㄩ', 'y'), - ('ˉ', '˥'), - ('ˊ', '˧˥'), - ('ˇ', '˨˩˦'), - ('ˋ', '˥˩'), - ('˙', ''), - ('，', ','), - ('。', '.'), - ('！', '!'), - ('？', '?'), - ('—', '-') -]] - - -def number_to_chinese(text): - numbers = re.findall(r'\d+(?:\.?\d+)?', text) - for number in numbers: - text = text.replace(number, cn2an.an2cn(number), 1) - return text - - -def chinese_to_bopomofo(text, taiwanese=False): - text = text.replace('、', '，').replace('；', '，').replace('：', '，') - words = jieba.lcut(text, cut_all=False) - text = '' - for word in words: - bopomofos = lazy_pinyin(word, BOPOMOFO) - if not re.search('[\u4e00-\u9fff]', word): - text += word - continue - for i in range(len(bopomofos)): - bopomofos[i] = re.sub(r'([\u3105-\u3129])$', r'\1ˉ', bopomofos[i]) - if text != '': - text += ' ' - if taiwanese: - text += '#'+'#'.join(bopomofos) - else: - text += ''.join(bopomofos) - return text - - -def latin_to_bopomofo(text): - for regex, replacement in _latin_to_bopomofo: - text = re.sub(regex, replacement, text) - return text - - -def bopomofo_to_romaji(text): - for regex, replacement in _bopomofo_to_romaji: - text = re.sub(regex, replacement, text) - return text - - -def bopomofo_to_ipa(text): - for regex, replacement in _bopomofo_to_ipa: - text = re.sub(regex, replacement, text) - return text - - -def bopomofo_to_ipa2(text): - for regex, replacement in _bopomofo_to_ipa2: - text = re.sub(regex, replacement, text) - return text - - -def chinese_to_romaji(text): - text = number_to_chinese(text) - text = chinese_to_bopomofo(text) - text = latin_to_bopomofo(text) - text = bopomofo_to_romaji(text) - text = re.sub('i([aoe])', r'y\1', text) - text = re.sub('u([aoəe])', r'w\1', text) - text = re.sub('([ʦsɹ]`[⁼ʰ]?)([→↓↑ ]+|$)', - r'\1ɹ`\2', text).replace('ɻ', 'ɹ`') - text = re.sub('([ʦs][⁼ʰ]?)([→↓↑ ]+|$)', r'\1ɹ\2', text) - return text - - -def chinese_to_lazy_ipa(text): - text = chinese_to_romaji(text) - for regex, replacement in _romaji_to_ipa: - text = re.sub(regex, replacement, text) - return text - - -def chinese_to_ipa(text): - text = number_to_chinese(text) - text = chinese_to_bopomofo(text) - text = latin_to_bopomofo(text) - text = bopomofo_to_ipa(text) - text = re.sub('i([aoe])', r'j\1', text) - text = re.sub('u([aoəe])', r'w\1', text) - text = re.sub('([sɹ]`[⁼ʰ]?)([→↓↑ ]+|$)', - r'\1ɹ`\2', text).replace('ɻ', 'ɹ`') - text = re.sub('([s][⁼ʰ]?)([→↓↑ ]+|$)', r'\1ɹ\2', text) - return text - - -def chinese_to_ipa2(text, taiwanese=False): - text = number_to_chinese(text) - text = chinese_to_bopomofo(text, taiwanese) - text = latin_to_bopomofo(text) - text = bopomofo_to_ipa2(text) - text = re.sub(r'i([aoe])', r'j\1', text) - text = re.sub(r'u([aoəe])', r'w\1', text) - text = re.sub(r'([ʂɹ]ʰ?)([˩˨˧˦˥ ]+|$)', r'\1ʅ\2', text) - text = re.sub(r'(sʰ?)([˩˨˧˦˥ ]+|$)', r'\1ɿ\2', text) - return text diff --git a/spaces/Arnasltlt/KlauskKnygos/app.py b/spaces/Arnasltlt/KlauskKnygos/app.py deleted file mode 100644 index b3cef235c5015750aba242314579fd627bea873f..0000000000000000000000000000000000000000 --- a/spaces/Arnasltlt/KlauskKnygos/app.py +++ /dev/null @@ -1,26 +0,0 @@ -import openai -import gradio as gr -import os - -openai.api_key = os.environ["openai_key"] - -def gpt4(instruction, email): - completion = openai.ChatCompletion.create( - model="gpt-4", - messages=[ - {"role": "system", "content": f'{instruction}'}, - {"role": "user", "content": f"{email}"}, - ], temperature=0, - ) - - return completion.choices[0].message.content - -# Define the Gradio input and output interfaces -inputs = [ - gr.inputs.Textbox(label="Instruction"), - gr.inputs.Textbox(label="Email") -] -output = gr.outputs.Textbox(label="Output") - -# Create a Gradio interface and launch it -gr.Interface(fn=gpt4, inputs=inputs, outputs=output, title="GPT-4 Demo").launch() diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/chardet/langturkishmodel.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/chardet/langturkishmodel.py deleted file mode 100644 index 291857c25c83f91a151c1d7760e8e5e09c1ee238..0000000000000000000000000000000000000000 --- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/chardet/langturkishmodel.py +++ /dev/null @@ -1,4380 +0,0 @@ -from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel - -# 3: Positive -# 2: Likely -# 1: Unlikely -# 0: Negative - -TURKISH_LANG_MODEL = { - 23: { # 'A' - 23: 0, # 'A' - 37: 0, # 'B' - 47: 0, # 'C' - 39: 0, # 'D' - 29: 0, # 'E' - 52: 0, # 'F' - 36: 0, # 'G' - 45: 0, # 'H' - 53: 0, # 'I' - 60: 0, # 'J' - 16: 0, # 'K' - 49: 0, # 'L' - 20: 0, # 'M' - 46: 0, # 'N' - 42: 0, # 'O' - 48: 0, # 'P' - 44: 0, # 'R' - 35: 0, # 'S' - 31: 0, # 'T' - 51: 0, # 'U' - 38: 0, # 'V' - 62: 0, # 'W' - 43: 0, # 'Y' - 56: 0, # 'Z' - 1: 3, # 'a' - 21: 0, # 'b' - 28: 0, # 'c' - 12: 2, # 'd' - 2: 3, # 'e' - 18: 0, # 'f' - 27: 1, # 'g' - 25: 1, # 'h' - 3: 1, # 'i' - 24: 0, # 'j' - 10: 2, # 'k' - 5: 1, # 'l' - 13: 1, # 'm' - 4: 1, # 'n' - 15: 0, # 'o' - 26: 0, # 'p' - 7: 1, # 'r' - 8: 1, # 's' - 9: 1, # 't' - 14: 1, # 'u' - 32: 0, # 'v' - 57: 0, # 'w' - 58: 0, # 'x' - 11: 3, # 'y' - 22: 0, # 'z' - 63: 0, # '·' - 54: 0, # 'Ç' - 50: 0, # 'Ö' - 55: 0, # 'Ü' - 59: 0, # 'â' - 33: 1, # 'ç' - 61: 0, # 'î' - 34: 0, # 'ö' - 17: 0, # 'ü' - 30: 0, # 'ğ' - 41: 0, # 'İ' - 6: 0, # 'ı' - 40: 0, # 'Ş' - 19: 0, # 'ş' - }, - 37: { # 'B' - 23: 0, # 'A' - 37: 0, # 'B' - 47: 2, # 'C' - 39: 0, # 'D' - 29: 0, # 'E' - 52: 2, # 'F' - 36: 0, # 'G' - 45: 0, # 'H' - 53: 0, # 'I' - 60: 0, # 'J' - 16: 1, # 'K' - 49: 0, # 'L' - 20: 0, # 'M' - 46: 0, # 'N' - 42: 0, # 'O' - 48: 1, # 'P' - 44: 0, # 'R' - 35: 1, # 'S' - 31: 0, # 'T' - 51: 0, # 'U' - 38: 1, # 'V' - 62: 0, # 'W' - 43: 1, # 'Y' - 56: 0, # 'Z' - 1: 2, # 'a' - 21: 0, # 'b' - 28: 2, # 'c' - 12: 0, # 'd' - 2: 3, # 'e' - 18: 0, # 'f' - 27: 0, # 'g' - 25: 0, # 'h' - 3: 0, # 'i' - 24: 0, # 'j' - 10: 0, # 'k' - 5: 0, # 'l' - 13: 1, # 'm' - 4: 1, # 'n' - 15: 0, # 'o' - 26: 0, # 'p' - 7: 0, # 'r' - 8: 0, # 's' - 9: 0, # 't' - 14: 2, # 'u' - 32: 0, # 'v' - 57: 0, # 'w' - 58: 0, # 'x' - 11: 0, # 'y' - 22: 1, # 'z' - 63: 0, # '·' - 54: 0, # 'Ç' - 50: 1, # 'Ö' - 55: 0, # 'Ü' - 59: 0, # 'â' - 33: 0, # 'ç' - 61: 0, # 'î' - 34: 1, # 'ö' - 17: 0, # 'ü' - 30: 0, # 'ğ' - 41: 0, # 'İ' - 6: 0, # 'ı' - 40: 1, # 'Ş' - 19: 1, # 'ş' - }, - 47: { # 'C' - 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-str_type: Tuple[type, ...] = (str, bytes) -_generator_type = type((_ for _ in ())) - - -class _ParseResultsWithOffset: - __slots__ = ["tup"] - - def __init__(self, p1, p2): - self.tup = (p1, p2) - - def __getitem__(self, i): - return self.tup[i] - - def __getstate__(self): - return self.tup - - def __setstate__(self, *args): - self.tup = args[0] - - -class ParseResults: - """Structured parse results, to provide multiple means of access to - the parsed data: - - - as a list (``len(results)``) - - by list index (``results[0], results[1]``, etc.) - - by attribute (``results.
-