Update parquet files (step 93 of 249)

spaces/1-13-am/neural-style-transfer/utils.py

@@ -1,138 +0,0 @@
-from skimage.exposure import match_histograms
-from skimage import io
-import os
-from PIL import Image
-import torch
-import torchvision
-import torchvision.transforms as transforms
-
-def normalize():
-  MEAN = [0.485, 0.456, 0.406]
-  STD = [0.229, 0.224, 0.225]
-  return transforms.Normalize(mean = MEAN, std = STD)
-
-def denormalize():
-  # out = (x - mean) / std
-  MEAN = [0.485, 0.456, 0.406]
-  STD = [0.229, 0.224, 0.225]
-  MEAN = [-mean/std for mean, std in zip(MEAN, STD)]
-  STD = [1/std for std in STD]
-  return transforms.Normalize(mean=MEAN, std=STD)
-
-def transformer(imsize = None, cropsize = None):
-  transformer = []
-  if imsize:
-        transformer.append(transforms.Resize(imsize))
-  if cropsize:
-        transformer.append(transforms.RandomCrop(cropsize))
-
-  transformer.append(transforms.ToTensor())
-  transformer.append(normalize())
-  return transforms.Compose(transformer)
-
-def load_img(path, imsize = None, cropsize = None):
-  transform = transformer(imsize = imsize, cropsize = cropsize)
-  # torchvision.transforms supports PIL Images
-  return transform(Image.open(path).convert("RGB")).unsqueeze(0)
-
-def tensor_to_img(tensor):
-  denormalizer = denormalize()
-  if tensor.device == "cuda":
-    tensor = tensor.cpu()
-  #
-  tensor = torchvision.utils.make_grid(denormalizer(tensor.squeeze()))
-  image = transforms.functional.to_pil_image(tensor.clamp_(0., 1.))
-  return image
-
-def save_img(tensor, path):
-  pass
-
-def histogram_matching(image, reference):
-  """
-  img: style image
-  reference: original img
-  output: style image that resembles original img's color histogram
-  """
-  device = image.device
-  reference = reference.cpu().permute(1, 2, 0).numpy()
-  image = image.cpu().permute(1, 2, 0).numpy()
-  output = match_histograms(image, reference, multichannel = True)
-  return torch.Tensor(output).permute(2, 0, 1).to(device)
-
-def batch_histogram_matching(images, reference):
-  """
-  images of shape BxCxHxW
-  reference of shape 1xCxHxW
-  """
-  reference = reference.squeeze()
-  output = torch.zeros_like(images, dtype = images.dtype)
-  B = images.shape[0]
-  for i in range(B):
-    output[i] = histogram_matching(images[i], reference)
-  return output
-
-def statistics(f, inverse = False, eps = 1e-10):
-  c, h, w = f.shape
-  f_mean = torch.mean(f.view(c, h*w), dim=1, keepdim=True)
-  f_zeromean = f.view(c, h*w) - f_mean
-  f_cov = torch.mm(f_zeromean, f_zeromean.t())
-
-  u, s, v = torch.svd(f_cov)
-
-  k = c
-  for i in range(c):
-    if s[i] < eps:
-        k = i
-        break
-  if inverse:
-        p = -0.5
-  else:
-        p = 0.5
-
-  f_covsqrt = torch.mm(torch.mm(u[:, 0:k], torch.diag(s[0:k].pow(p))), v[:, 0:k].t())
-  return f_mean, f_covsqrt
-
-def whitening(f):
-  c, h, w = f.shape
-  f_mean, f_inv_covsqrt = statistics(f, inverse = True)
-  whitened_f = torch.mm(f_inv_covsqrt, f.view(c, h*w) - f_mean)
-  return whitened_f.view(c, h, w)
-
-def batch_whitening(f):
-  b, c, h, w = f.shape
-  whitened_f = torch.zeros(size = (b, c, h, w), dtype = f.dtype, device = f.device)
-  for i in range(b):
-    whitened_f[i] = whitening(f[i])
-  return whitened_f
-
-def coloring(style, content):
-  s_c, s_h, s_w = style.shape
-  c_mean, c_covsqrt = statistics(content, inverse = False)
-  colored_s = torch.mm(c_covsqrt, whitening(style).view(s_c, s_h * s_w)) + c_mean
-  return colored_s.view(s_c, s_h, s_w)
-
-def batch_coloring(styles, content):
-  colored_styles = torch.zeros_like(styles, dtype = styles.dtype, device = styles.device)
-  for i, style in enumerate(styles):
-    colored_styles[i] = coloring(style, content[i])
-
-  return colored_styles
-
-def batch_wct(styles, content):
-  whitened_styles = batch_whitening(styles)
-  return batch_coloring(whitened_styles, content)
-
-class Image_Set(torch.utils.data.Dataset):
-  def __init__(self, root_path, imsize, cropsize):
-    super(Image_Set, self).__init__()
-    self.root_path = root_path
-    self.files = sorted(os.listdir(self.root_path))
-    self.transformer = transformer(imsize, cropsize)
-
-  def __len__(self):
-    return len(self.file_names)
-
-  def __getitem__(self, index):
-    image = Image.open(os.path.join(self.root_path + self.file_names[index])).convert("RGB")
-    return self.transformer(image)
-

spaces/109peko/anime-remove-background/README.md

@@ -1,14 +0,0 @@
----
-title: Anime Remove Background
-emoji: 🪄🖼️
-colorFrom: indigo
-colorTo: pink
-sdk: gradio
-sdk_version: 3.1.4
-app_file: app.py
-pinned: false
-license: apache-2.0
-duplicated_from: skytnt/anime-remove-background
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/1acneusushi/gradio-2dmoleculeeditor/data/Avast licence key download How to get the most out of your subscription.md

@@ -1,225 +0,0 @@
-
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- <h5>Avast AntiTrack Premium is a privacy protection app that disguises your online identity and stops data collectors from tracking you.</h5>
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- <h2>Conclusion</h2>
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- <p>If you want to get a free Avast license key for 2022, you can either use the recommendation program or download full versions of Avast products from the official website. You can enjoy the full features of Avast products for free without any cracks or keygens.</p>
- <p>If you want to download Avast products for free, you can click on the links below.</p>
- <ul>
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-<li><a href="https://www.avast.com/free-license#premium-security">Avast Premium Security</a></li>
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-<li><a href="https://www.avast.com/free-license#secureline-vpn">Avast SecureLine VPN</a></li>
-</ul>
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- <ol>
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-<li>Check your subscription details and click Continue.</li>
-<li>Your Avast product is now activated.</li>
-</ol>
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- <ol>
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- <table border="1">
-<tr><th>Name</th><th>Description</th><th>Screenshot</th></tr>
- <tr><td><strong>FrankU's Dutch parks and plazas</strong></td><td>A set of parks and plazas inspired by Dutch urban design, featuring brick paths, fountains, benches, flower beds and more.</td><td><img src="https://community.simtropolis.com/uploads/monthly_2017_08/5996a9f9a8c6f_FrankU_DutchParksAndPlazas.jpg" width="200" height="150"></td></tr>
- <tr><td><strong>Mattb's midrise office pack</strong></td><td>A pack of midrise office buildings with different styles and colors, ranging from modern glass towers to classic brick structures.</td><td><img src="https://community.simtropolis.com/uploads/monthly_2017_08/5996aa0f8d9f7_Mattb_MidriseOfficePack.jpg" width="200" height="150"></td></tr>
- <tr><td><strong>Jasoncw's American architecture set</strong></td><td>A set of American architecture buildings based on real-life examples, including Art Deco skyscrapers, Beaux-Arts landmarks, and Gothic churches.</td><td><img src="https://community.simtropolis.com/uploads/monthly_2017_08/5996aa1c8e8c5_Jasoncw_AmericanArchitectureSet.jpg" width="200" height="150"></td></tr>
- ```html various countries and eras, such as the Eiffel Tower, the Taj Mahal, the Colosseum, and the Statue of Liberty.</td><td><img src="https://community.simtropolis.com/uploads/monthly_2017_08/5996aa2c8f9a0_JBSimio_HistoricalLandmarks.jpg" width="200" height="150"></td></tr>
- <tr><td><strong>And many more!</strong></td><td>These are just some examples of the amazing content that you can find on STEX collection Vol.4. There are many more files that you can explore and enjoy, such as farms, factories, airports, seaports, stadiums, museums, schools, hospitals, fire stations, police stations, power plants, water plants, landmarks, parks, plazas, trees, flowers, signs, vehicles, people and more.</td><td><img src="https://community.simtropolis.com/uploads/monthly_2017_08/5996aa3b8f9a1_STEXCollectionVol4.jpg" width="200" height="150"></td></tr>
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-<p>STEX collection Vol.4 is a must-have for SimCity 4 fans who want to enhance their game with new features and options, improve their city's appearance with custom buildings and props, and support the SimCity 4 community and Simtropolis. It is a curated selection of the best mods and addons for SimCity 4 that you can get with a simple donation to Simtropolis or download as a ZIP file from their website. It contains over 1000 files from various categories that can make your game more fun, realistic and beautiful.</p>
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spaces/1line/AutoGPT/autogpt/memory/base.py

@@ -1,43 +0,0 @@
-"""Base class for memory providers."""
-import abc
-
-import openai
-
-from autogpt.config import AbstractSingleton, Config
-
-cfg = Config()
-
-
-def get_ada_embedding(text):
-    text = text.replace("\n", " ")
-    if cfg.use_azure:
-        return openai.Embedding.create(
-            input=[text],
-            engine=cfg.get_azure_deployment_id_for_model("text-embedding-ada-002"),
-        )["data"][0]["embedding"]
-    else:
-        return openai.Embedding.create(input=[text], model="text-embedding-ada-002")[
-            "data"
-        ][0]["embedding"]
-
-
-class MemoryProviderSingleton(AbstractSingleton):
-    @abc.abstractmethod
-    def add(self, data):
-        pass
-
-    @abc.abstractmethod
-    def get(self, data):
-        pass
-
-    @abc.abstractmethod
-    def clear(self):
-        pass
-
-    @abc.abstractmethod
-    def get_relevant(self, data, num_relevant=5):
-        pass
-
-    @abc.abstractmethod
-    def get_stats(self):
-        pass

spaces/1phancelerku/anime-remove-background/Download BEYBLADE BURST app for iOS and Android - Latest Version.md

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-<h1>Beyblade Burst App Download: How to Play and Enjoy the Game on Your Device</h1>
- <p>If you are a fan of the popular anime and toy series Beyblade, you might want to try out the Beyblade Burst App, a mobile game that lets you create, customize, and battle your own Beyblade Burst tops. The game is based on the third generation of the Beyblade franchise, which features a new system of interchangeable parts that can burst during battles. The game also allows you to challenge your friends and other players from around the world in online matches, join or create your own battle league, scan and control Bluetooth enabled Beyblade Burst tops, and use special moves and power-ups to win. In this article, we will show you how to download and install the Beyblade Burst App on your device, how to play the game, and some tips and tricks to help you become a better Blader.</p>
- <h2>What is Beyblade Burst App?</h2>
- <p>The Beyblade Burst App is a mobile game developed by Hasbro Inc. that is based on the Beyblade Burst anime and toy series. The game was released in 2016 and has been updated regularly with new features, content, and compatibility. The game is available for free on both Android and iOS devices, but it also offers in-app purchases for some items and features. The game has received positive reviews from users and critics, who praised its graphics, gameplay, customization options, and multiplayer modes. The game has also been nominated for several awards, such as the Kids' Choice Awards, the Webby Awards, and the TIGA Games Industry Awards.</p>
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- <h3>Features of Beyblade Burst App</h3>
- <p>The Beyblade Burst App has many features that make it fun and engaging for players of all ages. Some of the main features are:</p>
- <ul>
-<li>Create, customize, and battle your own Beyblade Burst tops with hundreds of different parts and colors.</li>
-<li>Challenge your friends and other players from over 90 countries worldwide to global multiplayer online matches, with leaderboards, personalized profiles, an enhanced digital top selection, and the capability of earning achievements.</li>
-<li>Join or create a league of your own, where you can invite your friends, choose a season length, earn points by competing in different types of battles, and host a toy tournament party.</li>
-<li>Scan a Beyblade Burst Energy Layer to unlock Bluetooth enabled digital controls within the app, where you can swipe left or right onscreen to change spin direction and speed of your top, charge up power during battle, and unleash mighty Avatar attacks.</li>
-<li>Experience the new Beyblade Burst Turbo Slingshock system, which features a rail system that propels digital tops through the Beystadium rails and into the Battle Ring for special power-up bonuses.</li>
-</ul>
- <h3>How to Download and Install Beyblade Burst App</h3>
- <p>The Beyblade Burst App is compatible with select Android and iOS devices. You can check the compatibility list on the official website or on the app store page. To download and install the app on your device, follow these steps:</p>
- <h4>For Android Devices</h4>
- <ol>
-<li>Go to the Google Play Store on your device or click <a href="(^1^)">here</a>.</li>
-<li>Search for "Beyblade Burst App" or tap on this <a href="(^1^)">link</a>.</li>
-<li>Tap on "Install" and wait for the app to download.</li>
-<li>Once the download is complete, tap on "Open" to launch the app.</li>
-<li>Follow the on-screen instructions to set up your account and start playing.</li>
-</ol>
- <h4>For iOS Devices</h4>
- <ol>
-<li>Go to the App Store on your device or click <a href="">here</a>.</li>
-<li>Search for "Beyblade Burst App" or tap on this <a href="">link</a>.</li>
-<li>Tap on "Get" and enter your Apple ID password or use Touch ID or Face ID to confirm.</li>
-<li>Wait for the app to download and install.</li>
-<li>Once the installation is done, tap on the app icon to open it.</li>
-<li>Follow the on-screen instructions to set up your account and start playing.</li>
-</ol>
- <h2>How to Play Beyblade Burst App</h2>
- <p>The Beyblade Burst App is easy to play and has a user-friendly interface. Here are some of the basic steps to play the game:</p>
- <h3>Create and Customize Your Beyblade Burst Tops</h3>
- <p>The first thing you need to do is to create your own Beyblade Burst top. You can choose from hundreds of different parts and colors, and mix and match them to create your unique combination. You can also scan a real-life Beyblade Burst top using your device's camera to unlock it in the game. To create and customize your top, follow these steps:</p>
- <ol>
-<li>Tap on the "Create" button on the main menu.</li>
-<li>Select a Bey type: Attack, Defense, Stamina, or Balance.</li>
-<li>Select an Energy Layer, a Forge Disc, and a Performance Tip from the available options. You can also tap on the "Randomize" button to get a random combination.</li>
-<li>Tap on the "Customize" button to change the colors of your parts. You can also tap on the "Swap" button to switch parts with another top.</li>
-<li>Tap on the "Save" button to save your top. You can also tap on the "Edit" button to rename your top or delete it.</li>
-</ol>
- <h3>Challenge Your Friends and Other Players Online</h3>
- <p>The Beyblade Burst App allows you to challenge your friends and other players from around the world in online battles. You can also chat with them, send them gifts, and view their profiles. To challenge someone online, follow these steps:</p>
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- <ol>
-<li>Tap on the "Battle" button on the main menu.</li>
-<li>Select a battle mode: Quick Match, League Match, or Friendly Match.</li>
-<li>Select a Bey Stadium: Basic Stadium, Slingshock Stadium, or Digital Stadium.</li>
-<li>Select a Beyblade Burst top from your collection or scan a new one.</li>
-<li>Wait for an opponent to join or invite someone from your friends list or league.</li>
-<li>When the battle starts, swipe up on the screen to launch your top. You can also tilt your device to steer your top.</li>
-<li>Tap on the screen to charge up power and unleash special moves and power-ups. You can also tap on the avatar icon of your top to activate its Avatar Attack.</li>
-<li>The battle ends when one of the tops bursts, stops spinning, or falls out of the stadium. The winner gets points and rewards based on their performance.</li>
-</ol>
- <h3>Join or Create a Battle League</h3>
- <p>The Beyblade Burst App also lets you join or create a battle league of your own, where you can compete with other players in different types of battles and earn points. You can also host a toy tournament party with your friends using real-life Beyblade Burst tops and scan their results into the app. To join or create a league, follow these steps:</p>
- <ol>
-<li>Tap on the "League" button on the main menu.</li>
-<li>Select an option: Join a League or Create a League.</li>
-<li>If you want to join a league, browse through the available leagues and tap on one that interests you. You can also search for a league by name or code. Then, tap on the "Join" button and wait for approval from the league owner.</li>
-<li>If you want to create a league, tap on the "Create" button and enter a name, description, code, season length, and battle type for your league. Then, tap on the "Create" button again and invite your friends or other players to join your league.</li>
-<li>Once you are in a league, you can view its details, members, standings, schedule, chat room, and rewards. You can also leave or delete a league at any time.</li>
-</ol>
- <h3>Scan and Control Bluetooth Enabled Beyblade Burst Tops</h3> <p>The Beyblade Burst App also supports Bluetooth enabled Beyblade Burst tops, which are special tops that have a built-in chip that can connect to your device via Bluetooth. You can scan these tops using the app and control them with digital commands. To scan and control Bluetooth enabled tops, follow these steps:</p>
- <ol>
-<li>Make sure your device has Bluetooth turned on and is compatible with the app.</li>
-<li>Tap on the "Scan" button on the main menu and select "Bluetooth Scan".</li>
-<li>Hold your device over the Energy Layer of the Bluetooth enabled top and wait for the app to recognize it.</li>
-<li>Once the top is scanned, you can view its details, customize its parts and colors, and add it to your collection.</li>
-<li>To control the top, tap on the "Battle" button and select "Bluetooth Battle".</li>
-<li>Select a Bey Stadium and a Bluetooth enabled top from your collection.</li>
-<li>Wait for an opponent to join or invite someone from your friends list or league who also has a Bluetooth enabled top.</li>
-<li>When the battle starts, swipe left or right on the screen to change the spin direction and speed of your top. You can also tap on the screen to charge up power and unleash special moves and power-ups. You can also tap on the avatar icon of your top to activate its Avatar Attack.</li>
-<li>The battle ends when one of the tops bursts, stops spinning, or falls out of the stadium. The winner gets points and rewards based on their performance.</li>
-</ol>
- <h3>Use Special Moves and Power-Ups</h3>
- <p>The Beyblade Burst App also features special moves and power-ups that you can use during battles to gain an edge over your opponent. These include:</p>
- <ul>
-<li>Avatar Attack: This is a powerful move that unleashes the avatar of your top, which can deal massive damage to your opponent's top. To use this move, you need to fill up the Avatar Meter by tapping on the screen during battle. Once the meter is full, tap on the avatar icon of your top and watch it unleash its fury.</li>
-<li>Burst Finish: This is a move that causes your opponent's top to burst instantly, giving you an automatic win. To use this move, you need to fill up the Burst Meter by dealing damage to your opponent's top during battle. Once the meter is full, tap on it and watch your opponent's top explode.</li>
-<li>Slingshock Power-Up: This is a power-up that boosts your top's speed and attack power when it enters the Slingshock Stadium. To use this power-up, you need to launch your top with enough force to make it ride on the rails of the stadium. Once it does, it will gain a blue aura and become more powerful.</li>
-</ul>
- <h2>Tips and Tricks for Beyblade Burst App</h2>
- <p>The Beyblade Burst App is a fun and exciting game, but it can also be challenging at times. Here are some tips and tricks to help you improve your skills and win more battles:</p>
- <h3>Know Your Bey Types and Their Advantages</h3>
- <p>The Beyblade Burst App features four types of Beyblade Burst tops: Attack, Defense, Stamina, and Balance. Each type has its own strengths and weaknesses, and knowing them can help you choose the best top for each battle. Here is a brief overview of each type:</p>
- <table>
-<tr><th>Type</th><th>Description</th><th>Advantage</th><th>Disadvantage</th></tr>
-<tr><td>Attack</td><td>These are aggressive tops that have high speed and attack power. They are designed to deal heavy damage to their opponents and burst them quickly.</td><td>They can overwhelm their opponents with powerful hits and bursts.</td><td>They have low stamina and defense, which makes them vulnerable to counterattacks and outlasting.</td></tr>
-<tr><td>Defense</td><td>These are defensive tops that have high durability and stability. They are designed to withstand attacks from their opponents and survive longer in battles.</td><td>They can resist bursts and knockouts from their opponents.</td><td>They have low speed and attack power, which makes them less effective at dealing damage and bursting their opponents.</td></tr>
-<tr><td>Stamina</td><td>These are endurance tops that have high spin time and balance. They are designed to outlast their opponents in long battles by spinning longer than them.</td><td>They can win by spin finish or by draining their opponents' stamina.</td><td>They have low attack power and defense, which makes them susceptible to bursts and knockouts from their opponents.</td></tr>
-<tr><td>Balance</td><td>These are versatile tops that have a mix of speed, attack power, durability, and stability. They are designed to adapt to different situations and opponents in battles.</td><td>They can perform well in any battle mode and stadium.</td><td>They have no clear advantage or disadvantage over any other type, which makes them unpredictable and inconsistent.</td></tr>
-</table>
- <p>Knowing your Bey type and its advantages can help you choose the best top for each battle. You can also use this knowledge to counter your opponent's type and exploit their weakness. For example, if you are facing an Attack type, you can use a Defense type to resist their hits and burst them. If you are facing a Defense type, you can use a Stamina type to outlast them and win by spin finish. If you are facing a Stamina type, you can use an Attack type to deal heavy damage and burst them. If you are facing a Balance type, you can use any type that suits your play style and strategy.</p>
- <h3>Master Different Launch Techniques</h3>
- <p>The way you launch your top can also affect the outcome of the battle. Different launch techniques can give your top different spin directions, speeds, angles, and trajectories, which can influence its performance and behavior in the stadium. Here are some of the launch techniques you can try:</p>
- <ul>
-<li>Standard Launch: This is the basic launch technique that gives your top a normal spin direction and speed. To perform this launch, swipe up on the screen with moderate force and aim for the center of the stadium.</li>
-<li>Sliding Shoot: This is a launch technique that gives your top a curved trajectory and more speed. To perform this launch, swipe up on the screen with more force and angle your swipe slightly to the left or right, depending on your top's spin direction.</li>
-<li>Banking Shoot: This is a launch technique that gives your top a high angle and more attack power. To perform this launch, swipe up on the screen with more force and aim for the edge of the stadium.</li>
-<li>Counter Break: This is a launch technique that gives your top a reverse spin direction and more defense power. To perform this launch, swipe down on the screen with moderate force and aim for the center of the stadium.</li>
-<li>Slingshock Launch: This is a launch technique that gives your top a boost of speed and power when it enters the Slingshock Stadium. To perform this launch, swipe up on the screen with more force and aim for the rails of the stadium.</li>
-</ul>
- <p>Mastering different launch techniques can help you gain an edge over your opponent and surprise them with unexpected moves. You can also experiment with different combinations of launch techniques and Bey types to find your best match.</p>
- <h3>Upgrade Your Beys and Unlock New Parts</h3>
- <p>The Beyblade Burst App also allows you to upgrade your Beys and unlock new parts by playing the game and earning rewards. Upgrading your Beys can improve their stats and abilities, while unlocking new parts can give you more options for customization. Here are some of the ways you can upgrade your Beys and unlock new parts:</p>
- <ul>
-<li>Level Up: You can level up your Beys by using them in battles and gaining experience points. Leveling up your Beys can increase their attack, defense, stamina, speed, agility, burst resistance, weight, size, and avatar power.</li>
-<li>Earn Coins: You can earn coins by winning battles, completing quests, watching ads, or buying them with real money. You can use coins to buy new parts from the shop or upgrade your existing parts.</li>
-<li>Earn Gems: You can earn gems by completing achievements, participating in events, or buying them with real money. You can use gems to buy premium parts from the shop or unlock special features in the game.</li>
-<li>Earn Beycoins: You can earn beycoins by playing in league matches or tournaments. You can use beycoins to buy exclusive parts from the league shop or enter higher-level tournaments.</li>
-<li>Earn Gifts: You can earn gifts by playing daily, inviting friends, or receiving them from other players. Gifts can contain coins, gems, beycoins, parts, or other items.</li>
-</ul>
- <p>Upgrading your Beys and unlocking new parts can help you enhance your performance and expand your collection. You can also trade parts with other players or sell them for coins if you have duplicates or unwanted ones.</p>
- <h3>Earn Rewards and Gifts by Playing Daily</h3>
- <p>The Beyblade Burst App also rewards you for playing daily by giving you various rewards and gifts. These include:</p>
- <ul>
-<li>Daily Login Bonus: You can get a daily login bonus by logging in to the game every day. The bonus can be coins, gems, beycoins, parts, or other items. The bonus increases every day until it resets on the seventh day.</li>
-<li>Daily Quest Bonus: You can get a daily quest bonus by completing three quests every day. The quests can be related to battles, leagues, tournaments, or other activities. The bonus can be coins, gems, beycoins, parts, or other items.</li>
-<li>Daily Spin: You can get a daily spin bonus by spinning a wheel every day. The wheel can give you coins, gems, beycoins, parts, or other items. You can also get extra spins by watching ads or spending gems.</li>
-<li>Daily Gift: You can get a daily gift bonus by opening a gift box every day. The gift box can contain coins, gems, beycoins, parts, or other items. You can also get extra gift boxes by watching ads or spending gems.</li>
-</ul>
- <p>Earning rewards and gifts by playing daily can help you get more resources and items for your Beys and your game. You can also share your rewards and gifts with your friends or other players to show your generosity and appreciation.</p>
- <h2>Conclusion</h2>
- <p>The Beyblade Burst App is a great game for fans of the Beyblade franchise and for anyone who enjoys spinning tops and battling games. The game offers a lot of features, content, and customization options that make it fun and engaging for players of all ages. The game also allows you to connect with your friends and other players from around the world in online battles, leagues, and tournaments. The game is easy to play and has a user-friendly interface, but it also requires skill and strategy to master. The game is compatible with select Android and iOS devices and is available for free on the app stores. However, the game also offers in-app purchases for some items and features. If you want to download and install the Beyblade Burst App on your device, follow the steps in this article and start playing today.</p>
- <h2>FAQs</h2>
- <p>Here are some of the frequently asked questions about the Beyblade Burst App:</p>
- <ol>
-<li>Q: How do I update the Beyblade Burst App?</li>
-<li>A: To update the Beyblade Burst App, go to the app store on your device and check if there is a new version available. If there is, tap on the "Update" button and wait for the app to download and install. You can also enable automatic updates on your device settings to get the latest version of the app automatically.</li>
-<li>Q: How do I reset the Beyblade Burst App?</li>
-<li>A: To reset the Beyblade Burst App, go to the settings menu on the app and tap on the "Reset" button. This will erase all your data and progress in the game and start from scratch. You can also delete and reinstall the app on your device to reset it.</li>
-<li>Q: How do I contact the Beyblade Burst App support team?</li>
-<li>A: To contact the Beyblade Burst App support team, go to the settings menu on the app and tap on the "Help" button. This will take you to a page where you can find FAQs, tutorials, feedback forms, and contact information for the support team.</li>
-<li>Q: How do I report a bug or a problem in the Beyblade Burst App?</li>
-<li>A: To report a bug or a problem in the Beyblade Burst App, go to the settings menu on the app and tap on the "Feedback" button. This will take you to a form where you can describe your issue and attach screenshots if needed. You can also email your report to [email protected].</li>
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-<li>A: To get more coins, gems, beycoins, parts, or other items in the Beyblade Burst App, you can do any of the following:</li>
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-<li>Buy them with real money through in-app purchases.</li>
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-<li>Receive them as gifts from your friends or other players.</li>
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spaces/1phancelerku/anime-remove-background/Download Battle Playground Simulator Mod APK and Experience the Ultimate Battle Simulation.md

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-<p>To download Battle Playground Simulator Mod APK, you need to find a trusted source that offers the latest version of the file <h3>The steps to download the APK file from a trusted source</h3>
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-<li>Toggle on the option for Unknown Sources.</li>
-<li>Tap OK to confirm.</li>
-</ul>
-<p>Note: The exact steps may vary depending on your device model and Android version. You can also check this guide for more details.</p>
-<h3>The steps to install the APK file and launch the game</h3>
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-<ul>
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-</ul>
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- <h2>Frequently Asked Questions</h2>
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spaces/2023Liu2023/bingo/src/components/ui/dropdown-menu.tsx

@@ -1,128 +0,0 @@
-'use client'
-
-import * as React from 'react'
-import * as DropdownMenuPrimitive from '@radix-ui/react-dropdown-menu'
-
-import { cn } from '@/lib/utils'
-
-const DropdownMenu = DropdownMenuPrimitive.Root
-
-const DropdownMenuTrigger = DropdownMenuPrimitive.Trigger
-
-const DropdownMenuGroup = DropdownMenuPrimitive.Group
-
-const DropdownMenuPortal = DropdownMenuPrimitive.Portal
-
-const DropdownMenuSub = DropdownMenuPrimitive.Sub
-
-const DropdownMenuRadioGroup = DropdownMenuPrimitive.RadioGroup
-
-const DropdownMenuSubContent = React.forwardRef<
-  React.ElementRef<typeof DropdownMenuPrimitive.SubContent>,
-  React.ComponentPropsWithoutRef<typeof DropdownMenuPrimitive.SubContent>
->(({ className, ...props }, ref) => (
-  <DropdownMenuPrimitive.SubContent
-    ref={ref}
-    className={cn(
-      'z-50 min-w-[8rem] overflow-hidden rounded-md border bg-popover p-1 text-popover-foreground shadow-md animate-in data-[side=bottom]:slide-in-from-top-1 data-[side=left]:slide-in-from-right-1 data-[side=right]:slide-in-from-left-1 data-[side=top]:slide-in-from-bottom-1',
-      className
-    )}
-    {...props}
-  />
-))
-DropdownMenuSubContent.displayName =
-  DropdownMenuPrimitive.SubContent.displayName
-
-const DropdownMenuContent = React.forwardRef<
-  React.ElementRef<typeof DropdownMenuPrimitive.Content>,
-  React.ComponentPropsWithoutRef<typeof DropdownMenuPrimitive.Content>
->(({ className, sideOffset = 4, ...props }, ref) => (
-  <DropdownMenuPrimitive.Portal>
-    <DropdownMenuPrimitive.Content
-      ref={ref}
-      sideOffset={sideOffset}
-      className={cn(
-        'z-50 min-w-[8rem] overflow-hidden rounded-md border bg-popover p-1 text-popover-foreground shadow animate-in data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2',
-        className
-      )}
-      {...props}
-    />
-  </DropdownMenuPrimitive.Portal>
-))
-DropdownMenuContent.displayName = DropdownMenuPrimitive.Content.displayName
-
-const DropdownMenuItem = React.forwardRef<
-  React.ElementRef<typeof DropdownMenuPrimitive.Item>,
-  React.ComponentPropsWithoutRef<typeof DropdownMenuPrimitive.Item> & {
-    inset?: boolean
-  }
->(({ className, inset, ...props }, ref) => (
-  <DropdownMenuPrimitive.Item
-    ref={ref}
-    className={cn(
-      'relative flex cursor-default select-none items-center rounded-sm px-2 py-1.5 text-sm outline-none transition-colors focus:bg-accent focus:text-accent-foreground data-[disabled]:pointer-events-none data-[disabled]:opacity-50',
-      inset && 'pl-8',
-      className
-    )}
-    {...props}
-  />
-))
-DropdownMenuItem.displayName = DropdownMenuPrimitive.Item.displayName
-
-const DropdownMenuLabel = React.forwardRef<
-  React.ElementRef<typeof DropdownMenuPrimitive.Label>,
-  React.ComponentPropsWithoutRef<typeof DropdownMenuPrimitive.Label> & {
-    inset?: boolean
-  }
->(({ className, inset, ...props }, ref) => (
-  <DropdownMenuPrimitive.Label
-    ref={ref}
-    className={cn(
-      'px-2 py-1.5 text-sm font-semibold',
-      inset && 'pl-8',
-      className
-    )}
-    {...props}
-  />
-))
-DropdownMenuLabel.displayName = DropdownMenuPrimitive.Label.displayName
-
-const DropdownMenuSeparator = React.forwardRef<
-  React.ElementRef<typeof DropdownMenuPrimitive.Separator>,
-  React.ComponentPropsWithoutRef<typeof DropdownMenuPrimitive.Separator>
->(({ className, ...props }, ref) => (
-  <DropdownMenuPrimitive.Separator
-    ref={ref}
-    className={cn('-mx-1 my-1 h-px bg-muted', className)}
-    {...props}
-  />
-))
-DropdownMenuSeparator.displayName = DropdownMenuPrimitive.Separator.displayName
-
-const DropdownMenuShortcut = ({
-  className,
-  ...props
-}: React.HTMLAttributes<HTMLSpanElement>) => {
-  return (
-    <span
-      className={cn('ml-auto text-xs tracking-widest opacity-60', className)}
-      {...props}
-    />
-  )
-}
-DropdownMenuShortcut.displayName = 'DropdownMenuShortcut'
-
-export {
-  DropdownMenu,
-  DropdownMenuTrigger,
-  DropdownMenuContent,
-  DropdownMenuItem,
-  DropdownMenuLabel,
-  DropdownMenuSeparator,
-  DropdownMenuShortcut,
-  DropdownMenuGroup,
-  DropdownMenuPortal,
-  DropdownMenuSub,
-  DropdownMenuSubContent,
-  DropdownMenuRadioGroup
-}

spaces/AIFILMS/generate_human_motion/README.md

@@ -1,14 +0,0 @@
----
-title: Generate Human Motion
-emoji: 🏃
-colorFrom: green
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.16.2
-app_file: app.py
-pinned: false
-license: apache-2.0
-duplicated_from: vumichien/generate_human_motion
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/AIFILMS/generate_human_motion/VQ-Trans/models/rotation2xyz.py

@@ -1,92 +0,0 @@
-# This code is based on https://github.com/Mathux/ACTOR.git
-import torch
-import utils.rotation_conversions as geometry
-
-
-from models.smpl import SMPL, JOINTSTYPE_ROOT
-# from .get_model import JOINTSTYPES
-JOINTSTYPES = ["a2m", "a2mpl", "smpl", "vibe", "vertices"]
-
-
-class Rotation2xyz:
-    def __init__(self, device, dataset='amass'):
-        self.device = device
-        self.dataset = dataset
-        self.smpl_model = SMPL().eval().to(device)
-
-    def __call__(self, x, mask, pose_rep, translation, glob,
-                 jointstype, vertstrans, betas=None, beta=0,
-                 glob_rot=None, get_rotations_back=False, **kwargs):
-        if pose_rep == "xyz":
-            return x
-
-        if mask is None:
-            mask = torch.ones((x.shape[0], x.shape[-1]), dtype=bool, device=x.device)
-
-        if not glob and glob_rot is None:
-            raise TypeError("You must specify global rotation if glob is False")
-
-        if jointstype not in JOINTSTYPES:
-            raise NotImplementedError("This jointstype is not implemented.")
-
-        if translation:
-            x_translations = x[:, -1, :3]
-            x_rotations = x[:, :-1]
-        else:
-            x_rotations = x
-
-        x_rotations = x_rotations.permute(0, 3, 1, 2)
-        nsamples, time, njoints, feats = x_rotations.shape
-
-        # Compute rotations (convert only masked sequences output)
-        if pose_rep == "rotvec":
-            rotations = geometry.axis_angle_to_matrix(x_rotations[mask])
-        elif pose_rep == "rotmat":
-            rotations = x_rotations[mask].view(-1, njoints, 3, 3)
-        elif pose_rep == "rotquat":
-            rotations = geometry.quaternion_to_matrix(x_rotations[mask])
-        elif pose_rep == "rot6d":
-            rotations = geometry.rotation_6d_to_matrix(x_rotations[mask])
-        else:
-            raise NotImplementedError("No geometry for this one.")
-
-        if not glob:
-            global_orient = torch.tensor(glob_rot, device=x.device)
-            global_orient = geometry.axis_angle_to_matrix(global_orient).view(1, 1, 3, 3)
-            global_orient = global_orient.repeat(len(rotations), 1, 1, 1)
-        else:
-            global_orient = rotations[:, 0]
-            rotations = rotations[:, 1:]
-
-        if betas is None:
-            betas = torch.zeros([rotations.shape[0], self.smpl_model.num_betas],
-                                dtype=rotations.dtype, device=rotations.device)
-            betas[:, 1] = beta
-            # import ipdb; ipdb.set_trace()
-        out = self.smpl_model(body_pose=rotations, global_orient=global_orient, betas=betas)
-
-        # get the desirable joints
-        joints = out[jointstype]
-
-        x_xyz = torch.empty(nsamples, time, joints.shape[1], 3, device=x.device, dtype=x.dtype)
-        x_xyz[~mask] = 0
-        x_xyz[mask] = joints
-
-        x_xyz = x_xyz.permute(0, 2, 3, 1).contiguous()
-
-        # the first translation root at the origin on the prediction
-        if jointstype != "vertices":
-            rootindex = JOINTSTYPE_ROOT[jointstype]
-            x_xyz = x_xyz - x_xyz[:, [rootindex], :, :]
-
-        if translation and vertstrans:
-            # the first translation root at the origin
-            x_translations = x_translations - x_translations[:, :, [0]]
-
-            # add the translation to all the joints
-            x_xyz = x_xyz + x_translations[:, None, :, :]
-
-        if get_rotations_back:
-            return x_xyz, rotations, global_orient
-        else:
-            return x_xyz

spaces/Abhay834/SY_Bot/app.py

@@ -1,203 +0,0 @@
-import os
-import gradio as gr
-from langchain.chat_models import ChatOpenAI
-from langchain import LLMChain, PromptTemplate
-from langchain.memory import ConversationBufferMemory
-
-OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
-
-template = """meet SYIT  it can have all data about a SY student and also assist like digital assistance
-data of the student is  following
-'Roll no 1  Name  ABHANG ANIKET RAJENDRA having prn no UIT22M1001'
-'Roll no 2  Name AHER PRASHANT RAYCHAND   having prn no UIT22M1002'
-'Roll no 3  Name  AHIRE HARSHADA BANICHANDhaving prn no UIT22M1003'
-'Roll no 4  Name  AMALE ADITYA MAHADEO having prn no UIT22M1004'
-'Roll no 5  Name AMALE ADITYA MAHADEO    having prn no UIT22M1005'
-'Roll no 6  Name ARGADE PANKAJ SOMNATH having prn no UIT22M1006'
-'Roll no 7  Name ARGADE PANKAJ SOMNATH having prn no UIT22M1007'
-'Roll no 8  Name AVHAD PRAVIN SOMNATH  having prn no UIT22M1008'
-'Roll no 9  Name  BADADHE ABHISHEK VIJAY having prn no UIT22M1009'"
-'Roll no 10  Name BADAKH ANIKET RAMESH having prn no UIT22M1010'
-'Roll no 11 Name BADGUJAR MANISH DIPAK having prn no UIT22M1011'
-'Roll no 12 Name  BHAGWAT SHREYASH SHRIDHAhaving prn no UIT22M1012'
-R.NO
-ROLL
-NO
-ELIGI.NO PRN CANDIDATE NAME M/F GR.NO
-1
-1 12022186614UIT22M1001ABHANG ANIKET RAJENDRA M 221020589
-2
-2 12022186732UIT22M1002AHER PRASHANT RAYCHAND (T M 221020590
-3
-3 12022186610UIT22M1003AHER YASHRAJ BALASAHEB M 221020591
-4
-4 12022186697UIT22F1004 AHIRE HARSHADA BANICHAND F 221020592
-5
-5 12022186622UIT22M1005AMALE ADITYA MAHADEO M 221020593
-6
-6 12022186644UIT22M1006ARGADE PANKAJ SOMNATH M 221020594
-7
-7 12022186703UIT22F1007 ATHARE SNEHAL GUNWANT F 221020595
-8
-8 12022186637UIT22M1008AVHAD PRAVIN SOMNATH M 221020596
-9
-9 12022186660UIT22M1009BADADHE ABHISHEK VIJAY M 221020597
-10
-10 12022186649UIT22M1010BADAKH ANIKET RAMESH M 221020598
-11
-11 12022186608UIT22M1011BADGUJAR MANISH DIPAK M 221020599
-12
-12 12022186655UIT22M1014BHAGWAT SHREYASH SHRIDHA M 221020600
-13
-13 12022186733UIT22M1015BHAVAR ATHARVA SANJAY (EW M 221020601
-14
-14 12022186669UIT22M1016BHAVARI SANKET DILIP M 221020602
-15
-15 12022186623UIT22M1017BHAVSAR SHANTANU KISHOR M 221020603 #REF!
-16
-16 12022186631UIT22M1018BHAWAR UDAYANRAJE VIJAYKU M 221020604
-17
-17 12022186714UIT22M1019BHOJANE SAGAR RAGHUNATH M 221020605
-18
-18 12022186605UIT22F1020 BHOR NIKITA BHASKAR F 221020606
-19
-19 12022186672UIT22M1021BHUJADE SARVESHWAR
-SURESH
-M 221020607
-20
-20 12022186704UIT22F1022 BHUSARI SHATAKSHI SATISH F 221020608
-21
-21 12022186643UIT22M1023BORDE ABHAY SANTOSH M 221020609
-22
-22 12022186709UIT22M1024BORKAR SAHIL MANISH M 221020610
-23
-23 12022186650UIT22M1013BAGWAN MAUZZAM SAMEER M 221020611
-24
-24 12022186639UIT22M1025BORSE VEDANT SACHIN M 221020612
-25
-25 12022186645UIT22M1026BULKUNDE PRATIK BHAUSAHEB M 221020613
-26
-26 12022186647UIT22M1027CHAUDHARI MAHESH SANJAY M 221020614
-27
-27 12022186675UIT22F1028 CHAVAN AARYA AVINASH F 221020615
-28
-28 12022186620UIT22M1029CHAVAN NIKHIL NILESH M 221020616
-29
-29 12022186729UIT22M1030DAHE MAHESH DAULAT (TFW M 221020617
-30
-30 12022186633UIT22F1031 DAINE KALYANI YADAV F 221020618
-31
-31 12022186642UIT22M1012BADHE OM SAMBHAJI M 221020619
-32
-32 12022186688UIT22F1033 DESHMUKH SANSKRUTI RAVI F 221020621
-33
-33 12022186701UIT22M1034DESHPANDE ATHARVA
-RAJENDRA
-M 221020622
-34
-34 12022186604UIT22F1035 DEVARE VAIBHAVI RAJENDRA F 221020623
-35
-35 12022186691UIT22F1036 DHAKNE DISHA BIPIN F 221020624
-36
-36 12022186632UIT22M1037DHAMDHERE TANMAY DATTATRA M 221020625
-37
-37 12022186689UIT22M1038DHOKCHAULE ADITYA
-SUDHAKAR
-M 221020626
-38
-38 12022186619UIT22M1039DOPHE VINIT BALASAHEB M 221020627
-39
-39 12022186626UIT22M1040GADHE SHIVAM RAMESHWAR M 221020628
-40
-40 12022186719UIT22F1041 GAGARE NIKITA BALASAHEB F 221020629
-41
-41 12022186710UIT22M1042GAGARE PRANAV KISHOR M 221020630
-42
-42 12022186724UIT22M1043GAIKWAD PRASAD SUNIL (EW M 221020631
-43
-43 12022186706UIT22M1044GAIKWAD SACHIN PANDURANG M 221020632
-44
-44 12022186681UIT22M1045GANGURDE SHUBHAM SANTOS M 221020633
-45
-45 12022186613UIT22F1056 JADHAV MAYURI RUSHIRAJ F 221020634
-46
-46 12022186731UIT22M1046GAVHANE ADESH BAJIRAO (EW M 221020635
-47
-47 12022186708UIT22F1047 GAWALI TEJASHREE
-TULSHIDAS
-F 221020636
-48
-48 12022186624UIT22M1048GHUSALE GAURAV SHAMRAO M 221020637
-49
-49 12022186665UIT22M1049GORDE MUKUND GOPINATH M 221020638
-50
-50 12022186670UIT22M1050GULDAGAD RUSHIKESH
-SANJAY
-M 221020639
-51
-51 12022186648UIT22M1053HON RITESH JAYANAND M 221020642
-52
-52 12022186616UIT22M1054HON SHANTANU M 221020643
-53
-53 12022186609UIT22F1134 VADANE AMRUTA SAKHARAM F 221020644
-54
-54 12022186654UIT22F1055 IMALE BHAKTI PANDIT F 221020645
-55
-55 12022186668UIT22M1057JADHAV UTKARSH SUNIL M 221020646
-56
-56 12022186734UIT22M1058JAGTAP ADITYA RAMBHAU (EW M 221020647
-57
-57 12022186625UIT22F1059 JAGTAP VAISHNAVI VIJAY F 221020648
-58
-58 12022186611UIT22M1060JARE KAUSHAL SANDIP M 221020649
-59
-59 12022186698UIT22F1061 KADAM DNYANESHWARI BALASA F 221020650
-60
-60 12022186735UIT22M1062KADAM RUTVIK RAVINDRA (EW M 221020651
-61
-61 12022186612UIT22F1063 KADAM SANTOSHI PANDIT F 221020652
-62
-62 12022186696UIT22M1064KAKADE SANJYOT SANDEEP M 221020653
-63
-63 12022186671UIT22F1065 KALE PRAJAKTA GORAKSHANAT F 221020654
-64
-64 12022186657UIT22M1066KANDALKAR ADITYA PRAKASH M 221020655
-65
-65 12022186682UIT22M1067KANGUDE SUYASH
-HAUSHABAPU
-M 221020656
-66
-66 1202120608UIT21M1038LANDE YOGESH CHANDRAKANT M 211019642
-67
-67 1202120608UIT21M1061SHELKE MAYANK VIJAYKUMAR M 211019665
-68 68 12022186969UEC22F1039MATE SONIYA SATISH F 221020420 200
-69
-69 2022186405UEE22F100BHINGARE SAKSHI DATTATRAY F 2
- 
- {chat_history}
-
-User: {user_message}
-Chatbot:"""
-
-prompt = PromptTemplate(
-    input_variables=["chat_history", "user_message"], template=template
-)
-
-memory = ConversationBufferMemory(memory_key="chat_history")
-
-llm_chain = LLMChain(
-    llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
-    prompt=prompt,
-    verbose=True,
-    memory=memory,
-)
-
-def get_text_response(user_message,history):
-    response = llm_chain.predict(user_message = user_message)
-    return response
-
-demo = gr.ChatInterface(get_text_response)
-
-if __name__ == "__main__":
-    demo.launch() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.
-

spaces/Adapter/T2I-Adapter/docs/FAQ.md

@@ -1,5 +0,0 @@
-# FAQ
-
-- **Q: The openpose adapter (t2iadapter_openpose_sd14v1) outputs gray-scale images.**
-
-    **A:** You can add `colorful` in the prompt to avoid this problem.

spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/basesizer/ScaleMethods.js

@@ -1,121 +0,0 @@
-import PopUp from '../../../plugins/popup.js';
-import ScaleDownDestroy from '../../../plugins/scale-down-destroy.js';
-import Yoyo from '../../../plugins/behaviors/scale/Yoyo.js';
-import { WaitComplete } from '../utils/WaitEvent.js'
-import GetParentSizerMethods from './GetParentSizerMethods.js';
-
-const IsPlainObject = Phaser.Utils.Objects.IsPlainObject;
-
-var OnInitScale = function (gameObject, scale) {
-    // Route 'complete' of scale to gameObject
-    scale.completeEventName = undefined;
-    scale.on('complete', function () {
-        if (scale.completeEventName) {
-            gameObject.emit(scale.completeEventName, gameObject);
-            scale.completeEventName = undefined;
-        }
-    })
-
-    // Update local state
-    scale.on('update', function () {
-        var parent = GetParentSizerMethods.getParentSizer(gameObject)
-        if (parent) {
-            parent.resetChildPositionState(gameObject);
-        }
-    })
-}
-
-export default {
-    popUp(duration, orientation, ease) {
-        if (IsPlainObject(duration)) {
-            var config = duration;
-            duration = config.duration;
-            orientation = config.orientation;
-            ease = config.ease;
-        }
-
-        var isInit = (this._scaleBehavior === undefined);
-
-        this._scaleBehavior = PopUp(this, duration, orientation, ease, this._scaleBehavior);
-
-        if (isInit) {
-            OnInitScale(this, this._scaleBehavior);
-        }
-
-        this._scaleBehavior.completeEventName = 'popup.complete';
-
-        return this;
-    },
-
-    popUpPromise(duration, orientation, ease) {
-        this.popUp(duration, orientation, ease);
-        return WaitComplete(this._scaleBehavior);
-    },
-
-    scaleDownDestroy(duration, orientation, ease, destroyMode) {
-        if (IsPlainObject(duration)) {
-            var config = duration;
-            duration = config.duration;
-            orientation = config.orientation;
-            ease = config.ease;
-            destroyMode = config.destroy;
-        }
-
-        var isInit = (this._scaleBehavior === undefined);
-
-        this._scaleBehavior = ScaleDownDestroy(this, duration, orientation, ease, destroyMode, this._scaleBehavior);
-
-        if (isInit) {
-            OnInitScale(this, this._scaleBehavior);
-        }
-
-        this._scaleBehavior.completeEventName = 'scaledown.complete';
-
-        return this;
-    },
-
-    scaleDownDestroyPromise(duration, orientation, ease, destroyMode) {
-        this.scaleDownDestroy(duration, orientation, ease, destroyMode);
-        return WaitComplete(this._scaleBehavior);
-    },
-
-    scaleDown(duration, orientation, ease) {
-        this.scaleDownDestroy(duration, orientation, ease, false);
-        return this;
-    },
-
-    scaleDownPromise(duration, orientation, ease) {
-        this.scaleDown(duration, orientation, ease);
-        return WaitComplete(this._scaleBehavior);
-    },
-
-    scaleYoyo(duration, peakValue, repeat, orientation, ease) {
-        if (IsPlainObject(duration)) {
-            var config = duration;
-            duration = config.duration;
-            peakValue = config.peakValue;
-            repeat = config.repeat;
-            orientation = config.orientation;
-            ease = config.ease;
-        }
-
-        var isInit = (this._scaleBehavior === undefined);
-
-        this._scaleBehavior = Yoyo(this, duration, peakValue, repeat, orientation, ease, this._scaleBehavior);
-
-        if (isInit) {
-            OnInitScale(this, this._scaleBehavior);
-        }
-
-        this._scaleBehavior.completeEventName = 'scaleyoyo.complete';
-
-        return this;
-    },
-
-    scaleYoyoPromise(duration, peakValue, repeat, orientation, ease) {
-        this.scaleYoyo(duration, peakValue, repeat, orientation, ease);
-        return WaitComplete(this._scaleBehavior);
-    },
-
-
-}

spaces/Aki004/herta-so-vits/onnx_export.py

@@ -1,56 +0,0 @@
-import torch
-from onnxexport.model_onnx import SynthesizerTrn
-import utils
-
-def main(NetExport):
-    path = "SoVits4.0"
-    if NetExport:
-        device = torch.device("cpu")
-        hps = utils.get_hparams_from_file(f"checkpoints/{path}/config.json")
-        SVCVITS = SynthesizerTrn(
-            hps.data.filter_length // 2 + 1,
-            hps.train.segment_size // hps.data.hop_length,
-            **hps.model)
-        _ = utils.load_checkpoint(f"checkpoints/{path}/model.pth", SVCVITS, None)
-        _ = SVCVITS.eval().to(device)
-        for i in SVCVITS.parameters():
-            i.requires_grad = False
-        
-        n_frame = 10
-        hidden_channels = 256  #(Hubert's shape[2])
-        
-        test_hidden_unit = torch.rand(1, n_frame, hidden_channels)
-        test_pitch = torch.rand(1, n_frame)
-        test_mel2ph = torch.arange(0, n_frame, dtype=torch.int64)[None] # torch.LongTensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]).unsqueeze(0)
-        test_uv = torch.ones(1, n_frame, dtype=torch.float32)
-        test_noise = torch.randn(1, 192, n_frame)
-        test_sid = torch.LongTensor([0])
-        input_names = ["c", "f0", "mel2ph", "uv", "noise", "sid"]
-        output_names = ["audio", ]
-        
-        torch.onnx.export(SVCVITS,
-                          (
-                              test_hidden_unit.to(device),
-                              test_pitch.to(device),
-                              test_mel2ph.to(device),
-                              test_uv.to(device),
-                              test_noise.to(device),
-                              test_sid.to(device)
-                          ),
-                          f"checkpoints/{path}/model.onnx",
-                          dynamic_axes={
-                              "c": [0, 1],
-                              "f0": [1],
-                              "mel2ph": [1],
-                              "uv": [1],
-                              "noise": [2],
-                          },
-                          do_constant_folding=False,
-                          opset_version=16,
-                          verbose=False,
-                          input_names=input_names,
-                          output_names=output_names)
-
-
-if __name__ == '__main__':
-    main(True)

spaces/Akmyradov/TurkmenTTSweSTT/uroman/lib/JSON/backportPP.pm

@@ -1,2806 +0,0 @@
-package # This is JSON::backportPP
-    JSON::PP;
-
-# JSON-2.0
-
-use 5.005;
-use strict;
-use base qw(Exporter);
-use overload ();
-
-use Carp ();
-use B ();
-#use Devel::Peek;
-
-use vars qw($VERSION);
-$VERSION = '2.27204';
-
-@JSON::PP::EXPORT = qw(encode_json decode_json from_json to_json);
-
-# instead of hash-access, i tried index-access for speed.
-# but this method is not faster than what i expected. so it will be changed.
-
-use constant P_ASCII                => 0;
-use constant P_LATIN1               => 1;
-use constant P_UTF8                 => 2;
-use constant P_INDENT               => 3;
-use constant P_CANONICAL            => 4;
-use constant P_SPACE_BEFORE         => 5;
-use constant P_SPACE_AFTER          => 6;
-use constant P_ALLOW_NONREF         => 7;
-use constant P_SHRINK               => 8;
-use constant P_ALLOW_BLESSED        => 9;
-use constant P_CONVERT_BLESSED      => 10;
-use constant P_RELAXED              => 11;
-
-use constant P_LOOSE                => 12;
-use constant P_ALLOW_BIGNUM         => 13;
-use constant P_ALLOW_BAREKEY        => 14;
-use constant P_ALLOW_SINGLEQUOTE    => 15;
-use constant P_ESCAPE_SLASH         => 16;
-use constant P_AS_NONBLESSED        => 17;
-
-use constant P_ALLOW_UNKNOWN        => 18;
-
-use constant OLD_PERL => $] < 5.008 ? 1 : 0;
-
-BEGIN {
-    my @xs_compati_bit_properties = qw(
-            latin1 ascii utf8 indent canonical space_before space_after allow_nonref shrink
-            allow_blessed convert_blessed relaxed allow_unknown
-    );
-    my @pp_bit_properties = qw(
-            allow_singlequote allow_bignum loose
-            allow_barekey escape_slash as_nonblessed
-    );
-
-    # Perl version check, Unicode handling is enable?
-    # Helper module sets @JSON::PP::_properties.
-    if ($] < 5.008 ) {
-        my $helper = $] >= 5.006 ? 'JSON::backportPP::Compat5006' : 'JSON::backportPP::Compat5005';
-        eval qq| require $helper |;
-        if ($@) { Carp::croak $@; }
-    }
-
-    for my $name (@xs_compati_bit_properties, @pp_bit_properties) {
-        my $flag_name = 'P_' . uc($name);
-
-        eval qq/
-            sub $name {
-                my \$enable = defined \$_[1] ? \$_[1] : 1;
-
-                if (\$enable) {
-                    \$_[0]->{PROPS}->[$flag_name] = 1;
-                }
-                else {
-                    \$_[0]->{PROPS}->[$flag_name] = 0;
-                }
-
-                \$_[0];
-            }
-
-            sub get_$name {
-                \$_[0]->{PROPS}->[$flag_name] ? 1 : '';
-            }
-        /;
-    }
-
-}
-
-
-
-# Functions
-
-my %encode_allow_method
-     = map {($_ => 1)} qw/utf8 pretty allow_nonref latin1 self_encode escape_slash
-                          allow_blessed convert_blessed indent indent_length allow_bignum
-                          as_nonblessed
-                        /;
-my %decode_allow_method
-     = map {($_ => 1)} qw/utf8 allow_nonref loose allow_singlequote allow_bignum
-                          allow_barekey max_size relaxed/;
-
-
-my $JSON; # cache
-
-sub encode_json ($) { # encode
-    ($JSON ||= __PACKAGE__->new->utf8)->encode(@_);
-}
-
-
-sub decode_json { # decode
-    ($JSON ||= __PACKAGE__->new->utf8)->decode(@_);
-}
-
-# Obsoleted
-
-sub to_json($) {
-   Carp::croak ("JSON::PP::to_json has been renamed to encode_json.");
-}
-
-
-sub from_json($) {
-   Carp::croak ("JSON::PP::from_json has been renamed to decode_json.");
-}
-
-
-# Methods
-
-sub new {
-    my $class = shift;
-    my $self  = {
-        max_depth   => 512,
-        max_size    => 0,
-        indent      => 0,
-        FLAGS       => 0,
-        fallback      => sub { encode_error('Invalid value. JSON can only reference.') },
-        indent_length => 3,
-    };
-
-    bless $self, $class;
-}
-
-
-sub encode {
-    return $_[0]->PP_encode_json($_[1]);
-}
-
-
-sub decode {
-    return $_[0]->PP_decode_json($_[1], 0x00000000);
-}
-
-
-sub decode_prefix {
-    return $_[0]->PP_decode_json($_[1], 0x00000001);
-}
-
-
-# accessor
-
-
-# pretty printing
-
-sub pretty {
-    my ($self, $v) = @_;
-    my $enable = defined $v ? $v : 1;
-
-    if ($enable) { # indent_length(3) for JSON::XS compatibility
-        $self->indent(1)->indent_length(3)->space_before(1)->space_after(1);
-    }
-    else {
-        $self->indent(0)->space_before(0)->space_after(0);
-    }
-
-    $self;
-}
-
-# etc
-
-sub max_depth {
-    my $max  = defined $_[1] ? $_[1] : 0x80000000;
-    $_[0]->{max_depth} = $max;
-    $_[0];
-}
-
-
-sub get_max_depth { $_[0]->{max_depth}; }
-
-
-sub max_size {
-    my $max  = defined $_[1] ? $_[1] : 0;
-    $_[0]->{max_size} = $max;
-    $_[0];
-}
-
-
-sub get_max_size { $_[0]->{max_size}; }
-
-
-sub filter_json_object {
-    $_[0]->{cb_object} = defined $_[1] ? $_[1] : 0;
-    $_[0]->{F_HOOK} = ($_[0]->{cb_object} or $_[0]->{cb_sk_object}) ? 1 : 0;
-    $_[0];
-}
-
-sub filter_json_single_key_object {
-    if (@_ > 1) {
-        $_[0]->{cb_sk_object}->{$_[1]} = $_[2];
-    }
-    $_[0]->{F_HOOK} = ($_[0]->{cb_object} or $_[0]->{cb_sk_object}) ? 1 : 0;
-    $_[0];
-}
-
-sub indent_length {
-    if (!defined $_[1] or $_[1] > 15 or $_[1] < 0) {
-        Carp::carp "The acceptable range of indent_length() is 0 to 15.";
-    }
-    else {
-        $_[0]->{indent_length} = $_[1];
-    }
-    $_[0];
-}
-
-sub get_indent_length {
-    $_[0]->{indent_length};
-}
-
-sub sort_by {
-    $_[0]->{sort_by} = defined $_[1] ? $_[1] : 1;
-    $_[0];
-}
-
-sub allow_bigint {
-    Carp::carp("allow_bigint() is obsoleted. use allow_bignum() insted.");
-}
-
-###############################
-
-###
-### Perl => JSON
-###
-
-
-{ # Convert
-
-    my $max_depth;
-    my $indent;
-    my $ascii;
-    my $latin1;
-    my $utf8;
-    my $space_before;
-    my $space_after;
-    my $canonical;
-    my $allow_blessed;
-    my $convert_blessed;
-
-    my $indent_length;
-    my $escape_slash;
-    my $bignum;
-    my $as_nonblessed;
-
-    my $depth;
-    my $indent_count;
-    my $keysort;
-
-
-    sub PP_encode_json {
-        my $self = shift;
-        my $obj  = shift;
-
-        $indent_count = 0;
-        $depth        = 0;
-
-        my $idx = $self->{PROPS};
-
-        ($ascii, $latin1, $utf8, $indent, $canonical, $space_before, $space_after, $allow_blessed,
-            $convert_blessed, $escape_slash, $bignum, $as_nonblessed)
-         = @{$idx}[P_ASCII .. P_SPACE_AFTER, P_ALLOW_BLESSED, P_CONVERT_BLESSED,
-                    P_ESCAPE_SLASH, P_ALLOW_BIGNUM, P_AS_NONBLESSED];
-
-        ($max_depth, $indent_length) = @{$self}{qw/max_depth indent_length/};
-
-        $keysort = $canonical ? sub { $a cmp $b } : undef;
-
-        if ($self->{sort_by}) {
-            $keysort = ref($self->{sort_by}) eq 'CODE' ? $self->{sort_by}
-                     : $self->{sort_by} =~ /\D+/       ? $self->{sort_by}
-                     : sub { $a cmp $b };
-        }
-
-        encode_error("hash- or arrayref expected (not a simple scalar, use allow_nonref to allow this)")
-             if(!ref $obj and !$idx->[ P_ALLOW_NONREF ]);
-
-        my $str  = $self->object_to_json($obj);
-
-        $str .= "\n" if ( $indent ); # JSON::XS 2.26 compatible
-
-        unless ($ascii or $latin1 or $utf8) {
-            utf8::upgrade($str);
-        }
-
-        if ($idx->[ P_SHRINK ]) {
-            utf8::downgrade($str, 1);
-        }
-
-        return $str;
-    }
-
-
-    sub object_to_json {
-        my ($self, $obj) = @_;
-        my $type = ref($obj);
-
-        if($type eq 'HASH'){
-            return $self->hash_to_json($obj);
-        }
-        elsif($type eq 'ARRAY'){
-            return $self->array_to_json($obj);
-        }
-        elsif ($type) { # blessed object?
-            if (blessed($obj)) {
-
-                return $self->value_to_json($obj) if ( $obj->isa('JSON::PP::Boolean') );
-
-                if ( $convert_blessed and $obj->can('TO_JSON') ) {
-                    my $result = $obj->TO_JSON();
-                    if ( defined $result and ref( $result ) ) {
-                        if ( refaddr( $obj ) eq refaddr( $result ) ) {
-                            encode_error( sprintf(
-                                "%s::TO_JSON method returned same object as was passed instead of a new one",
-                                ref $obj
-                            ) );
-                        }
-                    }
-
-                    return $self->object_to_json( $result );
-                }
-
-                return "$obj" if ( $bignum and _is_bignum($obj) );
-                return $self->blessed_to_json($obj) if ($allow_blessed and $as_nonblessed); # will be removed.
-
-                encode_error( sprintf("encountered object '%s', but neither allow_blessed "
-                    . "nor convert_blessed settings are enabled", $obj)
-                ) unless ($allow_blessed);
-
-                return 'null';
-            }
-            else {
-                return $self->value_to_json($obj);
-            }
-        }
-        else{
-            return $self->value_to_json($obj);
-        }
-    }
-
-
-    sub hash_to_json {
-        my ($self, $obj) = @_;
-        my @res;
-
-        encode_error("json text or perl structure exceeds maximum nesting level (max_depth set too low?)")
-                                         if (++$depth > $max_depth);
-
-        my ($pre, $post) = $indent ? $self->_up_indent() : ('', '');
-        my $del = ($space_before ? ' ' : '') . ':' . ($space_after ? ' ' : '');
-
-        for my $k ( _sort( $obj ) ) {
-            if ( OLD_PERL ) { utf8::decode($k) } # key for Perl 5.6 / be optimized
-            push @res, string_to_json( $self, $k )
-                          .  $del
-                          . ( $self->object_to_json( $obj->{$k} ) || $self->value_to_json( $obj->{$k} ) );
-        }
-
-        --$depth;
-        $self->_down_indent() if ($indent);
-
-        return   '{' . ( @res ? $pre : '' ) . ( @res ? join( ",$pre", @res ) . $post : '' )  . '}';
-    }
-
-
-    sub array_to_json {
-        my ($self, $obj) = @_;
-        my @res;
-
-        encode_error("json text or perl structure exceeds maximum nesting level (max_depth set too low?)")
-                                         if (++$depth > $max_depth);
-
-        my ($pre, $post) = $indent ? $self->_up_indent() : ('', '');
-
-        for my $v (@$obj){
-            push @res, $self->object_to_json($v) || $self->value_to_json($v);
-        }
-
-        --$depth;
-        $self->_down_indent() if ($indent);
-
-        return '[' . ( @res ? $pre : '' ) . ( @res ? join( ",$pre", @res ) . $post : '' ) . ']';
-    }
-
-
-    sub value_to_json {
-        my ($self, $value) = @_;
-
-        return 'null' if(!defined $value);
-
-        my $b_obj = B::svref_2object(\$value);  # for round trip problem
-        my $flags = $b_obj->FLAGS;
-
-        return $value # as is 
-            if $flags & ( B::SVp_IOK | B::SVp_NOK ) and !( $flags & B::SVp_POK ); # SvTYPE is IV or NV?
-
-        my $type = ref($value);
-
-        if(!$type){
-            return string_to_json($self, $value);
-        }
-        elsif( blessed($value) and  $value->isa('JSON::PP::Boolean') ){
-            return $$value == 1 ? 'true' : 'false';
-        }
-        elsif ($type) {
-            if ((overload::StrVal($value) =~ /=(\w+)/)[0]) {
-                return $self->value_to_json("$value");
-            }
-
-            if ($type eq 'SCALAR' and defined $$value) {
-                return   $$value eq '1' ? 'true'
-                       : $$value eq '0' ? 'false'
-                       : $self->{PROPS}->[ P_ALLOW_UNKNOWN ] ? 'null'
-                       : encode_error("cannot encode reference to scalar");
-            }
-
-             if ( $self->{PROPS}->[ P_ALLOW_UNKNOWN ] ) {
-                 return 'null';
-             }
-             else {
-                 if ( $type eq 'SCALAR' or $type eq 'REF' ) {
-                    encode_error("cannot encode reference to scalar");
-                 }
-                 else {
-                    encode_error("encountered $value, but JSON can only represent references to arrays or hashes");
-                 }
-             }
-
-        }
-        else {
-            return $self->{fallback}->($value)
-                 if ($self->{fallback} and ref($self->{fallback}) eq 'CODE');
-            return 'null';
-        }
-
-    }
-
-
-    my %esc = (
-        "\n" => '\n',
-        "\r" => '\r',
-        "\t" => '\t',
-        "\f" => '\f',
-        "\b" => '\b',
-        "\"" => '\"',
-        "\\" => '\\\\',
-        "\'" => '\\\'',
-    );
-
-
-    sub string_to_json {
-        my ($self, $arg) = @_;
-
-        $arg =~ s/([\x22\x5c\n\r\t\f\b])/$esc{$1}/g;
-        $arg =~ s/\//\\\//g if ($escape_slash);
-        $arg =~ s/([\x00-\x08\x0b\x0e-\x1f])/'\\u00' . unpack('H2', $1)/eg;
-
-        if ($ascii) {
-            $arg = JSON_PP_encode_ascii($arg);
-        }
-
-        if ($latin1) {
-            $arg = JSON_PP_encode_latin1($arg);
-        }
-
-        if ($utf8) {
-            utf8::encode($arg);
-        }
-
-        return '"' . $arg . '"';
-    }
-
-
-    sub blessed_to_json {
-        my $reftype = reftype($_[1]) || '';
-        if ($reftype eq 'HASH') {
-            return $_[0]->hash_to_json($_[1]);
-        }
-        elsif ($reftype eq 'ARRAY') {
-            return $_[0]->array_to_json($_[1]);
-        }
-        else {
-            return 'null';
-        }
-    }
-
-
-    sub encode_error {
-        my $error  = shift;
-        Carp::croak "$error";
-    }
-
-
-    sub _sort {
-        defined $keysort ? (sort $keysort (keys %{$_[0]})) : keys %{$_[0]};
-    }
-
-
-    sub _up_indent {
-        my $self  = shift;
-        my $space = ' ' x $indent_length;
-
-        my ($pre,$post) = ('','');
-
-        $post = "\n" . $space x $indent_count;
-
-        $indent_count++;
-
-        $pre = "\n" . $space x $indent_count;
-
-        return ($pre,$post);
-    }
-
-
-    sub _down_indent { $indent_count--; }
-
-
-    sub PP_encode_box {
-        {
-            depth        => $depth,
-            indent_count => $indent_count,
-        };
-    }
-
-} # Convert
-
-
-sub _encode_ascii {
-    join('',
-        map {
-            $_ <= 127 ?
-                chr($_) :
-            $_ <= 65535 ?
-                sprintf('\u%04x', $_) : sprintf('\u%x\u%x', _encode_surrogates($_));
-        } unpack('U*', $_[0])
-    );
-}
-
-
-sub _encode_latin1 {
-    join('',
-        map {
-            $_ <= 255 ?
-                chr($_) :
-            $_ <= 65535 ?
-                sprintf('\u%04x', $_) : sprintf('\u%x\u%x', _encode_surrogates($_));
-        } unpack('U*', $_[0])
-    );
-}
-
-
-sub _encode_surrogates { # from perlunicode
-    my $uni = $_[0] - 0x10000;
-    return ($uni / 0x400 + 0xD800, $uni % 0x400 + 0xDC00);
-}
-
-
-sub _is_bignum {
-    $_[0]->isa('Math::BigInt') or $_[0]->isa('Math::BigFloat');
-}
-
-
-
-#
-# JSON => Perl
-#
-
-my $max_intsize;
-
-BEGIN {
-    my $checkint = 1111;
-    for my $d (5..64) {
-        $checkint .= 1;
-        my $int   = eval qq| $checkint |;
-        if ($int =~ /[eE]/) {
-            $max_intsize = $d - 1;
-            last;
-        }
-    }
-}
-
-{ # PARSE 
-
-    my %escapes = ( #  by Jeremy Muhlich <jmuhlich [at] bitflood.org>
-        b    => "\x8",
-        t    => "\x9",
-        n    => "\xA",
-        f    => "\xC",
-        r    => "\xD",
-        '\\' => '\\',
-        '"'  => '"',
-        '/'  => '/',
-    );
-
-    my $text; # json data
-    my $at;   # offset
-    my $ch;   # 1chracter
-    my $len;  # text length (changed according to UTF8 or NON UTF8)
-    # INTERNAL
-    my $depth;          # nest counter
-    my $encoding;       # json text encoding
-    my $is_valid_utf8;  # temp variable
-    my $utf8_len;       # utf8 byte length
-    # FLAGS
-    my $utf8;           # must be utf8
-    my $max_depth;      # max nest number of objects and arrays
-    my $max_size;
-    my $relaxed;
-    my $cb_object;
-    my $cb_sk_object;
-
-    my $F_HOOK;
-
-    my $allow_bigint;   # using Math::BigInt
-    my $singlequote;    # loosely quoting
-    my $loose;          # 
-    my $allow_barekey;  # bareKey
-
-    # $opt flag
-    # 0x00000001 .... decode_prefix
-    # 0x10000000 .... incr_parse
-
-    sub PP_decode_json {
-        my ($self, $opt); # $opt is an effective flag during this decode_json.
-
-        ($self, $text, $opt) = @_;
-
-        ($at, $ch, $depth) = (0, '', 0);
-
-        if ( !defined $text or ref $text ) {
-            decode_error("malformed JSON string, neither array, object, number, string or atom");
-        }
-
-        my $idx = $self->{PROPS};
-
-        ($utf8, $relaxed, $loose, $allow_bigint, $allow_barekey, $singlequote)
-            = @{$idx}[P_UTF8, P_RELAXED, P_LOOSE .. P_ALLOW_SINGLEQUOTE];
-
-        if ( $utf8 ) {
-            utf8::downgrade( $text, 1 ) or Carp::croak("Wide character in subroutine entry");
-        }
-        else {
-            utf8::upgrade( $text );
-        }
-
-        $len = length $text;
-
-        ($max_depth, $max_size, $cb_object, $cb_sk_object, $F_HOOK)
-             = @{$self}{qw/max_depth  max_size cb_object cb_sk_object F_HOOK/};
-
-        if ($max_size > 1) {
-            use bytes;
-            my $bytes = length $text;
-            decode_error(
-                sprintf("attempted decode of JSON text of %s bytes size, but max_size is set to %s"
-                    , $bytes, $max_size), 1
-            ) if ($bytes > $max_size);
-        }
-
-        # Currently no effect
-        # should use regexp
-        my @octets = unpack('C4', $text);
-        $encoding =   ( $octets[0] and  $octets[1]) ? 'UTF-8'
-                    : (!$octets[0] and  $octets[1]) ? 'UTF-16BE'
-                    : (!$octets[0] and !$octets[1]) ? 'UTF-32BE'
-                    : ( $octets[2]                ) ? 'UTF-16LE'
-                    : (!$octets[2]                ) ? 'UTF-32LE'
-                    : 'unknown';
-
-        white(); # remove head white space
-
-        my $valid_start = defined $ch; # Is there a first character for JSON structure?
-
-        my $result = value();
-
-        return undef if ( !$result && ( $opt & 0x10000000 ) ); # for incr_parse
-
-        decode_error("malformed JSON string, neither array, object, number, string or atom") unless $valid_start;
-
-        if ( !$idx->[ P_ALLOW_NONREF ] and !ref $result ) {
-                decode_error(
-                'JSON text must be an object or array (but found number, string, true, false or null,'
-                       . ' use allow_nonref to allow this)', 1);
-        }
-
-        Carp::croak('something wrong.') if $len < $at; # we won't arrive here.
-
-        my $consumed = defined $ch ? $at - 1 : $at; # consumed JSON text length
-
-        white(); # remove tail white space
-
-        if ( $ch ) {
-            return ( $result, $consumed ) if ($opt & 0x00000001); # all right if decode_prefix
-            decode_error("garbage after JSON object");
-        }
-
-        ( $opt & 0x00000001 ) ? ( $result, $consumed ) : $result;
-    }
-
-
-    sub next_chr {
-        return $ch = undef if($at >= $len);
-        $ch = substr($text, $at++, 1);
-    }
-
-
-    sub value {
-        white();
-        return          if(!defined $ch);
-        return object() if($ch eq '{');
-        return array()  if($ch eq '[');
-        return string() if($ch eq '"' or ($singlequote and $ch eq "'"));
-        return number() if($ch =~ /[0-9]/ or $ch eq '-');
-        return word();
-    }
-
-    sub string {
-        my ($i, $s, $t, $u);
-        my $utf16;
-        my $is_utf8;
-
-        ($is_valid_utf8, $utf8_len) = ('', 0);
-
-        $s = ''; # basically UTF8 flag on
-
-        if($ch eq '"' or ($singlequote and $ch eq "'")){
-            my $boundChar = $ch;
-
-            OUTER: while( defined(next_chr()) ){
-
-                if($ch eq $boundChar){
-                    next_chr();
-
-                    if ($utf16) {
-                        decode_error("missing low surrogate character in surrogate pair");
-                    }
-
-                    utf8::decode($s) if($is_utf8);
-
-                    return $s;
-                }
-                elsif($ch eq '\\'){
-                    next_chr();
-                    if(exists $escapes{$ch}){
-                        $s .= $escapes{$ch};
-                    }
-                    elsif($ch eq 'u'){ # UNICODE handling
-                        my $u = '';
-
-                        for(1..4){
-                            $ch = next_chr();
-                            last OUTER if($ch !~ /[0-9a-fA-F]/);
-                            $u .= $ch;
-                        }
-
-                        # U+D800 - U+DBFF
-                        if ($u =~ /^[dD][89abAB][0-9a-fA-F]{2}/) { # UTF-16 high surrogate?
-                            $utf16 = $u;
-                        }
-                        # U+DC00 - U+DFFF
-                        elsif ($u =~ /^[dD][c-fC-F][0-9a-fA-F]{2}/) { # UTF-16 low surrogate?
-                            unless (defined $utf16) {
-                                decode_error("missing high surrogate character in surrogate pair");
-                            }
-                            $is_utf8 = 1;
-                            $s .= JSON_PP_decode_surrogates($utf16, $u) || next;
-                            $utf16 = undef;
-                        }
-                        else {
-                            if (defined $utf16) {
-                                decode_error("surrogate pair expected");
-                            }
-
-                            if ( ( my $hex = hex( $u ) ) > 127 ) {
-                                $is_utf8 = 1;
-                                $s .= JSON_PP_decode_unicode($u) || next;
-                            }
-                            else {
-                                $s .= chr $hex;
-                            }
-                        }
-
-                    }
-                    else{
-                        unless ($loose) {
-                            $at -= 2;
-                            decode_error('illegal backslash escape sequence in string');
-                        }
-                        $s .= $ch;
-                    }
-                }
-                else{
-
-                    if ( ord $ch  > 127 ) {
-                        if ( $utf8 ) {
-                            unless( $ch = is_valid_utf8($ch) ) {
-                                $at -= 1;
-                                decode_error("malformed UTF-8 character in JSON string");
-                            }
-                            else {
-                                $at += $utf8_len - 1;
-                            }
-                        }
-                        else {
-                            utf8::encode( $ch );
-                        }
-
-                        $is_utf8 = 1;
-                    }
-
-                    if (!$loose) {
-                        if ($ch =~ /[\x00-\x1f\x22\x5c]/)  { # '/' ok
-                            $at--;
-                            decode_error('invalid character encountered while parsing JSON string');
-                        }
-                    }
-
-                    $s .= $ch;
-                }
-            }
-        }
-
-        decode_error("unexpected end of string while parsing JSON string");
-    }
-
-
-    sub white {
-        while( defined $ch  ){
-            if($ch le ' '){
-                next_chr();
-            }
-            elsif($ch eq '/'){
-                next_chr();
-                if(defined $ch and $ch eq '/'){
-                    1 while(defined(next_chr()) and $ch ne "\n" and $ch ne "\r");
-                }
-                elsif(defined $ch and $ch eq '*'){
-                    next_chr();
-                    while(1){
-                        if(defined $ch){
-                            if($ch eq '*'){
-                                if(defined(next_chr()) and $ch eq '/'){
-                                    next_chr();
-                                    last;
-                                }
-                            }
-                            else{
-                                next_chr();
-                            }
-                        }
-                        else{
-                            decode_error("Unterminated comment");
-                        }
-                    }
-                    next;
-                }
-                else{
-                    $at--;
-                    decode_error("malformed JSON string, neither array, object, number, string or atom");
-                }
-            }
-            else{
-                if ($relaxed and $ch eq '#') { # correctly?
-                    pos($text) = $at;
-                    $text =~ /\G([^\n]*(?:\r\n|\r|\n|$))/g;
-                    $at = pos($text);
-                    next_chr;
-                    next;
-                }
-
-                last;
-            }
-        }
-    }
-
-
-    sub array {
-        my $a  = $_[0] || []; # you can use this code to use another array ref object.
-
-        decode_error('json text or perl structure exceeds maximum nesting level (max_depth set too low?)')
-                                                    if (++$depth > $max_depth);
-
-        next_chr();
-        white();
-
-        if(defined $ch and $ch eq ']'){
-            --$depth;
-            next_chr();
-            return $a;
-        }
-        else {
-            while(defined($ch)){
-                push @$a, value();
-
-                white();
-
-                if (!defined $ch) {
-                    last;
-                }
-
-                if($ch eq ']'){
-                    --$depth;
-                    next_chr();
-                    return $a;
-                }
-
-                if($ch ne ','){
-                    last;
-                }
-
-                next_chr();
-                white();
-
-                if ($relaxed and $ch eq ']') {
-                    --$depth;
-                    next_chr();
-                    return $a;
-                }
-
-            }
-        }
-
-        decode_error(", or ] expected while parsing array");
-    }
-
-
-    sub object {
-        my $o = $_[0] || {}; # you can use this code to use another hash ref object.
-        my $k;
-
-        decode_error('json text or perl structure exceeds maximum nesting level (max_depth set too low?)')
-                                                if (++$depth > $max_depth);
-        next_chr();
-        white();
-
-        if(defined $ch and $ch eq '}'){
-            --$depth;
-            next_chr();
-            if ($F_HOOK) {
-                return _json_object_hook($o);
-            }
-            return $o;
-        }
-        else {
-            while (defined $ch) {
-                $k = ($allow_barekey and $ch ne '"' and $ch ne "'") ? bareKey() : string();
-                white();
-
-                if(!defined $ch or $ch ne ':'){
-                    $at--;
-                    decode_error("':' expected");
-                }
-
-                next_chr();
-                $o->{$k} = value();
-                white();
-
-                last if (!defined $ch);
-
-                if($ch eq '}'){
-                    --$depth;
-                    next_chr();
-                    if ($F_HOOK) {
-                        return _json_object_hook($o);
-                    }
-                    return $o;
-                }
-
-                if($ch ne ','){
-                    last;
-                }
-
-                next_chr();
-                white();
-
-                if ($relaxed and $ch eq '}') {
-                    --$depth;
-                    next_chr();
-                    if ($F_HOOK) {
-                        return _json_object_hook($o);
-                    }
-                    return $o;
-                }
-
-            }
-
-        }
-
-        $at--;
-        decode_error(", or } expected while parsing object/hash");
-    }
-
-
-    sub bareKey { # doesn't strictly follow Standard ECMA-262 3rd Edition
-        my $key;
-        while($ch =~ /[^\x00-\x23\x25-\x2F\x3A-\x40\x5B-\x5E\x60\x7B-\x7F]/){
-            $key .= $ch;
-            next_chr();
-        }
-        return $key;
-    }
-
-
-    sub word {
-        my $word =  substr($text,$at-1,4);
-
-        if($word eq 'true'){
-            $at += 3;
-            next_chr;
-            return $JSON::PP::true;
-        }
-        elsif($word eq 'null'){
-            $at += 3;
-            next_chr;
-            return undef;
-        }
-        elsif($word eq 'fals'){
-            $at += 3;
-            if(substr($text,$at,1) eq 'e'){
-                $at++;
-                next_chr;
-                return $JSON::PP::false;
-            }
-        }
-
-        $at--; # for decode_error report
-
-        decode_error("'null' expected")  if ($word =~ /^n/);
-        decode_error("'true' expected")  if ($word =~ /^t/);
-        decode_error("'false' expected") if ($word =~ /^f/);
-        decode_error("malformed JSON string, neither array, object, number, string or atom");
-    }
-
-
-    sub number {
-        my $n    = '';
-        my $v;
-
-        # According to RFC4627, hex or oct digits are invalid.
-        if($ch eq '0'){
-            my $peek = substr($text,$at,1);
-            my $hex  = $peek =~ /[xX]/; # 0 or 1
-
-            if($hex){
-                decode_error("malformed number (leading zero must not be followed by another digit)");
-                ($n) = ( substr($text, $at+1) =~ /^([0-9a-fA-F]+)/);
-            }
-            else{ # oct
-                ($n) = ( substr($text, $at) =~ /^([0-7]+)/);
-                if (defined $n and length $n > 1) {
-                    decode_error("malformed number (leading zero must not be followed by another digit)");
-                }
-            }
-
-            if(defined $n and length($n)){
-                if (!$hex and length($n) == 1) {
-                   decode_error("malformed number (leading zero must not be followed by another digit)");
-                }
-                $at += length($n) + $hex;
-                next_chr;
-                return $hex ? hex($n) : oct($n);
-            }
-        }
-
-        if($ch eq '-'){
-            $n = '-';
-            next_chr;
-            if (!defined $ch or $ch !~ /\d/) {
-                decode_error("malformed number (no digits after initial minus)");
-            }
-        }
-
-        while(defined $ch and $ch =~ /\d/){
-            $n .= $ch;
-            next_chr;
-        }
-
-        if(defined $ch and $ch eq '.'){
-            $n .= '.';
-
-            next_chr;
-            if (!defined $ch or $ch !~ /\d/) {
-                decode_error("malformed number (no digits after decimal point)");
-            }
-            else {
-                $n .= $ch;
-            }
-
-            while(defined(next_chr) and $ch =~ /\d/){
-                $n .= $ch;
-            }
-        }
-
-        if(defined $ch and ($ch eq 'e' or $ch eq 'E')){
-            $n .= $ch;
-            next_chr;
-
-            if(defined($ch) and ($ch eq '+' or $ch eq '-')){
-                $n .= $ch;
-                next_chr;
-                if (!defined $ch or $ch =~ /\D/) {
-                    decode_error("malformed number (no digits after exp sign)");
-                }
-                $n .= $ch;
-            }
-            elsif(defined($ch) and $ch =~ /\d/){
-                $n .= $ch;
-            }
-            else {
-                decode_error("malformed number (no digits after exp sign)");
-            }
-
-            while(defined(next_chr) and $ch =~ /\d/){
-                $n .= $ch;
-            }
-
-        }
-
-        $v .= $n;
-
-        if ($v !~ /[.eE]/ and length $v > $max_intsize) {
-            if ($allow_bigint) { # from Adam Sussman
-                require Math::BigInt;
-                return Math::BigInt->new($v);
-            }
-            else {
-                return "$v";
-            }
-        }
-        elsif ($allow_bigint) {
-            require Math::BigFloat;
-            return Math::BigFloat->new($v);
-        }
-
-        return 0+$v;
-    }
-
-
-    sub is_valid_utf8 {
-
-        $utf8_len = $_[0] =~ /[\x00-\x7F]/  ? 1
-                  : $_[0] =~ /[\xC2-\xDF]/  ? 2
-                  : $_[0] =~ /[\xE0-\xEF]/  ? 3
-                  : $_[0] =~ /[\xF0-\xF4]/  ? 4
-                  : 0
-                  ;
-
-        return unless $utf8_len;
-
-        my $is_valid_utf8 = substr($text, $at - 1, $utf8_len);
-
-        return ( $is_valid_utf8 =~ /^(?:
-             [\x00-\x7F]
-            |[\xC2-\xDF][\x80-\xBF]
-            |[\xE0][\xA0-\xBF][\x80-\xBF]
-            |[\xE1-\xEC][\x80-\xBF][\x80-\xBF]
-            |[\xED][\x80-\x9F][\x80-\xBF]
-            |[\xEE-\xEF][\x80-\xBF][\x80-\xBF]
-            |[\xF0][\x90-\xBF][\x80-\xBF][\x80-\xBF]
-            |[\xF1-\xF3][\x80-\xBF][\x80-\xBF][\x80-\xBF]
-            |[\xF4][\x80-\x8F][\x80-\xBF][\x80-\xBF]
-        )$/x )  ? $is_valid_utf8 : '';
-    }
-
-
-    sub decode_error {
-        my $error  = shift;
-        my $no_rep = shift;
-        my $str    = defined $text ? substr($text, $at) : '';
-        my $mess   = '';
-        my $type   = $] >= 5.008           ? 'U*'
-                   : $] <  5.006           ? 'C*'
-                   : utf8::is_utf8( $str ) ? 'U*' # 5.6
-                   : 'C*'
-                   ;
-
-        for my $c ( unpack( $type, $str ) ) { # emulate pv_uni_display() ?
-            $mess .=  $c == 0x07 ? '\a'
-                    : $c == 0x09 ? '\t'
-                    : $c == 0x0a ? '\n'
-                    : $c == 0x0d ? '\r'
-                    : $c == 0x0c ? '\f'
-                    : $c <  0x20 ? sprintf('\x{%x}', $c)
-                    : $c == 0x5c ? '\\\\'
-                    : $c <  0x80 ? chr($c)
-                    : sprintf('\x{%x}', $c)
-                    ;
-            if ( length $mess >= 20 ) {
-                $mess .= '...';
-                last;
-            }
-        }
-
-        unless ( length $mess ) {
-            $mess = '(end of string)';
-        }
-
-        Carp::croak (
-            $no_rep ? "$error" : "$error, at character offset $at (before \"$mess\")"
-        );
-
-    }
-
-
-    sub _json_object_hook {
-        my $o    = $_[0];
-        my @ks = keys %{$o};
-
-        if ( $cb_sk_object and @ks == 1 and exists $cb_sk_object->{ $ks[0] } and ref $cb_sk_object->{ $ks[0] } ) {
-            my @val = $cb_sk_object->{ $ks[0] }->( $o->{$ks[0]} );
-            if (@val == 1) {
-                return $val[0];
-            }
-        }
-
-        my @val = $cb_object->($o) if ($cb_object);
-        if (@val == 0 or @val > 1) {
-            return $o;
-        }
-        else {
-            return $val[0];
-        }
-    }
-
-
-    sub PP_decode_box {
-        {
-            text    => $text,
-            at      => $at,
-            ch      => $ch,
-            len     => $len,
-            depth   => $depth,
-            encoding      => $encoding,
-            is_valid_utf8 => $is_valid_utf8,
-        };
-    }
-
-} # PARSE
-
-
-sub _decode_surrogates { # from perlunicode
-    my $uni = 0x10000 + (hex($_[0]) - 0xD800) * 0x400 + (hex($_[1]) - 0xDC00);
-    my $un  = pack('U*', $uni);
-    utf8::encode( $un );
-    return $un;
-}
-
-
-sub _decode_unicode {
-    my $un = pack('U', hex shift);
-    utf8::encode( $un );
-    return $un;
-}
-
-#
-# Setup for various Perl versions (the code from JSON::PP58)
-#
-
-BEGIN {
-
-    unless ( defined &utf8::is_utf8 ) {
-       require Encode;
-       *utf8::is_utf8 = *Encode::is_utf8;
-    }
-
-    if ( $] >= 5.008 ) {
-        *JSON::PP::JSON_PP_encode_ascii      = \&_encode_ascii;
-        *JSON::PP::JSON_PP_encode_latin1     = \&_encode_latin1;
-        *JSON::PP::JSON_PP_decode_surrogates = \&_decode_surrogates;
-        *JSON::PP::JSON_PP_decode_unicode    = \&_decode_unicode;
-    }
-
-    if ($] >= 5.008 and $] < 5.008003) { # join() in 5.8.0 - 5.8.2 is broken.
-        package # hide from PAUSE
-          JSON::PP;
-        require subs;
-        subs->import('join');
-        eval q|
-            sub join {
-                return '' if (@_ < 2);
-                my $j   = shift;
-                my $str = shift;
-                for (@_) { $str .= $j . $_; }
-                return $str;
-            }
-        |;
-    }
-
-
-    sub JSON::PP::incr_parse {
-        local $Carp::CarpLevel = 1;
-        ( $_[0]->{_incr_parser} ||= JSON::PP::IncrParser->new )->incr_parse( @_ );
-    }
-
-
-    sub JSON::PP::incr_skip {
-        ( $_[0]->{_incr_parser} ||= JSON::PP::IncrParser->new )->incr_skip;
-    }
-
-
-    sub JSON::PP::incr_reset {
-        ( $_[0]->{_incr_parser} ||= JSON::PP::IncrParser->new )->incr_reset;
-    }
-
-    eval q{
-        sub JSON::PP::incr_text : lvalue {
-            $_[0]->{_incr_parser} ||= JSON::PP::IncrParser->new;
-
-            if ( $_[0]->{_incr_parser}->{incr_parsing} ) {
-                Carp::croak("incr_text can not be called when the incremental parser already started parsing");
-            }
-            $_[0]->{_incr_parser}->{incr_text};
-        }
-    } if ( $] >= 5.006 );
-
-} # Setup for various Perl versions (the code from JSON::PP58)
-
-
-###############################
-# Utilities
-#
-
-BEGIN {
-    eval 'require Scalar::Util';
-    unless($@){
-        *JSON::PP::blessed = \&Scalar::Util::blessed;
-        *JSON::PP::reftype = \&Scalar::Util::reftype;
-        *JSON::PP::refaddr = \&Scalar::Util::refaddr;
-    }
-    else{ # This code is from Scalar::Util.
-        # warn $@;
-        eval 'sub UNIVERSAL::a_sub_not_likely_to_be_here { ref($_[0]) }';
-        *JSON::PP::blessed = sub {
-            local($@, $SIG{__DIE__}, $SIG{__WARN__});
-            ref($_[0]) ? eval { $_[0]->a_sub_not_likely_to_be_here } : undef;
-        };
-        my %tmap = qw(
-            B::NULL   SCALAR
-            B::HV     HASH
-            B::AV     ARRAY
-            B::CV     CODE
-            B::IO     IO
-            B::GV     GLOB
-            B::REGEXP REGEXP
-        );
-        *JSON::PP::reftype = sub {
-            my $r = shift;
-
-            return undef unless length(ref($r));
-
-            my $t = ref(B::svref_2object($r));
-
-            return
-                exists $tmap{$t} ? $tmap{$t}
-              : length(ref($$r)) ? 'REF'
-              :                    'SCALAR';
-        };
-        *JSON::PP::refaddr = sub {
-          return undef unless length(ref($_[0]));
-
-          my $addr;
-          if(defined(my $pkg = blessed($_[0]))) {
-            $addr .= bless $_[0], 'Scalar::Util::Fake';
-            bless $_[0], $pkg;
-          }
-          else {
-            $addr .= $_[0]
-          }
-
-          $addr =~ /0x(\w+)/;
-          local $^W;
-          #no warnings 'portable';
-          hex($1);
-        }
-    }
-}
-
-
-# shamelessly copied and modified from JSON::XS code.
-
-unless ( $INC{'JSON/PP.pm'} ) {
-    eval q|
-        package
-            JSON::PP::Boolean;
-
-        use overload (
-            "0+"     => sub { ${$_[0]} },
-            "++"     => sub { $_[0] = ${$_[0]} + 1 },
-            "--"     => sub { $_[0] = ${$_[0]} - 1 },
-            fallback => 1,
-        );
-    |;
-}
-
-$JSON::PP::true  = do { bless \(my $dummy = 1), "JSON::PP::Boolean" };
-$JSON::PP::false = do { bless \(my $dummy = 0), "JSON::PP::Boolean" };
-
-sub is_bool { defined $_[0] and UNIVERSAL::isa($_[0], "JSON::PP::Boolean"); }
-
-sub true  { $JSON::PP::true  }
-sub false { $JSON::PP::false }
-sub null  { undef; }
-
-###############################
-
-###############################
-
-package # hide from PAUSE
-  JSON::PP::IncrParser;
-
-use strict;
-
-use constant INCR_M_WS   => 0; # initial whitespace skipping
-use constant INCR_M_STR  => 1; # inside string
-use constant INCR_M_BS   => 2; # inside backslash
-use constant INCR_M_JSON => 3; # outside anything, count nesting
-use constant INCR_M_C0   => 4;
-use constant INCR_M_C1   => 5;
-
-use vars qw($VERSION);
-$VERSION = '1.01';
-
-my $unpack_format = $] < 5.006 ? 'C*' : 'U*';
-
-sub new {
-    my ( $class ) = @_;
-
-    bless {
-        incr_nest    => 0,
-        incr_text    => undef,
-        incr_parsing => 0,
-        incr_p       => 0,
-    }, $class;
-}
-
-
-sub incr_parse {
-    my ( $self, $coder, $text ) = @_;
-
-    $self->{incr_text} = '' unless ( defined $self->{incr_text} );
-
-    if ( defined $text ) {
-        if ( utf8::is_utf8( $text ) and !utf8::is_utf8( $self->{incr_text} ) ) {
-            utf8::upgrade( $self->{incr_text} ) ;
-            utf8::decode( $self->{incr_text} ) ;
-        }
-        $self->{incr_text} .= $text;
-    }
-
-
-    my $max_size = $coder->get_max_size;
-
-    if ( defined wantarray ) {
-
-        $self->{incr_mode} = INCR_M_WS unless defined $self->{incr_mode};
-
-        if ( wantarray ) {
-            my @ret;
-
-            $self->{incr_parsing} = 1;
-
-            do {
-                push @ret, $self->_incr_parse( $coder, $self->{incr_text} );
-
-                unless ( !$self->{incr_nest} and $self->{incr_mode} == INCR_M_JSON ) {
-                    $self->{incr_mode} = INCR_M_WS if $self->{incr_mode} != INCR_M_STR;
-                }
-
-            } until ( length $self->{incr_text} >= $self->{incr_p} );
-
-            $self->{incr_parsing} = 0;
-
-            return @ret;
-        }
-        else { # in scalar context
-            $self->{incr_parsing} = 1;
-            my $obj = $self->_incr_parse( $coder, $self->{incr_text} );
-            $self->{incr_parsing} = 0 if defined $obj; # pointed by Martin J. Evans
-            return $obj ? $obj : undef; # $obj is an empty string, parsing was completed.
-        }
-
-    }
-
-}
-
-
-sub _incr_parse {
-    my ( $self, $coder, $text, $skip ) = @_;
-    my $p = $self->{incr_p};
-    my $restore = $p;
-
-    my @obj;
-    my $len = length $text;
-
-    if ( $self->{incr_mode} == INCR_M_WS ) {
-        while ( $len > $p ) {
-            my $s = substr( $text, $p, 1 );
-            $p++ and next if ( 0x20 >= unpack($unpack_format, $s) );
-            $self->{incr_mode} = INCR_M_JSON;
-            last;
-       }
-    }
-
-    while ( $len > $p ) {
-        my $s = substr( $text, $p++, 1 );
-
-        if ( $s eq '"' ) {
-            if (substr( $text, $p - 2, 1 ) eq '\\' ) {
-                next;
-            }
-
-            if ( $self->{incr_mode} != INCR_M_STR  ) {
-                $self->{incr_mode} = INCR_M_STR;
-            }
-            else {
-                $self->{incr_mode} = INCR_M_JSON;
-                unless ( $self->{incr_nest} ) {
-                    last;
-                }
-            }
-        }
-
-        if ( $self->{incr_mode} == INCR_M_JSON ) {
-
-            if ( $s eq '[' or $s eq '{' ) {
-                if ( ++$self->{incr_nest} > $coder->get_max_depth ) {
-                    Carp::croak('json text or perl structure exceeds maximum nesting level (max_depth set too low?)');
-                }
-            }
-            elsif ( $s eq ']' or $s eq '}' ) {
-                last if ( --$self->{incr_nest} <= 0 );
-            }
-            elsif ( $s eq '#' ) {
-                while ( $len > $p ) {
-                    last if substr( $text, $p++, 1 ) eq "\n";
-                }
-            }
-
-        }
-
-    }
-
-    $self->{incr_p} = $p;
-
-    return if ( $self->{incr_mode} == INCR_M_STR and not $self->{incr_nest} );
-    return if ( $self->{incr_mode} == INCR_M_JSON and $self->{incr_nest} > 0 );
-
-    return '' unless ( length substr( $self->{incr_text}, 0, $p ) );
-
-    local $Carp::CarpLevel = 2;
-
-    $self->{incr_p} = $restore;
-    $self->{incr_c} = $p;
-
-    my ( $obj, $tail ) = $coder->PP_decode_json( substr( $self->{incr_text}, 0, $p ), 0x10000001 );
-
-    $self->{incr_text} = substr( $self->{incr_text}, $p );
-    $self->{incr_p} = 0;
-
-    return $obj || '';
-}
-
-
-sub incr_text {
-    if ( $_[0]->{incr_parsing} ) {
-        Carp::croak("incr_text can not be called when the incremental parser already started parsing");
-    }
-    $_[0]->{incr_text};
-}
-
-
-sub incr_skip {
-    my $self  = shift;
-    $self->{incr_text} = substr( $self->{incr_text}, $self->{incr_c} );
-    $self->{incr_p} = 0;
-}
-
-
-sub incr_reset {
-    my $self = shift;
-    $self->{incr_text}    = undef;
-    $self->{incr_p}       = 0;
-    $self->{incr_mode}    = 0;
-    $self->{incr_nest}    = 0;
-    $self->{incr_parsing} = 0;
-}
-
-###############################
-
-
-1;
-__END__
-=pod
-
-=head1 NAME
-
-JSON::PP - JSON::XS compatible pure-Perl module.
-
-=head1 SYNOPSIS
-
- use JSON::PP;
-
- # exported functions, they croak on error
- # and expect/generate UTF-8
-
- $utf8_encoded_json_text = encode_json $perl_hash_or_arrayref;
- $perl_hash_or_arrayref  = decode_json $utf8_encoded_json_text;
-
- # OO-interface
-
- $coder = JSON::PP->new->ascii->pretty->allow_nonref;
- 
- $json_text   = $json->encode( $perl_scalar );
- $perl_scalar = $json->decode( $json_text );
- 
- $pretty_printed = $json->pretty->encode( $perl_scalar ); # pretty-printing
- 
- # Note that JSON version 2.0 and above will automatically use
- # JSON::XS or JSON::PP, so you should be able to just:
- 
- use JSON;
-
-
-=head1 VERSION
-
-    2.27200
-
-L<JSON::XS> 2.27 (~2.30) compatible.
-
-=head1 DESCRIPTION
-
-This module is L<JSON::XS> compatible pure Perl module.
-(Perl 5.8 or later is recommended)
-
-JSON::XS is the fastest and most proper JSON module on CPAN.
-It is written by Marc Lehmann in C, so must be compiled and
-installed in the used environment.
-
-JSON::PP is a pure-Perl module and has compatibility to JSON::XS.
-
-
-=head2 FEATURES
-
-=over
-
-=item * correct unicode handling
-
-This module knows how to handle Unicode (depending on Perl version).
-
-See to L<JSON::XS/A FEW NOTES ON UNICODE AND PERL> and
-L<UNICODE HANDLING ON PERLS>.
-
-
-=item * round-trip integrity
-
-When you serialise a perl data structure using only data types
-supported by JSON and Perl, the deserialised data structure is
-identical on the Perl level. (e.g. the string "2.0" doesn't suddenly
-become "2" just because it looks like a number). There I<are> minor
-exceptions to this, read the MAPPING section below to learn about
-those.
-
-
-=item * strict checking of JSON correctness
-
-There is no guessing, no generating of illegal JSON texts by default,
-and only JSON is accepted as input by default (the latter is a
-security feature). But when some options are set, loose checking
-features are available.
-
-=back
-
-=head1 FUNCTIONAL INTERFACE
-
-Some documents are copied and modified from L<JSON::XS/FUNCTIONAL INTERFACE>.
-
-=head2 encode_json
-
-    $json_text = encode_json $perl_scalar
-
-Converts the given Perl data structure to a UTF-8 encoded, binary string.
-
-This function call is functionally identical to:
-
-    $json_text = JSON::PP->new->utf8->encode($perl_scalar)
-
-=head2 decode_json
-
-    $perl_scalar = decode_json $json_text
-
-The opposite of C<encode_json>: expects an UTF-8 (binary) string and tries
-to parse that as an UTF-8 encoded JSON text, returning the resulting
-reference.
-
-This function call is functionally identical to:
-
-    $perl_scalar = JSON::PP->new->utf8->decode($json_text)
-
-=head2 JSON::PP::is_bool
-
-    $is_boolean = JSON::PP::is_bool($scalar)
-
-Returns true if the passed scalar represents either JSON::PP::true or
-JSON::PP::false, two constants that act like C<1> and C<0> respectively
-and are also used to represent JSON C<true> and C<false> in Perl strings.
-
-=head2 JSON::PP::true
-
-Returns JSON true value which is blessed object.
-It C<isa> JSON::PP::Boolean object.
-
-=head2 JSON::PP::false
-
-Returns JSON false value which is blessed object.
-It C<isa> JSON::PP::Boolean object.
-
-=head2 JSON::PP::null
-
-Returns C<undef>.
-
-See L<MAPPING>, below, for more information on how JSON values are mapped to
-Perl.
-
-
-=head1 HOW DO I DECODE A DATA FROM OUTER AND ENCODE TO OUTER
-
-This section supposes that your perl version is 5.8 or later.
-
-If you know a JSON text from an outer world - a network, a file content, and so on,
-is encoded in UTF-8, you should use C<decode_json> or C<JSON> module object
-with C<utf8> enable. And the decoded result will contain UNICODE characters.
-
-  # from network
-  my $json        = JSON::PP->new->utf8;
-  my $json_text   = CGI->new->param( 'json_data' );
-  my $perl_scalar = $json->decode( $json_text );
-  
-  # from file content
-  local $/;
-  open( my $fh, '<', 'json.data' );
-  $json_text   = <$fh>;
-  $perl_scalar = decode_json( $json_text );
-
-If an outer data is not encoded in UTF-8, firstly you should C<decode> it.
-
-  use Encode;
-  local $/;
-  open( my $fh, '<', 'json.data' );
-  my $encoding = 'cp932';
-  my $unicode_json_text = decode( $encoding, <$fh> ); # UNICODE
-  
-  # or you can write the below code.
-  #
-  # open( my $fh, "<:encoding($encoding)", 'json.data' );
-  # $unicode_json_text = <$fh>;
-
-In this case, C<$unicode_json_text> is of course UNICODE string.
-So you B<cannot> use C<decode_json> nor C<JSON> module object with C<utf8> enable.
-Instead of them, you use C<JSON> module object with C<utf8> disable.
-
-  $perl_scalar = $json->utf8(0)->decode( $unicode_json_text );
-
-Or C<encode 'utf8'> and C<decode_json>:
-
-  $perl_scalar = decode_json( encode( 'utf8', $unicode_json_text ) );
-  # this way is not efficient.
-
-And now, you want to convert your C<$perl_scalar> into JSON data and
-send it to an outer world - a network or a file content, and so on.
-
-Your data usually contains UNICODE strings and you want the converted data to be encoded
-in UTF-8, you should use C<encode_json> or C<JSON> module object with C<utf8> enable.
-
-  print encode_json( $perl_scalar ); # to a network? file? or display?
-  # or
-  print $json->utf8->encode( $perl_scalar );
-
-If C<$perl_scalar> does not contain UNICODE but C<$encoding>-encoded strings
-for some reason, then its characters are regarded as B<latin1> for perl
-(because it does not concern with your $encoding).
-You B<cannot> use C<encode_json> nor C<JSON> module object with C<utf8> enable.
-Instead of them, you use C<JSON> module object with C<utf8> disable.
-Note that the resulted text is a UNICODE string but no problem to print it.
-
-  # $perl_scalar contains $encoding encoded string values
-  $unicode_json_text = $json->utf8(0)->encode( $perl_scalar );
-  # $unicode_json_text consists of characters less than 0x100
-  print $unicode_json_text;
-
-Or C<decode $encoding> all string values and C<encode_json>:
-
-  $perl_scalar->{ foo } = decode( $encoding, $perl_scalar->{ foo } );
-  # ... do it to each string values, then encode_json
-  $json_text = encode_json( $perl_scalar );
-
-This method is a proper way but probably not efficient.
-
-See to L<Encode>, L<perluniintro>.
-
-
-=head1 METHODS
-
-Basically, check to L<JSON> or L<JSON::XS>.
-
-=head2 new
-
-    $json = JSON::PP->new
-
-Returns a new JSON::PP object that can be used to de/encode JSON
-strings.
-
-All boolean flags described below are by default I<disabled>.
-
-The mutators for flags all return the JSON object again and thus calls can
-be chained:
-
-   my $json = JSON::PP->new->utf8->space_after->encode({a => [1,2]})
-   => {"a": [1, 2]}
-
-=head2 ascii
-
-    $json = $json->ascii([$enable])
-    
-    $enabled = $json->get_ascii
-
-If $enable is true (or missing), then the encode method will not generate characters outside
-the code range 0..127. Any Unicode characters outside that range will be escaped using either
-a single \uXXXX or a double \uHHHH\uLLLLL escape sequence, as per RFC4627.
-(See to L<JSON::XS/OBJECT-ORIENTED INTERFACE>).
-
-In Perl 5.005, there is no character having high value (more than 255).
-See to L<UNICODE HANDLING ON PERLS>.
-
-If $enable is false, then the encode method will not escape Unicode characters unless
-required by the JSON syntax or other flags. This results in a faster and more compact format.
-
-  JSON::PP->new->ascii(1)->encode([chr 0x10401])
-  => ["\ud801\udc01"]
-
-=head2 latin1
-
-    $json = $json->latin1([$enable])
-    
-    $enabled = $json->get_latin1
-
-If $enable is true (or missing), then the encode method will encode the resulting JSON
-text as latin1 (or iso-8859-1), escaping any characters outside the code range 0..255.
-
-If $enable is false, then the encode method will not escape Unicode characters
-unless required by the JSON syntax or other flags.
-
-  JSON::XS->new->latin1->encode (["\x{89}\x{abc}"]
-  => ["\x{89}\\u0abc"]    # (perl syntax, U+abc escaped, U+89 not)
-
-See to L<UNICODE HANDLING ON PERLS>.
-
-=head2 utf8
-
-    $json = $json->utf8([$enable])
-    
-    $enabled = $json->get_utf8
-
-If $enable is true (or missing), then the encode method will encode the JSON result
-into UTF-8, as required by many protocols, while the decode method expects to be handled
-an UTF-8-encoded string. Please note that UTF-8-encoded strings do not contain any
-characters outside the range 0..255, they are thus useful for bytewise/binary I/O.
-
-(In Perl 5.005, any character outside the range 0..255 does not exist.
-See to L<UNICODE HANDLING ON PERLS>.)
-
-In future versions, enabling this option might enable autodetection of the UTF-16 and UTF-32
-encoding families, as described in RFC4627.
-
-If $enable is false, then the encode method will return the JSON string as a (non-encoded)
-Unicode string, while decode expects thus a Unicode string. Any decoding or encoding
-(e.g. to UTF-8 or UTF-16) needs to be done yourself, e.g. using the Encode module.
-
-Example, output UTF-16BE-encoded JSON:
-
-  use Encode;
-  $jsontext = encode "UTF-16BE", JSON::PP->new->encode ($object);
-
-Example, decode UTF-32LE-encoded JSON:
-
-  use Encode;
-  $object = JSON::PP->new->decode (decode "UTF-32LE", $jsontext);
-
-
-=head2 pretty
-
-    $json = $json->pretty([$enable])
-
-This enables (or disables) all of the C<indent>, C<space_before> and
-C<space_after> flags in one call to generate the most readable
-(or most compact) form possible.
-
-Equivalent to:
-
-   $json->indent->space_before->space_after
-
-=head2 indent
-
-    $json = $json->indent([$enable])
-    
-    $enabled = $json->get_indent
-
-The default indent space length is three.
-You can use C<indent_length> to change the length.
-
-=head2 space_before
-
-    $json = $json->space_before([$enable])
-    
-    $enabled = $json->get_space_before
-
-If C<$enable> is true (or missing), then the C<encode> method will add an extra
-optional space before the C<:> separating keys from values in JSON objects.
-
-If C<$enable> is false, then the C<encode> method will not add any extra
-space at those places.
-
-This setting has no effect when decoding JSON texts.
-
-Example, space_before enabled, space_after and indent disabled:
-
-   {"key" :"value"}
-
-=head2 space_after
-
-    $json = $json->space_after([$enable])
-    
-    $enabled = $json->get_space_after
-
-If C<$enable> is true (or missing), then the C<encode> method will add an extra
-optional space after the C<:> separating keys from values in JSON objects
-and extra whitespace after the C<,> separating key-value pairs and array
-members.
-
-If C<$enable> is false, then the C<encode> method will not add any extra
-space at those places.
-
-This setting has no effect when decoding JSON texts.
-
-Example, space_before and indent disabled, space_after enabled:
-
-   {"key": "value"}
-
-=head2 relaxed
-
-    $json = $json->relaxed([$enable])
-    
-    $enabled = $json->get_relaxed
-
-If C<$enable> is true (or missing), then C<decode> will accept some
-extensions to normal JSON syntax (see below). C<encode> will not be
-affected in anyway. I<Be aware that this option makes you accept invalid
-JSON texts as if they were valid!>. I suggest only to use this option to
-parse application-specific files written by humans (configuration files,
-resource files etc.)
-
-If C<$enable> is false (the default), then C<decode> will only accept
-valid JSON texts.
-
-Currently accepted extensions are:
-
-=over 4
-
-=item * list items can have an end-comma
-
-JSON I<separates> array elements and key-value pairs with commas. This
-can be annoying if you write JSON texts manually and want to be able to
-quickly append elements, so this extension accepts comma at the end of
-such items not just between them:
-
-   [
-      1,
-      2, <- this comma not normally allowed
-   ]
-   {
-      "k1": "v1",
-      "k2": "v2", <- this comma not normally allowed
-   }
-
-=item * shell-style '#'-comments
-
-Whenever JSON allows whitespace, shell-style comments are additionally
-allowed. They are terminated by the first carriage-return or line-feed
-character, after which more white-space and comments are allowed.
-
-  [
-     1, # this comment not allowed in JSON
-        # neither this one...
-  ]
-
-=back
-
-=head2 canonical
-
-    $json = $json->canonical([$enable])
-    
-    $enabled = $json->get_canonical
-
-If C<$enable> is true (or missing), then the C<encode> method will output JSON objects
-by sorting their keys. This is adding a comparatively high overhead.
-
-If C<$enable> is false, then the C<encode> method will output key-value
-pairs in the order Perl stores them (which will likely change between runs
-of the same script).
-
-This option is useful if you want the same data structure to be encoded as
-the same JSON text (given the same overall settings). If it is disabled,
-the same hash might be encoded differently even if contains the same data,
-as key-value pairs have no inherent ordering in Perl.
-
-This setting has no effect when decoding JSON texts.
-
-If you want your own sorting routine, you can give a code reference
-or a subroutine name to C<sort_by>. See to C<JSON::PP OWN METHODS>.
-
-=head2 allow_nonref
-
-    $json = $json->allow_nonref([$enable])
-    
-    $enabled = $json->get_allow_nonref
-
-If C<$enable> is true (or missing), then the C<encode> method can convert a
-non-reference into its corresponding string, number or null JSON value,
-which is an extension to RFC4627. Likewise, C<decode> will accept those JSON
-values instead of croaking.
-
-If C<$enable> is false, then the C<encode> method will croak if it isn't
-passed an arrayref or hashref, as JSON texts must either be an object
-or array. Likewise, C<decode> will croak if given something that is not a
-JSON object or array.
-
-   JSON::PP->new->allow_nonref->encode ("Hello, World!")
-   => "Hello, World!"
-
-=head2 allow_unknown
-
-    $json = $json->allow_unknown ([$enable])
-    
-    $enabled = $json->get_allow_unknown
-
-If $enable is true (or missing), then "encode" will *not* throw an
-exception when it encounters values it cannot represent in JSON (for
-example, filehandles) but instead will encode a JSON "null" value.
-Note that blessed objects are not included here and are handled
-separately by c<allow_nonref>.
-
-If $enable is false (the default), then "encode" will throw an
-exception when it encounters anything it cannot encode as JSON.
-
-This option does not affect "decode" in any way, and it is
-recommended to leave it off unless you know your communications
-partner.
-
-=head2 allow_blessed
-
-    $json = $json->allow_blessed([$enable])
-    
-    $enabled = $json->get_allow_blessed
-
-If C<$enable> is true (or missing), then the C<encode> method will not
-barf when it encounters a blessed reference. Instead, the value of the
-B<convert_blessed> option will decide whether C<null> (C<convert_blessed>
-disabled or no C<TO_JSON> method found) or a representation of the
-object (C<convert_blessed> enabled and C<TO_JSON> method found) is being
-encoded. Has no effect on C<decode>.
-
-If C<$enable> is false (the default), then C<encode> will throw an
-exception when it encounters a blessed object.
-
-=head2 convert_blessed
-
-    $json = $json->convert_blessed([$enable])
-    
-    $enabled = $json->get_convert_blessed
-
-If C<$enable> is true (or missing), then C<encode>, upon encountering a
-blessed object, will check for the availability of the C<TO_JSON> method
-on the object's class. If found, it will be called in scalar context
-and the resulting scalar will be encoded instead of the object. If no
-C<TO_JSON> method is found, the value of C<allow_blessed> will decide what
-to do.
-
-The C<TO_JSON> method may safely call die if it wants. If C<TO_JSON>
-returns other blessed objects, those will be handled in the same
-way. C<TO_JSON> must take care of not causing an endless recursion cycle
-(== crash) in this case. The name of C<TO_JSON> was chosen because other
-methods called by the Perl core (== not by the user of the object) are
-usually in upper case letters and to avoid collisions with the C<to_json>
-function or method.
-
-This setting does not yet influence C<decode> in any way.
-
-If C<$enable> is false, then the C<allow_blessed> setting will decide what
-to do when a blessed object is found.
-
-=head2 filter_json_object
-
-    $json = $json->filter_json_object([$coderef])
-
-When C<$coderef> is specified, it will be called from C<decode> each
-time it decodes a JSON object. The only argument passed to the coderef
-is a reference to the newly-created hash. If the code references returns
-a single scalar (which need not be a reference), this value
-(i.e. a copy of that scalar to avoid aliasing) is inserted into the
-deserialised data structure. If it returns an empty list
-(NOTE: I<not> C<undef>, which is a valid scalar), the original deserialised
-hash will be inserted. This setting can slow down decoding considerably.
-
-When C<$coderef> is omitted or undefined, any existing callback will
-be removed and C<decode> will not change the deserialised hash in any
-way.
-
-Example, convert all JSON objects into the integer 5:
-
-   my $js = JSON::PP->new->filter_json_object (sub { 5 });
-   # returns [5]
-   $js->decode ('[{}]'); # the given subroutine takes a hash reference.
-   # throw an exception because allow_nonref is not enabled
-   # so a lone 5 is not allowed.
-   $js->decode ('{"a":1, "b":2}');
-
-=head2 filter_json_single_key_object
-
-    $json = $json->filter_json_single_key_object($key [=> $coderef])
-
-Works remotely similar to C<filter_json_object>, but is only called for
-JSON objects having a single key named C<$key>.
-
-This C<$coderef> is called before the one specified via
-C<filter_json_object>, if any. It gets passed the single value in the JSON
-object. If it returns a single value, it will be inserted into the data
-structure. If it returns nothing (not even C<undef> but the empty list),
-the callback from C<filter_json_object> will be called next, as if no
-single-key callback were specified.
-
-If C<$coderef> is omitted or undefined, the corresponding callback will be
-disabled. There can only ever be one callback for a given key.
-
-As this callback gets called less often then the C<filter_json_object>
-one, decoding speed will not usually suffer as much. Therefore, single-key
-objects make excellent targets to serialise Perl objects into, especially
-as single-key JSON objects are as close to the type-tagged value concept
-as JSON gets (it's basically an ID/VALUE tuple). Of course, JSON does not
-support this in any way, so you need to make sure your data never looks
-like a serialised Perl hash.
-
-Typical names for the single object key are C<__class_whatever__>, or
-C<$__dollars_are_rarely_used__$> or C<}ugly_brace_placement>, or even
-things like C<__class_md5sum(classname)__>, to reduce the risk of clashing
-with real hashes.
-
-Example, decode JSON objects of the form C<< { "__widget__" => <id> } >>
-into the corresponding C<< $WIDGET{<id>} >> object:
-
-   # return whatever is in $WIDGET{5}:
-   JSON::PP
-      ->new
-      ->filter_json_single_key_object (__widget__ => sub {
-            $WIDGET{ $_[0] }
-         })
-      ->decode ('{"__widget__": 5')
-
-   # this can be used with a TO_JSON method in some "widget" class
-   # for serialisation to json:
-   sub WidgetBase::TO_JSON {
-      my ($self) = @_;
-
-      unless ($self->{id}) {
-         $self->{id} = ..get..some..id..;
-         $WIDGET{$self->{id}} = $self;
-      }
-
-      { __widget__ => $self->{id} }
-   }
-
-=head2 shrink
-
-    $json = $json->shrink([$enable])
-    
-    $enabled = $json->get_shrink
-
-In JSON::XS, this flag resizes strings generated by either
-C<encode> or C<decode> to their minimum size possible.
-It will also try to downgrade any strings to octet-form if possible.
-
-In JSON::PP, it is noop about resizing strings but tries
-C<utf8::downgrade> to the returned string by C<encode>.
-See to L<utf8>.
-
-See to L<JSON::XS/OBJECT-ORIENTED INTERFACE>
-
-=head2 max_depth
-
-    $json = $json->max_depth([$maximum_nesting_depth])
-    
-    $max_depth = $json->get_max_depth
-
-Sets the maximum nesting level (default C<512>) accepted while encoding
-or decoding. If a higher nesting level is detected in JSON text or a Perl
-data structure, then the encoder and decoder will stop and croak at that
-point.
-
-Nesting level is defined by number of hash- or arrayrefs that the encoder
-needs to traverse to reach a given point or the number of C<{> or C<[>
-characters without their matching closing parenthesis crossed to reach a
-given character in a string.
-
-If no argument is given, the highest possible setting will be used, which
-is rarely useful.
-
-See L<JSON::XS/SSECURITY CONSIDERATIONS> for more info on why this is useful.
-
-When a large value (100 or more) was set and it de/encodes a deep nested object/text,
-it may raise a warning 'Deep recursion on subroutine' at the perl runtime phase.
-
-=head2 max_size
-
-    $json = $json->max_size([$maximum_string_size])
-    
-    $max_size = $json->get_max_size
-
-Set the maximum length a JSON text may have (in bytes) where decoding is
-being attempted. The default is C<0>, meaning no limit. When C<decode>
-is called on a string that is longer then this many bytes, it will not
-attempt to decode the string but throw an exception. This setting has no
-effect on C<encode> (yet).
-
-If no argument is given, the limit check will be deactivated (same as when
-C<0> is specified).
-
-See L<JSON::XS/SECURITY CONSIDERATIONS> for more info on why this is useful.
-
-=head2 encode
-
-    $json_text = $json->encode($perl_scalar)
-
-Converts the given Perl data structure (a simple scalar or a reference
-to a hash or array) to its JSON representation. Simple scalars will be
-converted into JSON string or number sequences, while references to arrays
-become JSON arrays and references to hashes become JSON objects. Undefined
-Perl values (e.g. C<undef>) become JSON C<null> values.
-References to the integers C<0> and C<1> are converted into C<true> and C<false>.
-
-=head2 decode
-
-    $perl_scalar = $json->decode($json_text)
-
-The opposite of C<encode>: expects a JSON text and tries to parse it,
-returning the resulting simple scalar or reference. Croaks on error.
-
-JSON numbers and strings become simple Perl scalars. JSON arrays become
-Perl arrayrefs and JSON objects become Perl hashrefs. C<true> becomes
-C<1> (C<JSON::true>), C<false> becomes C<0> (C<JSON::false>) and
-C<null> becomes C<undef>.
-
-=head2 decode_prefix
-
-    ($perl_scalar, $characters) = $json->decode_prefix($json_text)
-
-This works like the C<decode> method, but instead of raising an exception
-when there is trailing garbage after the first JSON object, it will
-silently stop parsing there and return the number of characters consumed
-so far.
-
-   JSON->new->decode_prefix ("[1] the tail")
-   => ([], 3)
-
-=head1 INCREMENTAL PARSING
-
-Most of this section are copied and modified from L<JSON::XS/INCREMENTAL PARSING>.
-
-In some cases, there is the need for incremental parsing of JSON texts.
-This module does allow you to parse a JSON stream incrementally.
-It does so by accumulating text until it has a full JSON object, which
-it then can decode. This process is similar to using C<decode_prefix>
-to see if a full JSON object is available, but is much more efficient
-(and can be implemented with a minimum of method calls).
-
-This module will only attempt to parse the JSON text once it is sure it
-has enough text to get a decisive result, using a very simple but
-truly incremental parser. This means that it sometimes won't stop as
-early as the full parser, for example, it doesn't detect parenthesis
-mismatches. The only thing it guarantees is that it starts decoding as
-soon as a syntactically valid JSON text has been seen. This means you need
-to set resource limits (e.g. C<max_size>) to ensure the parser will stop
-parsing in the presence if syntax errors.
-
-The following methods implement this incremental parser.
-
-=head2 incr_parse
-
-    $json->incr_parse( [$string] ) # void context
-    
-    $obj_or_undef = $json->incr_parse( [$string] ) # scalar context
-    
-    @obj_or_empty = $json->incr_parse( [$string] ) # list context
-
-This is the central parsing function. It can both append new text and
-extract objects from the stream accumulated so far (both of these
-functions are optional).
-
-If C<$string> is given, then this string is appended to the already
-existing JSON fragment stored in the C<$json> object.
-
-After that, if the function is called in void context, it will simply
-return without doing anything further. This can be used to add more text
-in as many chunks as you want.
-
-If the method is called in scalar context, then it will try to extract
-exactly I<one> JSON object. If that is successful, it will return this
-object, otherwise it will return C<undef>. If there is a parse error,
-this method will croak just as C<decode> would do (one can then use
-C<incr_skip> to skip the erroneous part). This is the most common way of
-using the method.
-
-And finally, in list context, it will try to extract as many objects
-from the stream as it can find and return them, or the empty list
-otherwise. For this to work, there must be no separators between the JSON
-objects or arrays, instead they must be concatenated back-to-back. If
-an error occurs, an exception will be raised as in the scalar context
-case. Note that in this case, any previously-parsed JSON texts will be
-lost.
-
-Example: Parse some JSON arrays/objects in a given string and return them.
-
-    my @objs = JSON->new->incr_parse ("[5][7][1,2]");
-
-=head2 incr_text
-
-    $lvalue_string = $json->incr_text
-
-This method returns the currently stored JSON fragment as an lvalue, that
-is, you can manipulate it. This I<only> works when a preceding call to
-C<incr_parse> in I<scalar context> successfully returned an object. Under
-all other circumstances you must not call this function (I mean it.
-although in simple tests it might actually work, it I<will> fail under
-real world conditions). As a special exception, you can also call this
-method before having parsed anything.
-
-This function is useful in two cases: a) finding the trailing text after a
-JSON object or b) parsing multiple JSON objects separated by non-JSON text
-(such as commas).
-
-    $json->incr_text =~ s/\s*,\s*//;
-
-In Perl 5.005, C<lvalue> attribute is not available.
-You must write codes like the below:
-
-    $string = $json->incr_text;
-    $string =~ s/\s*,\s*//;
-    $json->incr_text( $string );
-
-=head2 incr_skip
-
-    $json->incr_skip
-
-This will reset the state of the incremental parser and will remove the
-parsed text from the input buffer. This is useful after C<incr_parse>
-died, in which case the input buffer and incremental parser state is left
-unchanged, to skip the text parsed so far and to reset the parse state.
-
-=head2 incr_reset
-
-    $json->incr_reset
-
-This completely resets the incremental parser, that is, after this call,
-it will be as if the parser had never parsed anything.
-
-This is useful if you want to repeatedly parse JSON objects and want to
-ignore any trailing data, which means you have to reset the parser after
-each successful decode.
-
-See to L<JSON::XS/INCREMENTAL PARSING> for examples.
-
-
-=head1 JSON::PP OWN METHODS
-
-=head2 allow_singlequote
-
-    $json = $json->allow_singlequote([$enable])
-
-If C<$enable> is true (or missing), then C<decode> will accept
-JSON strings quoted by single quotations that are invalid JSON
-format.
-
-    $json->allow_singlequote->decode({"foo":'bar'});
-    $json->allow_singlequote->decode({'foo':"bar"});
-    $json->allow_singlequote->decode({'foo':'bar'});
-
-As same as the C<relaxed> option, this option may be used to parse
-application-specific files written by humans.
-
-
-=head2 allow_barekey
-
-    $json = $json->allow_barekey([$enable])
-
-If C<$enable> is true (or missing), then C<decode> will accept
-bare keys of JSON object that are invalid JSON format.
-
-As same as the C<relaxed> option, this option may be used to parse
-application-specific files written by humans.
-
-    $json->allow_barekey->decode('{foo:"bar"}');
-
-=head2 allow_bignum
-
-    $json = $json->allow_bignum([$enable])
-
-If C<$enable> is true (or missing), then C<decode> will convert
-the big integer Perl cannot handle as integer into a L<Math::BigInt>
-object and convert a floating number (any) into a L<Math::BigFloat>.
-
-On the contrary, C<encode> converts C<Math::BigInt> objects and C<Math::BigFloat>
-objects into JSON numbers with C<allow_blessed> enable.
-
-   $json->allow_nonref->allow_blessed->allow_bignum;
-   $bigfloat = $json->decode('2.000000000000000000000000001');
-   print $json->encode($bigfloat);
-   # => 2.000000000000000000000000001
-
-See to L<JSON::XS/MAPPING> about the normal conversion of JSON number.
-
-=head2 loose
-
-    $json = $json->loose([$enable])
-
-The unescaped [\x00-\x1f\x22\x2f\x5c] strings are invalid in JSON strings
-and the module doesn't allow to C<decode> to these (except for \x2f).
-If C<$enable> is true (or missing), then C<decode>  will accept these
-unescaped strings.
-
-    $json->loose->decode(qq|["abc
-                                   def"]|);
-
-See L<JSON::XS/SSECURITY CONSIDERATIONS>.
-
-=head2 escape_slash
-
-    $json = $json->escape_slash([$enable])
-
-According to JSON Grammar, I<slash> (U+002F) is escaped. But default
-JSON::PP (as same as JSON::XS) encodes strings without escaping slash.
-
-If C<$enable> is true (or missing), then C<encode> will escape slashes.
-
-=head2 indent_length
-
-    $json = $json->indent_length($length)
-
-JSON::XS indent space length is 3 and cannot be changed.
-JSON::PP set the indent space length with the given $length.
-The default is 3. The acceptable range is 0 to 15.
-
-=head2 sort_by
-
-    $json = $json->sort_by($function_name)
-    $json = $json->sort_by($subroutine_ref)
-
-If $function_name or $subroutine_ref are set, its sort routine are used
-in encoding JSON objects.
-
-   $js = $pc->sort_by(sub { $JSON::PP::a cmp $JSON::PP::b })->encode($obj);
-   # is($js, q|{"a":1,"b":2,"c":3,"d":4,"e":5,"f":6,"g":7,"h":8,"i":9}|);
-
-   $js = $pc->sort_by('own_sort')->encode($obj);
-   # is($js, q|{"a":1,"b":2,"c":3,"d":4,"e":5,"f":6,"g":7,"h":8,"i":9}|);
-
-   sub JSON::PP::own_sort { $JSON::PP::a cmp $JSON::PP::b }
-
-As the sorting routine runs in the JSON::PP scope, the given
-subroutine name and the special variables C<$a>, C<$b> will begin
-'JSON::PP::'.
-
-If $integer is set, then the effect is same as C<canonical> on.
-
-=head1 INTERNAL
-
-For developers.
-
-=over
-
-=item PP_encode_box
-
-Returns
-
-        {
-            depth        => $depth,
-            indent_count => $indent_count,
-        }
-
-
-=item PP_decode_box
-
-Returns
-
-        {
-            text    => $text,
-            at      => $at,
-            ch      => $ch,
-            len     => $len,
-            depth   => $depth,
-            encoding      => $encoding,
-            is_valid_utf8 => $is_valid_utf8,
-        };
-
-=back
-
-=head1 MAPPING
-
-This section is copied from JSON::XS and modified to C<JSON::PP>.
-JSON::XS and JSON::PP mapping mechanisms are almost equivalent.
-
-See to L<JSON::XS/MAPPING>.
-
-=head2 JSON -> PERL
-
-=over 4
-
-=item object
-
-A JSON object becomes a reference to a hash in Perl. No ordering of object
-keys is preserved (JSON does not preserver object key ordering itself).
-
-=item array
-
-A JSON array becomes a reference to an array in Perl.
-
-=item string
-
-A JSON string becomes a string scalar in Perl - Unicode codepoints in JSON
-are represented by the same codepoints in the Perl string, so no manual
-decoding is necessary.
-
-=item number
-
-A JSON number becomes either an integer, numeric (floating point) or
-string scalar in perl, depending on its range and any fractional parts. On
-the Perl level, there is no difference between those as Perl handles all
-the conversion details, but an integer may take slightly less memory and
-might represent more values exactly than floating point numbers.
-
-If the number consists of digits only, C<JSON> will try to represent
-it as an integer value. If that fails, it will try to represent it as
-a numeric (floating point) value if that is possible without loss of
-precision. Otherwise it will preserve the number as a string value (in
-which case you lose roundtripping ability, as the JSON number will be
-re-encoded to a JSON string).
-
-Numbers containing a fractional or exponential part will always be
-represented as numeric (floating point) values, possibly at a loss of
-precision (in which case you might lose perfect roundtripping ability, but
-the JSON number will still be re-encoded as a JSON number).
-
-Note that precision is not accuracy - binary floating point values cannot
-represent most decimal fractions exactly, and when converting from and to
-floating point, C<JSON> only guarantees precision up to but not including
-the least significant bit.
-
-When C<allow_bignum> is enable, the big integers 
-and the numeric can be optionally converted into L<Math::BigInt> and
-L<Math::BigFloat> objects.
-
-=item true, false
-
-These JSON atoms become C<JSON::PP::true> and C<JSON::PP::false>,
-respectively. They are overloaded to act almost exactly like the numbers
-C<1> and C<0>. You can check whether a scalar is a JSON boolean by using
-the C<JSON::is_bool> function.
-
-   print JSON::PP::true . "\n";
-    => true
-   print JSON::PP::true + 1;
-    => 1
-
-   ok(JSON::true eq  '1');
-   ok(JSON::true == 1);
-
-C<JSON> will install these missing overloading features to the backend modules.
-
-
-=item null
-
-A JSON null atom becomes C<undef> in Perl.
-
-C<JSON::PP::null> returns C<undef>.
-
-=back
-
-
-=head2 PERL -> JSON
-
-The mapping from Perl to JSON is slightly more difficult, as Perl is a
-truly typeless language, so we can only guess which JSON type is meant by
-a Perl value.
-
-=over 4
-
-=item hash references
-
-Perl hash references become JSON objects. As there is no inherent ordering
-in hash keys (or JSON objects), they will usually be encoded in a
-pseudo-random order that can change between runs of the same program but
-stays generally the same within a single run of a program. C<JSON>
-optionally sort the hash keys (determined by the I<canonical> flag), so
-the same data structure will serialise to the same JSON text (given same
-settings and version of JSON::XS), but this incurs a runtime overhead
-and is only rarely useful, e.g. when you want to compare some JSON text
-against another for equality.
-
-
-=item array references
-
-Perl array references become JSON arrays.
-
-=item other references
-
-Other unblessed references are generally not allowed and will cause an
-exception to be thrown, except for references to the integers C<0> and
-C<1>, which get turned into C<false> and C<true> atoms in JSON. You can
-also use C<JSON::false> and C<JSON::true> to improve readability.
-
-   to_json [\0,JSON::PP::true]      # yields [false,true]
-
-=item JSON::PP::true, JSON::PP::false, JSON::PP::null
-
-These special values become JSON true and JSON false values,
-respectively. You can also use C<\1> and C<\0> directly if you want.
-
-JSON::PP::null returns C<undef>.
-
-=item blessed objects
-
-Blessed objects are not directly representable in JSON. See the
-C<allow_blessed> and C<convert_blessed> methods on various options on
-how to deal with this: basically, you can choose between throwing an
-exception, encoding the reference as if it weren't blessed, or provide
-your own serialiser method.
-
-See to L<convert_blessed>.
-
-=item simple scalars
-
-Simple Perl scalars (any scalar that is not a reference) are the most
-difficult objects to encode: JSON::XS and JSON::PP will encode undefined scalars as
-JSON C<null> values, scalars that have last been used in a string context
-before encoding as JSON strings, and anything else as number value:
-
-   # dump as number
-   encode_json [2]                      # yields [2]
-   encode_json [-3.0e17]                # yields [-3e+17]
-   my $value = 5; encode_json [$value]  # yields [5]
-
-   # used as string, so dump as string
-   print $value;
-   encode_json [$value]                 # yields ["5"]
-
-   # undef becomes null
-   encode_json [undef]                  # yields [null]
-
-You can force the type to be a string by stringifying it:
-
-   my $x = 3.1; # some variable containing a number
-   "$x";        # stringified
-   $x .= "";    # another, more awkward way to stringify
-   print $x;    # perl does it for you, too, quite often
-
-You can force the type to be a number by numifying it:
-
-   my $x = "3"; # some variable containing a string
-   $x += 0;     # numify it, ensuring it will be dumped as a number
-   $x *= 1;     # same thing, the choice is yours.
-
-You can not currently force the type in other, less obscure, ways.
-
-Note that numerical precision has the same meaning as under Perl (so
-binary to decimal conversion follows the same rules as in Perl, which
-can differ to other languages). Also, your perl interpreter might expose
-extensions to the floating point numbers of your platform, such as
-infinities or NaN's - these cannot be represented in JSON, and it is an
-error to pass those in.
-
-=item Big Number
-
-When C<allow_bignum> is enable, 
-C<encode> converts C<Math::BigInt> objects and C<Math::BigFloat>
-objects into JSON numbers.
-
-
-=back
-
-=head1 UNICODE HANDLING ON PERLS
-
-If you do not know about Unicode on Perl well,
-please check L<JSON::XS/A FEW NOTES ON UNICODE AND PERL>.
-
-=head2 Perl 5.8 and later
-
-Perl can handle Unicode and the JSON::PP de/encode methods also work properly.
-
-    $json->allow_nonref->encode(chr hex 3042);
-    $json->allow_nonref->encode(chr hex 12345);
-
-Returns C<"\u3042"> and C<"\ud808\udf45"> respectively.
-
-    $json->allow_nonref->decode('"\u3042"');
-    $json->allow_nonref->decode('"\ud808\udf45"');
-
-Returns UTF-8 encoded strings with UTF8 flag, regarded as C<U+3042> and C<U+12345>.
-
-Note that the versions from Perl 5.8.0 to 5.8.2, Perl built-in C<join> was broken,
-so JSON::PP wraps the C<join> with a subroutine. Thus JSON::PP works slow in the versions.
-
-
-=head2 Perl 5.6
-
-Perl can handle Unicode and the JSON::PP de/encode methods also work.
-
-=head2 Perl 5.005
-
-Perl 5.005 is a byte semantics world -- all strings are sequences of bytes.
-That means the unicode handling is not available.
-
-In encoding,
-
-    $json->allow_nonref->encode(chr hex 3042);  # hex 3042 is 12354.
-    $json->allow_nonref->encode(chr hex 12345); # hex 12345 is 74565.
-
-Returns C<B> and C<E>, as C<chr> takes a value more than 255, it treats
-as C<$value % 256>, so the above codes are equivalent to :
-
-    $json->allow_nonref->encode(chr 66);
-    $json->allow_nonref->encode(chr 69);
-
-In decoding,
-
-    $json->decode('"\u00e3\u0081\u0082"');
-
-The returned is a byte sequence C<0xE3 0x81 0x82> for UTF-8 encoded
-japanese character (C<HIRAGANA LETTER A>).
-And if it is represented in Unicode code point, C<U+3042>.
-
-Next, 
-
-    $json->decode('"\u3042"');
-
-We ordinary expect the returned value is a Unicode character C<U+3042>.
-But here is 5.005 world. This is C<0xE3 0x81 0x82>.
-
-    $json->decode('"\ud808\udf45"');
-
-This is not a character C<U+12345> but bytes - C<0xf0 0x92 0x8d 0x85>.
-
-
-=head1 TODO
-
-=over
-
-=item speed
-
-=item memory saving
-
-=back
-
-
-=head1 SEE ALSO
-
-Most of the document are copied and modified from JSON::XS doc.
-
-L<JSON::XS>
-
-RFC4627 (L<http://www.ietf.org/rfc/rfc4627.txt>)
-
-=head1 AUTHOR
-
-Makamaka Hannyaharamitu, E<lt>makamaka[at]cpan.orgE<gt>
-
-
-=head1 COPYRIGHT AND LICENSE
-
-Copyright 2007-2012 by Makamaka Hannyaharamitu
-
-This library is free software; you can redistribute it and/or modify
-it under the same terms as Perl itself. 
-
-=cut

spaces/Alpaca233/SadTalker/src/face3d/models/arcface_torch/eval/verification.py

@@ -1,407 +0,0 @@
-"""Helper for evaluation on the Labeled Faces in the Wild dataset 
-"""
-
-# MIT License
-#
-# Copyright (c) 2016 David Sandberg
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in all
-# copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-# SOFTWARE.
-
-
-import datetime
-import os
-import pickle
-
-import mxnet as mx
-import numpy as np
-import sklearn
-import torch
-from mxnet import ndarray as nd
-from scipy import interpolate
-from sklearn.decomposition import PCA
-from sklearn.model_selection import KFold
-
-
-class LFold:
-    def __init__(self, n_splits=2, shuffle=False):
-        self.n_splits = n_splits
-        if self.n_splits > 1:
-            self.k_fold = KFold(n_splits=n_splits, shuffle=shuffle)
-
-    def split(self, indices):
-        if self.n_splits > 1:
-            return self.k_fold.split(indices)
-        else:
-            return [(indices, indices)]
-
-
-def calculate_roc(thresholds,
-                  embeddings1,
-                  embeddings2,
-                  actual_issame,
-                  nrof_folds=10,
-                  pca=0):
-    assert (embeddings1.shape[0] == embeddings2.shape[0])
-    assert (embeddings1.shape[1] == embeddings2.shape[1])
-    nrof_pairs = min(len(actual_issame), embeddings1.shape[0])
-    nrof_thresholds = len(thresholds)
-    k_fold = LFold(n_splits=nrof_folds, shuffle=False)
-
-    tprs = np.zeros((nrof_folds, nrof_thresholds))
-    fprs = np.zeros((nrof_folds, nrof_thresholds))
-    accuracy = np.zeros((nrof_folds))
-    indices = np.arange(nrof_pairs)
-
-    if pca == 0:
-        diff = np.subtract(embeddings1, embeddings2)
-        dist = np.sum(np.square(diff), 1)
-
-    for fold_idx, (train_set, test_set) in enumerate(k_fold.split(indices)):
-        if pca > 0:
-            print('doing pca on', fold_idx)
-            embed1_train = embeddings1[train_set]
-            embed2_train = embeddings2[train_set]
-            _embed_train = np.concatenate((embed1_train, embed2_train), axis=0)
-            pca_model = PCA(n_components=pca)
-            pca_model.fit(_embed_train)
-            embed1 = pca_model.transform(embeddings1)
-            embed2 = pca_model.transform(embeddings2)
-            embed1 = sklearn.preprocessing.normalize(embed1)
-            embed2 = sklearn.preprocessing.normalize(embed2)
-            diff = np.subtract(embed1, embed2)
-            dist = np.sum(np.square(diff), 1)
-
-        # Find the best threshold for the fold
-        acc_train = np.zeros((nrof_thresholds))
-        for threshold_idx, threshold in enumerate(thresholds):
-            _, _, acc_train[threshold_idx] = calculate_accuracy(
-                threshold, dist[train_set], actual_issame[train_set])
-        best_threshold_index = np.argmax(acc_train)
-        for threshold_idx, threshold in enumerate(thresholds):
-            tprs[fold_idx, threshold_idx], fprs[fold_idx, threshold_idx], _ = calculate_accuracy(
-                threshold, dist[test_set],
-                actual_issame[test_set])
-        _, _, accuracy[fold_idx] = calculate_accuracy(
-            thresholds[best_threshold_index], dist[test_set],
-            actual_issame[test_set])
-
-    tpr = np.mean(tprs, 0)
-    fpr = np.mean(fprs, 0)
-    return tpr, fpr, accuracy
-
-
-def calculate_accuracy(threshold, dist, actual_issame):
-    predict_issame = np.less(dist, threshold)
-    tp = np.sum(np.logical_and(predict_issame, actual_issame))
-    fp = np.sum(np.logical_and(predict_issame, np.logical_not(actual_issame)))
-    tn = np.sum(
-        np.logical_and(np.logical_not(predict_issame),
-                       np.logical_not(actual_issame)))
-    fn = np.sum(np.logical_and(np.logical_not(predict_issame), actual_issame))
-
-    tpr = 0 if (tp + fn == 0) else float(tp) / float(tp + fn)
-    fpr = 0 if (fp + tn == 0) else float(fp) / float(fp + tn)
-    acc = float(tp + tn) / dist.size
-    return tpr, fpr, acc
-
-
-def calculate_val(thresholds,
-                  embeddings1,
-                  embeddings2,
-                  actual_issame,
-                  far_target,
-                  nrof_folds=10):
-    assert (embeddings1.shape[0] == embeddings2.shape[0])
-    assert (embeddings1.shape[1] == embeddings2.shape[1])
-    nrof_pairs = min(len(actual_issame), embeddings1.shape[0])
-    nrof_thresholds = len(thresholds)
-    k_fold = LFold(n_splits=nrof_folds, shuffle=False)
-
-    val = np.zeros(nrof_folds)
-    far = np.zeros(nrof_folds)
-
-    diff = np.subtract(embeddings1, embeddings2)
-    dist = np.sum(np.square(diff), 1)
-    indices = np.arange(nrof_pairs)
-
-    for fold_idx, (train_set, test_set) in enumerate(k_fold.split(indices)):
-
-        # Find the threshold that gives FAR = far_target
-        far_train = np.zeros(nrof_thresholds)
-        for threshold_idx, threshold in enumerate(thresholds):
-            _, far_train[threshold_idx] = calculate_val_far(
-                threshold, dist[train_set], actual_issame[train_set])
-        if np.max(far_train) >= far_target:
-            f = interpolate.interp1d(far_train, thresholds, kind='slinear')
-            threshold = f(far_target)
-        else:
-            threshold = 0.0
-
-        val[fold_idx], far[fold_idx] = calculate_val_far(
-            threshold, dist[test_set], actual_issame[test_set])
-
-    val_mean = np.mean(val)
-    far_mean = np.mean(far)
-    val_std = np.std(val)
-    return val_mean, val_std, far_mean
-
-
-def calculate_val_far(threshold, dist, actual_issame):
-    predict_issame = np.less(dist, threshold)
-    true_accept = np.sum(np.logical_and(predict_issame, actual_issame))
-    false_accept = np.sum(
-        np.logical_and(predict_issame, np.logical_not(actual_issame)))
-    n_same = np.sum(actual_issame)
-    n_diff = np.sum(np.logical_not(actual_issame))
-    # print(true_accept, false_accept)
-    # print(n_same, n_diff)
-    val = float(true_accept) / float(n_same)
-    far = float(false_accept) / float(n_diff)
-    return val, far
-
-
-def evaluate(embeddings, actual_issame, nrof_folds=10, pca=0):
-    # Calculate evaluation metrics
-    thresholds = np.arange(0, 4, 0.01)
-    embeddings1 = embeddings[0::2]
-    embeddings2 = embeddings[1::2]
-    tpr, fpr, accuracy = calculate_roc(thresholds,
-                                       embeddings1,
-                                       embeddings2,
-                                       np.asarray(actual_issame),
-                                       nrof_folds=nrof_folds,
-                                       pca=pca)
-    thresholds = np.arange(0, 4, 0.001)
-    val, val_std, far = calculate_val(thresholds,
-                                      embeddings1,
-                                      embeddings2,
-                                      np.asarray(actual_issame),
-                                      1e-3,
-                                      nrof_folds=nrof_folds)
-    return tpr, fpr, accuracy, val, val_std, far
-
-@torch.no_grad()
-def load_bin(path, image_size):
-    try:
-        with open(path, 'rb') as f:
-            bins, issame_list = pickle.load(f)  # py2
-    except UnicodeDecodeError as e:
-        with open(path, 'rb') as f:
-            bins, issame_list = pickle.load(f, encoding='bytes')  # py3
-    data_list = []
-    for flip in [0, 1]:
-        data = torch.empty((len(issame_list) * 2, 3, image_size[0], image_size[1]))
-        data_list.append(data)
-    for idx in range(len(issame_list) * 2):
-        _bin = bins[idx]
-        img = mx.image.imdecode(_bin)
-        if img.shape[1] != image_size[0]:
-            img = mx.image.resize_short(img, image_size[0])
-        img = nd.transpose(img, axes=(2, 0, 1))
-        for flip in [0, 1]:
-            if flip == 1:
-                img = mx.ndarray.flip(data=img, axis=2)
-            data_list[flip][idx][:] = torch.from_numpy(img.asnumpy())
-        if idx % 1000 == 0:
-            print('loading bin', idx)
-    print(data_list[0].shape)
-    return data_list, issame_list
-
-@torch.no_grad()
-def test(data_set, backbone, batch_size, nfolds=10):
-    print('testing verification..')
-    data_list = data_set[0]
-    issame_list = data_set[1]
-    embeddings_list = []
-    time_consumed = 0.0
-    for i in range(len(data_list)):
-        data = data_list[i]
-        embeddings = None
-        ba = 0
-        while ba < data.shape[0]:
-            bb = min(ba + batch_size, data.shape[0])
-            count = bb - ba
-            _data = data[bb - batch_size: bb]
-            time0 = datetime.datetime.now()
-            img = ((_data / 255) - 0.5) / 0.5
-            net_out: torch.Tensor = backbone(img)
-            _embeddings = net_out.detach().cpu().numpy()
-            time_now = datetime.datetime.now()
-            diff = time_now - time0
-            time_consumed += diff.total_seconds()
-            if embeddings is None:
-                embeddings = np.zeros((data.shape[0], _embeddings.shape[1]))
-            embeddings[ba:bb, :] = _embeddings[(batch_size - count):, :]
-            ba = bb
-        embeddings_list.append(embeddings)
-
-    _xnorm = 0.0
-    _xnorm_cnt = 0
-    for embed in embeddings_list:
-        for i in range(embed.shape[0]):
-            _em = embed[i]
-            _norm = np.linalg.norm(_em)
-            _xnorm += _norm
-            _xnorm_cnt += 1
-    _xnorm /= _xnorm_cnt
-
-    acc1 = 0.0
-    std1 = 0.0
-    embeddings = embeddings_list[0] + embeddings_list[1]
-    embeddings = sklearn.preprocessing.normalize(embeddings)
-    print(embeddings.shape)
-    print('infer time', time_consumed)
-    _, _, accuracy, val, val_std, far = evaluate(embeddings, issame_list, nrof_folds=nfolds)
-    acc2, std2 = np.mean(accuracy), np.std(accuracy)
-    return acc1, std1, acc2, std2, _xnorm, embeddings_list
-
-
-def dumpR(data_set,
-          backbone,
-          batch_size,
-          name='',
-          data_extra=None,
-          label_shape=None):
-    print('dump verification embedding..')
-    data_list = data_set[0]
-    issame_list = data_set[1]
-    embeddings_list = []
-    time_consumed = 0.0
-    for i in range(len(data_list)):
-        data = data_list[i]
-        embeddings = None
-        ba = 0
-        while ba < data.shape[0]:
-            bb = min(ba + batch_size, data.shape[0])
-            count = bb - ba
-
-            _data = nd.slice_axis(data, axis=0, begin=bb - batch_size, end=bb)
-            time0 = datetime.datetime.now()
-            if data_extra is None:
-                db = mx.io.DataBatch(data=(_data,), label=(_label,))
-            else:
-                db = mx.io.DataBatch(data=(_data, _data_extra),
-                                     label=(_label,))
-            model.forward(db, is_train=False)
-            net_out = model.get_outputs()
-            _embeddings = net_out[0].asnumpy()
-            time_now = datetime.datetime.now()
-            diff = time_now - time0
-            time_consumed += diff.total_seconds()
-            if embeddings is None:
-                embeddings = np.zeros((data.shape[0], _embeddings.shape[1]))
-            embeddings[ba:bb, :] = _embeddings[(batch_size - count):, :]
-            ba = bb
-        embeddings_list.append(embeddings)
-    embeddings = embeddings_list[0] + embeddings_list[1]
-    embeddings = sklearn.preprocessing.normalize(embeddings)
-    actual_issame = np.asarray(issame_list)
-    outname = os.path.join('temp.bin')
-    with open(outname, 'wb') as f:
-        pickle.dump((embeddings, issame_list),
-                    f,
-                    protocol=pickle.HIGHEST_PROTOCOL)
-
-
-# if __name__ == '__main__':
-#
-#     parser = argparse.ArgumentParser(description='do verification')
-#     # general
-#     parser.add_argument('--data-dir', default='', help='')
-#     parser.add_argument('--model',
-#                         default='../model/softmax,50',
-#                         help='path to load model.')
-#     parser.add_argument('--target',
-#                         default='lfw,cfp_ff,cfp_fp,agedb_30',
-#                         help='test targets.')
-#     parser.add_argument('--gpu', default=0, type=int, help='gpu id')
-#     parser.add_argument('--batch-size', default=32, type=int, help='')
-#     parser.add_argument('--max', default='', type=str, help='')
-#     parser.add_argument('--mode', default=0, type=int, help='')
-#     parser.add_argument('--nfolds', default=10, type=int, help='')
-#     args = parser.parse_args()
-#     image_size = [112, 112]
-#     print('image_size', image_size)
-#     ctx = mx.gpu(args.gpu)
-#     nets = []
-#     vec = args.model.split(',')
-#     prefix = args.model.split(',')[0]
-#     epochs = []
-#     if len(vec) == 1:
-#         pdir = os.path.dirname(prefix)
-#         for fname in os.listdir(pdir):
-#             if not fname.endswith('.params'):
-#                 continue
-#             _file = os.path.join(pdir, fname)
-#             if _file.startswith(prefix):
-#                 epoch = int(fname.split('.')[0].split('-')[1])
-#                 epochs.append(epoch)
-#         epochs = sorted(epochs, reverse=True)
-#         if len(args.max) > 0:
-#             _max = [int(x) for x in args.max.split(',')]
-#             assert len(_max) == 2
-#             if len(epochs) > _max[1]:
-#                 epochs = epochs[_max[0]:_max[1]]
-#
-#     else:
-#         epochs = [int(x) for x in vec[1].split('|')]
-#     print('model number', len(epochs))
-#     time0 = datetime.datetime.now()
-#     for epoch in epochs:
-#         print('loading', prefix, epoch)
-#         sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
-#         # arg_params, aux_params = ch_dev(arg_params, aux_params, ctx)
-#         all_layers = sym.get_internals()
-#         sym = all_layers['fc1_output']
-#         model = mx.mod.Module(symbol=sym, context=ctx, label_names=None)
-#         # model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0], image_size[1]))], label_shapes=[('softmax_label', (args.batch_size,))])
-#         model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0],
-#                                           image_size[1]))])
-#         model.set_params(arg_params, aux_params)
-#         nets.append(model)
-#     time_now = datetime.datetime.now()
-#     diff = time_now - time0
-#     print('model loading time', diff.total_seconds())
-#
-#     ver_list = []
-#     ver_name_list = []
-#     for name in args.target.split(','):
-#         path = os.path.join(args.data_dir, name + ".bin")
-#         if os.path.exists(path):
-#             print('loading.. ', name)
-#             data_set = load_bin(path, image_size)
-#             ver_list.append(data_set)
-#             ver_name_list.append(name)
-#
-#     if args.mode == 0:
-#         for i in range(len(ver_list)):
-#             results = []
-#             for model in nets:
-#                 acc1, std1, acc2, std2, xnorm, embeddings_list = test(
-#                     ver_list[i], model, args.batch_size, args.nfolds)
-#                 print('[%s]XNorm: %f' % (ver_name_list[i], xnorm))
-#                 print('[%s]Accuracy: %1.5f+-%1.5f' % (ver_name_list[i], acc1, std1))
-#                 print('[%s]Accuracy-Flip: %1.5f+-%1.5f' % (ver_name_list[i], acc2, std2))
-#                 results.append(acc2)
-#             print('Max of [%s] is %1.5f' % (ver_name_list[i], np.max(results)))
-#     elif args.mode == 1:
-#         raise ValueError
-#     else:
-#         model = nets[0]
-#         dumpR(ver_list[0], model, args.batch_size, args.target)

spaces/Amrrs/DragGan-Inversion/stylegan_human/pti/training/coaches/localitly_regulizer.py

@@ -1,70 +0,0 @@
-import torch
-import numpy as np
-import wandb
-from pti.pti_configs import hyperparameters, global_config
-l2_criterion = torch.nn.MSELoss(reduction='mean')
-
-
-def l2_loss(real_images, generated_images):
-    loss = l2_criterion(real_images, generated_images)
-    return loss
-
-
-class Space_Regulizer:
-    def __init__(self, original_G, lpips_net):
-        self.original_G = original_G
-        self.morphing_regulizer_alpha = hyperparameters.regulizer_alpha
-        self.lpips_loss = lpips_net
-
-    def get_morphed_w_code(self, new_w_code, fixed_w):
-        interpolation_direction = new_w_code - fixed_w
-        interpolation_direction_norm = torch.norm(interpolation_direction, p=2)
-        direction_to_move = hyperparameters.regulizer_alpha * \
-            interpolation_direction / interpolation_direction_norm
-        result_w = fixed_w + direction_to_move
-        self.morphing_regulizer_alpha * fixed_w + \
-            (1 - self.morphing_regulizer_alpha) * new_w_code
-
-        return result_w
-
-    def get_image_from_ws(self, w_codes, G):
-        return torch.cat([G.synthesis(w_code, noise_mode='none', force_fp32=True) for w_code in w_codes])
-
-    def ball_holder_loss_lazy(self, new_G, num_of_sampled_latents, w_batch, use_wandb=False):
-        loss = 0.0
-
-        z_samples = np.random.randn(
-            num_of_sampled_latents, self.original_G.z_dim)
-        w_samples = self.original_G.mapping(torch.from_numpy(z_samples).to(global_config.device), None,
-                                            truncation_psi=0.5)
-        territory_indicator_ws = [self.get_morphed_w_code(
-            w_code.unsqueeze(0), w_batch) for w_code in w_samples]
-
-        for w_code in territory_indicator_ws:
-            new_img = new_G.synthesis(
-                w_code, noise_mode='none', force_fp32=True)
-            with torch.no_grad():
-                old_img = self.original_G.synthesis(
-                    w_code, noise_mode='none', force_fp32=True)
-
-            if hyperparameters.regulizer_l2_lambda > 0:
-                l2_loss_val = l2_loss.l2_loss(old_img, new_img)
-                if use_wandb:
-                    wandb.log({f'space_regulizer_l2_loss_val': l2_loss_val.detach().cpu()},
-                              step=global_config.training_step)
-                loss += l2_loss_val * hyperparameters.regulizer_l2_lambda
-
-            if hyperparameters.regulizer_lpips_lambda > 0:
-                loss_lpips = self.lpips_loss(old_img, new_img)
-                loss_lpips = torch.mean(torch.squeeze(loss_lpips))
-                if use_wandb:
-                    wandb.log({f'space_regulizer_lpips_loss_val': loss_lpips.detach().cpu()},
-                              step=global_config.training_step)
-                loss += loss_lpips * hyperparameters.regulizer_lpips_lambda
-
-        return loss / len(territory_indicator_ws)
-
-    def space_regulizer_loss(self, new_G, w_batch, use_wandb):
-        ret_val = self.ball_holder_loss_lazy(
-            new_G, hyperparameters.latent_ball_num_of_samples, w_batch, use_wandb)
-        return ret_val

spaces/AnTo2209/3D_Zeroshot_Neural_Style_Transfer/src/sampler/simple_sampler.py

@@ -1,39 +0,0 @@
-import numpy as np
-import torch
-
-
-class SimpleSampler:
-    def __init__(self, total, batch):
-        self.total = total
-        self.batch = batch
-        self.curr = total
-        self.ids = None
-
-    def nextids(self):
-        self.curr+=self.batch
-        if self.curr + self.batch > self.total:
-            self.ids = torch.LongTensor(np.random.permutation(self.total))
-            self.curr = 0
-        return self.ids[self.curr:self.curr+self.batch]
-
-def InfiniteSampler(n):
-    # i = 0
-    i = n - 1
-    order = np.random.permutation(n)
-    while True:
-        yield order[i]
-        i += 1
-        if i >= n:
-            np.random.seed()
-            order = np.random.permutation(n)
-            i = 0
-
-class InfiniteSamplerWrapper(torch.utils.data.sampler.Sampler):
-    def __init__(self, num_samples):
-        self.num_samples = num_samples
-
-    def __iter__(self):
-        return iter(InfiniteSampler(self.num_samples))
-
-    def __len__(self):
-        return 2 ** 31

spaces/Anar0140/4.RealTime-MediaPipe-AI-From-Video-On-Any-Device/README.md

@@ -1,14 +0,0 @@
----
-title: 4.RealTime MediaPipe AI From Video On Any Device
-emoji: 👁💻👁
-colorFrom: blue
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.17.0
-app_file: app.py
-pinned: false
-license: mit
-duplicated_from: AI-ZTH-03-23/4.RealTime-MediaPipe-AI-From-Video-On-Any-Device
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/docs/source/en/api/pipelines/score_sde_ve.md

@@ -1,35 +0,0 @@
-<!--Copyright 2023 The HuggingFace Team. All rights reserved.
-
-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.
--->
-
-# Score SDE VE
-
-[Score-Based Generative Modeling through Stochastic Differential Equations](https://huggingface.co/papers/2011.13456) (Score SDE) is by Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon and Ben Poole. This pipeline implements the variance expanding (VE) variant of the stochastic differential equation method.
-
-The abstract from the paper is:
-
-*Creating noise from data is easy; creating data from noise is generative modeling. We present a stochastic differential equation (SDE) that smoothly transforms a complex data distribution to a known prior distribution by slowly injecting noise, and a corresponding reverse-time SDE that transforms the prior distribution back into the data distribution by slowly removing the noise. Crucially, the reverse-time SDE depends only on the time-dependent gradient field (\aka, score) of the perturbed data distribution. By leveraging advances in score-based generative modeling, we can accurately estimate these scores with neural networks, and use numerical SDE solvers to generate samples. We show that this framework encapsulates previous approaches in score-based generative modeling and diffusion probabilistic modeling, allowing for new sampling procedures and new modeling capabilities. In particular, we introduce a predictor-corrector framework to correct errors in the evolution of the discretized reverse-time SDE. We also derive an equivalent neural ODE that samples from the same distribution as the SDE, but additionally enables exact likelihood computation, and improved sampling efficiency. In addition, we provide a new way to solve inverse problems with score-based models, as demonstrated with experiments on class-conditional generation, image inpainting, and colorization. Combined with multiple architectural improvements, we achieve record-breaking performance for unconditional image generation on CIFAR-10 with an Inception score of 9.89 and FID of 2.20, a competitive likelihood of 2.99 bits/dim, and demonstrate high fidelity generation of 1024 x 1024 images for the first time from a score-based generative model.*
-
-The original codebase can be found at [yang-song/score_sde_pytorch](https://github.com/yang-song/score_sde_pytorch).
-
-<Tip>
-
-Make sure to check out the Schedulers [guide](/using-diffusers/schedulers) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](/using-diffusers/loading#reuse-components-across-pipelines) section to learn how to efficiently load the same components into multiple pipelines.
-
-</Tip>
-
-## ScoreSdeVePipeline
-[[autodoc]] ScoreSdeVePipeline
-	- all
-	- __call__
-
-## ImagePipelineOutput
-[[autodoc]] pipelines.ImagePipelineOutput

spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_image_variation.py

@@ -1,414 +0,0 @@
-# Copyright 2023 The HuggingFace Team. All rights reserved.
-#
-# 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.
-
-import inspect
-import warnings
-from typing import Callable, List, Optional, Union
-
-import PIL
-import torch
-from packaging import version
-from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
-
-from ...configuration_utils import FrozenDict
-from ...image_processor import VaeImageProcessor
-from ...models import AutoencoderKL, UNet2DConditionModel
-from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import deprecate, logging, randn_tensor
-from ..pipeline_utils import DiffusionPipeline
-from . import StableDiffusionPipelineOutput
-from .safety_checker import StableDiffusionSafetyChecker
-
-
-logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
-
-
-class StableDiffusionImageVariationPipeline(DiffusionPipeline):
-    r"""
-    Pipeline to generate image variations from an input image using Stable Diffusion.
-
-    This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods
-    implemented for all pipelines (downloading, saving, running on a particular device, etc.).
-
-    Args:
-        vae ([`AutoencoderKL`]):
-            Variational Auto-Encoder (VAE) model to encode and decode images to and from latent representations.
-        image_encoder ([`~transformers.CLIPVisionModelWithProjection`]):
-            Frozen CLIP image-encoder ([clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14)).
-        text_encoder ([`~transformers.CLIPTextModel`]):
-            Frozen text-encoder ([clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14)).
-        tokenizer ([`~transformers.CLIPTokenizer`]):
-            A `CLIPTokenizer` to tokenize text.
-        unet ([`UNet2DConditionModel`]):
-            A `UNet2DConditionModel` to denoise the encoded image latents.
-        scheduler ([`SchedulerMixin`]):
-            A scheduler to be used in combination with `unet` to denoise the encoded image latents. Can be one of
-            [`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
-        safety_checker ([`StableDiffusionSafetyChecker`]):
-            Classification module that estimates whether generated images could be considered offensive or harmful.
-            Please refer to the [model card](https://huggingface.co/runwayml/stable-diffusion-v1-5) for more details
-            about a model's potential harms.
-        feature_extractor ([`~transformers.CLIPImageProcessor`]):
-            A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
-    """
-    # TODO: feature_extractor is required to encode images (if they are in PIL format),
-    # we should give a descriptive message if the pipeline doesn't have one.
-    _optional_components = ["safety_checker"]
-
-    def __init__(
-        self,
-        vae: AutoencoderKL,
-        image_encoder: CLIPVisionModelWithProjection,
-        unet: UNet2DConditionModel,
-        scheduler: KarrasDiffusionSchedulers,
-        safety_checker: StableDiffusionSafetyChecker,
-        feature_extractor: CLIPImageProcessor,
-        requires_safety_checker: bool = True,
-    ):
-        super().__init__()
-
-        if safety_checker is None and requires_safety_checker:
-            logger.warn(
-                f"You have disabled the safety checker for {self.__class__} by passing `safety_checker=None`. Ensure"
-                " that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered"
-                " results in services or applications open to the public. Both the diffusers team and Hugging Face"
-                " strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling"
-                " it only for use-cases that involve analyzing network behavior or auditing its results. For more"
-                " information, please have a look at https://github.com/huggingface/diffusers/pull/254 ."
-            )
-
-        if safety_checker is not None and feature_extractor is None:
-            raise ValueError(
-                "Make sure to define a feature extractor when loading {self.__class__} if you want to use the safety"
-                " checker. If you do not want to use the safety checker, you can pass `'safety_checker=None'` instead."
-            )
-
-        is_unet_version_less_0_9_0 = hasattr(unet.config, "_diffusers_version") and version.parse(
-            version.parse(unet.config._diffusers_version).base_version
-        ) < version.parse("0.9.0.dev0")
-        is_unet_sample_size_less_64 = hasattr(unet.config, "sample_size") and unet.config.sample_size < 64
-        if is_unet_version_less_0_9_0 and is_unet_sample_size_less_64:
-            deprecation_message = (
-                "The configuration file of the unet has set the default `sample_size` to smaller than"
-                " 64 which seems highly unlikely .If you're checkpoint is a fine-tuned version of any of the"
-                " following: \n- CompVis/stable-diffusion-v1-4 \n- CompVis/stable-diffusion-v1-3 \n-"
-                " CompVis/stable-diffusion-v1-2 \n- CompVis/stable-diffusion-v1-1 \n- runwayml/stable-diffusion-v1-5"
-                " \n- runwayml/stable-diffusion-inpainting \n you should change 'sample_size' to 64 in the"
-                " configuration file. Please make sure to update the config accordingly as leaving `sample_size=32`"
-                " in the config might lead to incorrect results in future versions. If you have downloaded this"
-                " checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for"
-                " the `unet/config.json` file"
-            )
-            deprecate("sample_size<64", "1.0.0", deprecation_message, standard_warn=False)
-            new_config = dict(unet.config)
-            new_config["sample_size"] = 64
-            unet._internal_dict = FrozenDict(new_config)
-
-        self.register_modules(
-            vae=vae,
-            image_encoder=image_encoder,
-            unet=unet,
-            scheduler=scheduler,
-            safety_checker=safety_checker,
-            feature_extractor=feature_extractor,
-        )
-        self.vae_scale_factor = 2 ** (len(self.vae.config.block_out_channels) - 1)
-        self.image_processor = VaeImageProcessor(vae_scale_factor=self.vae_scale_factor)
-        self.register_to_config(requires_safety_checker=requires_safety_checker)
-
-    def _encode_image(self, image, device, num_images_per_prompt, do_classifier_free_guidance):
-        dtype = next(self.image_encoder.parameters()).dtype
-
-        if not isinstance(image, torch.Tensor):
-            image = self.feature_extractor(images=image, return_tensors="pt").pixel_values
-
-        image = image.to(device=device, dtype=dtype)
-        image_embeddings = self.image_encoder(image).image_embeds
-        image_embeddings = image_embeddings.unsqueeze(1)
-
-        # duplicate image embeddings for each generation per prompt, using mps friendly method
-        bs_embed, seq_len, _ = image_embeddings.shape
-        image_embeddings = image_embeddings.repeat(1, num_images_per_prompt, 1)
-        image_embeddings = image_embeddings.view(bs_embed * num_images_per_prompt, seq_len, -1)
-
-        if do_classifier_free_guidance:
-            negative_prompt_embeds = torch.zeros_like(image_embeddings)
-
-            # For classifier free guidance, we need to do two forward passes.
-            # Here we concatenate the unconditional and text embeddings into a single batch
-            # to avoid doing two forward passes
-            image_embeddings = torch.cat([negative_prompt_embeds, image_embeddings])
-
-        return image_embeddings
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.run_safety_checker
-    def run_safety_checker(self, image, device, dtype):
-        if self.safety_checker is None:
-            has_nsfw_concept = None
-        else:
-            if torch.is_tensor(image):
-                feature_extractor_input = self.image_processor.postprocess(image, output_type="pil")
-            else:
-                feature_extractor_input = self.image_processor.numpy_to_pil(image)
-            safety_checker_input = self.feature_extractor(feature_extractor_input, return_tensors="pt").to(device)
-            image, has_nsfw_concept = self.safety_checker(
-                images=image, clip_input=safety_checker_input.pixel_values.to(dtype)
-            )
-        return image, has_nsfw_concept
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.decode_latents
-    def decode_latents(self, latents):
-        warnings.warn(
-            "The decode_latents method is deprecated and will be removed in a future version. Please"
-            " use VaeImageProcessor instead",
-            FutureWarning,
-        )
-        latents = 1 / self.vae.config.scaling_factor * latents
-        image = self.vae.decode(latents, return_dict=False)[0]
-        image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
-        image = image.cpu().permute(0, 2, 3, 1).float().numpy()
-        return image
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs
-    def prepare_extra_step_kwargs(self, generator, eta):
-        # prepare extra kwargs for the scheduler step, since not all schedulers have the same signature
-        # eta (η) is only used with the DDIMScheduler, it will be ignored for other schedulers.
-        # eta corresponds to η in DDIM paper: https://arxiv.org/abs/2010.02502
-        # and should be between [0, 1]
-
-        accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
-        extra_step_kwargs = {}
-        if accepts_eta:
-            extra_step_kwargs["eta"] = eta
-
-        # check if the scheduler accepts generator
-        accepts_generator = "generator" in set(inspect.signature(self.scheduler.step).parameters.keys())
-        if accepts_generator:
-            extra_step_kwargs["generator"] = generator
-        return extra_step_kwargs
-
-    def check_inputs(self, image, height, width, callback_steps):
-        if (
-            not isinstance(image, torch.Tensor)
-            and not isinstance(image, PIL.Image.Image)
-            and not isinstance(image, list)
-        ):
-            raise ValueError(
-                "`image` has to be of type `torch.FloatTensor` or `PIL.Image.Image` or `List[PIL.Image.Image]` but is"
-                f" {type(image)}"
-            )
-
-        if height % 8 != 0 or width % 8 != 0:
-            raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
-
-        if (callback_steps is None) or (
-            callback_steps is not None and (not isinstance(callback_steps, int) or callback_steps <= 0)
-        ):
-            raise ValueError(
-                f"`callback_steps` has to be a positive integer but is {callback_steps} of type"
-                f" {type(callback_steps)}."
-            )
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_latents
-    def prepare_latents(self, batch_size, num_channels_latents, height, width, dtype, device, generator, latents=None):
-        shape = (batch_size, num_channels_latents, height // self.vae_scale_factor, width // self.vae_scale_factor)
-        if isinstance(generator, list) and len(generator) != batch_size:
-            raise ValueError(
-                f"You have passed a list of generators of length {len(generator)}, but requested an effective batch"
-                f" size of {batch_size}. Make sure the batch size matches the length of the generators."
-            )
-
-        if latents is None:
-            latents = randn_tensor(shape, generator=generator, device=device, dtype=dtype)
-        else:
-            latents = latents.to(device)
-
-        # scale the initial noise by the standard deviation required by the scheduler
-        latents = latents * self.scheduler.init_noise_sigma
-        return latents
-
-    @torch.no_grad()
-    def __call__(
-        self,
-        image: Union[PIL.Image.Image, List[PIL.Image.Image], torch.FloatTensor],
-        height: Optional[int] = None,
-        width: Optional[int] = None,
-        num_inference_steps: int = 50,
-        guidance_scale: float = 7.5,
-        num_images_per_prompt: Optional[int] = 1,
-        eta: float = 0.0,
-        generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
-        latents: Optional[torch.FloatTensor] = None,
-        output_type: Optional[str] = "pil",
-        return_dict: bool = True,
-        callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
-        callback_steps: int = 1,
-    ):
-        r"""
-        The call function to the pipeline for generation.
-
-        Args:
-            image (`PIL.Image.Image` or `List[PIL.Image.Image]` or `torch.FloatTensor`):
-                Image or images to guide image generation. If you provide a tensor, it needs to be compatible with
-                [`CLIPImageProcessor`](https://huggingface.co/lambdalabs/sd-image-variations-diffusers/blob/main/feature_extractor/preprocessor_config.json).
-            height (`int`, *optional*, defaults to `self.unet.config.sample_size * self.vae_scale_factor`):
-                The height in pixels of the generated image.
-            width (`int`, *optional*, defaults to `self.unet.config.sample_size * self.vae_scale_factor`):
-                The width in pixels of the generated image.
-            num_inference_steps (`int`, *optional*, defaults to 50):
-                The number of denoising steps. More denoising steps usually lead to a higher quality image at the
-                expense of slower inference. This parameter is modulated by `strength`.
-            guidance_scale (`float`, *optional*, defaults to 7.5):
-                A higher guidance scale value encourages the model to generate images closely linked to the text
-                `prompt` at the expense of lower image quality. Guidance scale is enabled when `guidance_scale > 1`.
-            num_images_per_prompt (`int`, *optional*, defaults to 1):
-                The number of images to generate per prompt.
-            eta (`float`, *optional*, defaults to 0.0):
-                Corresponds to parameter eta (η) from the [DDIM](https://arxiv.org/abs/2010.02502) paper. Only applies
-                to the [`~schedulers.DDIMScheduler`], and is ignored in other schedulers.
-            generator (`torch.Generator` or `List[torch.Generator]`, *optional*):
-                A [`torch.Generator`](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make
-                generation deterministic.
-            latents (`torch.FloatTensor`, *optional*):
-                Pre-generated noisy latents sampled from a Gaussian distribution, to be used as inputs for image
-                generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor is generated by sampling using the supplied random `generator`.
-            output_type (`str`, *optional*, defaults to `"pil"`):
-                The output format of the generated image. Choose between `PIL.Image` or `np.array`.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] instead of a
-                plain tuple.
-            callback (`Callable`, *optional*):
-                A function that calls every `callback_steps` steps during inference. The function is called with the
-                following arguments: `callback(step: int, timestep: int, latents: torch.FloatTensor)`.
-            callback_steps (`int`, *optional*, defaults to 1):
-                The frequency at which the `callback` function is called. If not specified, the callback is called at
-                every step.
-
-        Returns:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] or `tuple`:
-                If `return_dict` is `True`, [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] is returned,
-                otherwise a `tuple` is returned where the first element is a list with the generated images and the
-                second element is a list of `bool`s indicating whether the corresponding generated image contains
-                "not-safe-for-work" (nsfw) content.
-
-        Examples:
-
-        ```py
-        from diffusers import StableDiffusionImageVariationPipeline
-        from PIL import Image
-        from io import BytesIO
-        import requests
-
-        pipe = StableDiffusionImageVariationPipeline.from_pretrained(
-            "lambdalabs/sd-image-variations-diffusers", revision="v2.0"
-        )
-        pipe = pipe.to("cuda")
-
-        url = "https://lh3.googleusercontent.com/y-iFOHfLTwkuQSUegpwDdgKmOjRSTvPxat63dQLB25xkTs4lhIbRUFeNBWZzYf370g=s1200"
-
-        response = requests.get(url)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-
-        out = pipe(image, num_images_per_prompt=3, guidance_scale=15)
-        out["images"][0].save("result.jpg")
-        ```
-        """
-        # 0. Default height and width to unet
-        height = height or self.unet.config.sample_size * self.vae_scale_factor
-        width = width or self.unet.config.sample_size * self.vae_scale_factor
-
-        # 1. Check inputs. Raise error if not correct
-        self.check_inputs(image, height, width, callback_steps)
-
-        # 2. Define call parameters
-        if isinstance(image, PIL.Image.Image):
-            batch_size = 1
-        elif isinstance(image, list):
-            batch_size = len(image)
-        else:
-            batch_size = image.shape[0]
-        device = self._execution_device
-        # here `guidance_scale` is defined analog to the guidance weight `w` of equation (2)
-        # of the Imagen paper: https://arxiv.org/pdf/2205.11487.pdf . `guidance_scale = 1`
-        # corresponds to doing no classifier free guidance.
-        do_classifier_free_guidance = guidance_scale > 1.0
-
-        # 3. Encode input image
-        image_embeddings = self._encode_image(image, device, num_images_per_prompt, do_classifier_free_guidance)
-
-        # 4. Prepare timesteps
-        self.scheduler.set_timesteps(num_inference_steps, device=device)
-        timesteps = self.scheduler.timesteps
-
-        # 5. Prepare latent variables
-        num_channels_latents = self.unet.config.in_channels
-        latents = self.prepare_latents(
-            batch_size * num_images_per_prompt,
-            num_channels_latents,
-            height,
-            width,
-            image_embeddings.dtype,
-            device,
-            generator,
-            latents,
-        )
-
-        # 6. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
-        extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
-
-        # 7. Denoising loop
-        num_warmup_steps = len(timesteps) - num_inference_steps * self.scheduler.order
-        with self.progress_bar(total=num_inference_steps) as progress_bar:
-            for i, t in enumerate(timesteps):
-                # expand the latents if we are doing classifier free guidance
-                latent_model_input = torch.cat([latents] * 2) if do_classifier_free_guidance else latents
-                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
-
-                # predict the noise residual
-                noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=image_embeddings).sample
-
-                # perform guidance
-                if do_classifier_free_guidance:
-                    noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
-                    noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
-
-                # compute the previous noisy sample x_t -> x_t-1
-                latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
-
-                # call the callback, if provided
-                if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
-                    progress_bar.update()
-                    if callback is not None and i % callback_steps == 0:
-                        callback(i, t, latents)
-
-        if not output_type == "latent":
-            image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]
-            image, has_nsfw_concept = self.run_safety_checker(image, device, image_embeddings.dtype)
-        else:
-            image = latents
-            has_nsfw_concept = None
-
-        if has_nsfw_concept is None:
-            do_denormalize = [True] * image.shape[0]
-        else:
-            do_denormalize = [not has_nsfw for has_nsfw in has_nsfw_concept]
-
-        image = self.image_processor.postprocess(image, output_type=output_type, do_denormalize=do_denormalize)
-
-        if not return_dict:
-            return (image, has_nsfw_concept)
-
-        return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)

spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/pascal_voc12_aug.py

@@ -1,9 +0,0 @@
-_base_ = './pascal_voc12.py'
-# dataset settings
-data = dict(
-    train=dict(
-        ann_dir=['SegmentationClass', 'SegmentationClassAug'],
-        split=[
-            'ImageSets/Segmentation/train.txt',
-            'ImageSets/Segmentation/aug.txt'
-        ]))

spaces/AnnasBlackHat/Image-Downloader/app.py

@@ -1,70 +0,0 @@
-from cProfile import label
-from distutils.log import debug
-from random import choices
-import gradio as gr
-import re
-import requests
-import os
-import shutil
-import gofile
-import json
-import time
-
-
-try: os.mkdir('images')
-except: print('images dir might already exist...')
-
-
-def download_local(url):
-    resp = requests.get(url, allow_redirects=True)    
-    filename, file_extension = os.path.splitext(url)
-    filename = os.path.basename(url)
-    if file_extension == '':
-        filename = filename+'.jpg'
-        
-    filename = 'images/{}_{}'.format(int(time.time()), filename)
-    with open(filename, 'wb') as handler:
-        handler.write(resp.content)
-    return filename
-
-
-def download(text, is_upload):
-    pattern = '(?:(?:https?|ftp):\/\/)?[\w/\-?=%.]+\.[\w/\-&?=%.]+'
-    print(text)
-    print('upload?: ',is_upload)
-
-    urls = re.findall(pattern, text)
-    print(f'{len(urls)} urls')
-
-    if len(urls) == 0 :
-        return 'No Url Found'
-
-    err_msgs = []
-
-    #downloading all files 
-    print('downloading...')    
-    for i, url in enumerate(urls):
-        try:
-            download_local(url)
-            if i % int(len(urls) * 0.1) == 0:
-                print(f'>>> {i} files downloaded')
-        except Exception as e :
-            err_msgs.append(f'error downloading: {url} - {str(e)}')
-
-    #zipping 
-    print('zipping images...')
-    shutil.make_archive('images', 'zip', 'images')    
-    
-    result =  '{} link found, {}'.format(len(urls), " ,\n ".join(err_msgs))
-
-    if is_upload == 'yes':
-        print('uploading...')
-        download_links = gofile.Gofile().upload(["images.zip"])
-        result += f'download link : {" ".join(download_links)}'
-
-    return "images.zip", result
-
-iface = gr.Interface(fn=download, 
-                    inputs=["text",gr.Radio(choices=['yes','no'], label='Upload to Gofile? (slow process)')], 
-                    outputs=["file", "text"])
-iface.launch(debug=True)

spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/mmcv/ops/assign_score_withk.py

@@ -1,123 +0,0 @@
-from torch.autograd import Function
-
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext(
-    '_ext', ['assign_score_withk_forward', 'assign_score_withk_backward'])
-
-
-class AssignScoreWithK(Function):
-    r"""Perform weighted sum to generate output features according to scores.
-    Modified from `PAConv <https://github.com/CVMI-Lab/PAConv/tree/main/
-    scene_seg/lib/paconv_lib/src/gpu>`_.
-
-    This is a memory-efficient CUDA implementation of assign_scores operation,
-    which first transform all point features with weight bank, then assemble
-    neighbor features with ``knn_idx`` and perform weighted sum of ``scores``.
-
-    See the `paper <https://arxiv.org/pdf/2103.14635.pdf>`_ appendix Sec. D for
-        more detailed descriptions.
-
-    Note:
-        This implementation assumes using ``neighbor`` kernel input, which is
-            (point_features - center_features, point_features).
-        See https://github.com/CVMI-Lab/PAConv/blob/main/scene_seg/model/
-        pointnet2/paconv.py#L128 for more details.
-    """
-
-    @staticmethod
-    def forward(ctx,
-                scores,
-                point_features,
-                center_features,
-                knn_idx,
-                aggregate='sum'):
-        """
-        Args:
-            scores (torch.Tensor): (B, npoint, K, M), predicted scores to
-                aggregate weight matrices in the weight bank.
-                ``npoint`` is the number of sampled centers.
-                ``K`` is the number of queried neighbors.
-                ``M`` is the number of weight matrices in the weight bank.
-            point_features (torch.Tensor): (B, N, M, out_dim)
-                Pre-computed point features to be aggregated.
-            center_features (torch.Tensor): (B, N, M, out_dim)
-                Pre-computed center features to be aggregated.
-            knn_idx (torch.Tensor): (B, npoint, K), index of sampled kNN.
-                We assume the first idx in each row is the idx of the center.
-            aggregate (str, optional): Aggregation method.
-                Can be 'sum', 'avg' or 'max'. Defaults: 'sum'.
-
-        Returns:
-            torch.Tensor: (B, out_dim, npoint, K), the aggregated features.
-        """
-        agg = {'sum': 0, 'avg': 1, 'max': 2}
-
-        B, N, M, out_dim = point_features.size()
-        _, npoint, K, _ = scores.size()
-
-        output = point_features.new_zeros((B, out_dim, npoint, K))
-        ext_module.assign_score_withk_forward(
-            point_features.contiguous(),
-            center_features.contiguous(),
-            scores.contiguous(),
-            knn_idx.contiguous(),
-            output,
-            B=B,
-            N0=N,
-            N1=npoint,
-            M=M,
-            K=K,
-            O=out_dim,
-            aggregate=agg[aggregate])
-
-        ctx.save_for_backward(output, point_features, center_features, scores,
-                              knn_idx)
-        ctx.agg = agg[aggregate]
-
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_out):
-        """
-        Args:
-            grad_out (torch.Tensor): (B, out_dim, npoint, K)
-
-        Returns:
-            grad_scores (torch.Tensor): (B, npoint, K, M)
-            grad_point_features (torch.Tensor): (B, N, M, out_dim)
-            grad_center_features (torch.Tensor): (B, N, M, out_dim)
-        """
-        _, point_features, center_features, scores, knn_idx = ctx.saved_tensors
-
-        agg = ctx.agg
-
-        B, N, M, out_dim = point_features.size()
-        _, npoint, K, _ = scores.size()
-
-        grad_point_features = point_features.new_zeros(point_features.shape)
-        grad_center_features = center_features.new_zeros(center_features.shape)
-        grad_scores = scores.new_zeros(scores.shape)
-
-        ext_module.assign_score_withk_backward(
-            grad_out.contiguous(),
-            point_features.contiguous(),
-            center_features.contiguous(),
-            scores.contiguous(),
-            knn_idx.contiguous(),
-            grad_point_features,
-            grad_center_features,
-            grad_scores,
-            B=B,
-            N0=N,
-            N1=npoint,
-            M=M,
-            K=K,
-            O=out_dim,
-            aggregate=agg)
-
-        return grad_scores, grad_point_features, \
-            grad_center_features, None, None
-
-
-assign_score_withk = AssignScoreWithK.apply

spaces/Apex-X/ROOPOK/roop/ui.py

@@ -1,285 +0,0 @@
-import os
-import sys
-import webbrowser
-import customtkinter as ctk
-from tkinterdnd2 import TkinterDnD, DND_ALL
-from typing import Any, Callable, Tuple, Optional
-import cv2
-from PIL import Image, ImageOps
-
-import roop.globals
-import roop.metadata
-from roop.face_analyser import get_one_face
-from roop.capturer import get_video_frame, get_video_frame_total
-from roop.face_reference import get_face_reference, set_face_reference, clear_face_reference
-from roop.predictor import predict_frame, clear_predictor
-from roop.processors.frame.core import get_frame_processors_modules
-from roop.utilities import is_image, is_video, resolve_relative_path
-
-ROOT = None
-ROOT_HEIGHT = 700
-ROOT_WIDTH = 600
-
-PREVIEW = None
-PREVIEW_MAX_HEIGHT = 700
-PREVIEW_MAX_WIDTH = 1200
-
-RECENT_DIRECTORY_SOURCE = None
-RECENT_DIRECTORY_TARGET = None
-RECENT_DIRECTORY_OUTPUT = None
-
-preview_label = None
-preview_slider = None
-source_label = None
-target_label = None
-status_label = None
-
-
-# todo: remove by native support -> https://github.com/TomSchimansky/CustomTkinter/issues/934
-class CTk(ctk.CTk, TkinterDnD.DnDWrapper):
-    def __init__(self, *args: Any, **kwargs: Any) -> None:
-        super().__init__(*args, **kwargs)
-        self.TkdndVersion = TkinterDnD._require(self)
-
-
-def init(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global ROOT, PREVIEW
-
-    ROOT = create_root(start, destroy)
-    PREVIEW = create_preview(ROOT)
-
-    return ROOT
-
-
-def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global source_label, target_label, status_label
-
-    ctk.deactivate_automatic_dpi_awareness()
-    ctk.set_appearance_mode('system')
-    ctk.set_default_color_theme(resolve_relative_path('ui.json'))
-
-    root = CTk()
-    root.minsize(ROOT_WIDTH, ROOT_HEIGHT)
-    root.title(f'{roop.metadata.name} {roop.metadata.version}')
-    root.configure()
-    root.protocol('WM_DELETE_WINDOW', lambda: destroy())
-
-    source_label = ctk.CTkLabel(root, text=None, fg_color=ctk.ThemeManager.theme.get('RoopDropArea').get('fg_color'))
-    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)
-    source_label.drop_target_register(DND_ALL)
-    source_label.dnd_bind('<<Drop>>', lambda event: select_source_path(event.data))
-    if roop.globals.source_path:
-        select_source_path(roop.globals.source_path)
-
-    target_label = ctk.CTkLabel(root, text=None, fg_color=ctk.ThemeManager.theme.get('RoopDropArea').get('fg_color'))
-    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)
-    target_label.drop_target_register(DND_ALL)
-    target_label.dnd_bind('<<Drop>>', lambda event: select_target_path(event.data))
-    if roop.globals.target_path:
-        select_target_path(roop.globals.target_path)
-
-    source_button = ctk.CTkButton(root, text='Select a face', cursor='hand2', command=lambda: select_source_path())
-    source_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)
-
-    target_button = ctk.CTkButton(root, text='Select a target', cursor='hand2', command=lambda: select_target_path())
-    target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)
-
-    keep_fps_value = ctk.BooleanVar(value=roop.globals.keep_fps)
-    keep_fps_checkbox = ctk.CTkSwitch(root, text='Keep target fps', variable=keep_fps_value, cursor='hand2', command=lambda: setattr(roop.globals, 'keep_fps', not roop.globals.keep_fps))
-    keep_fps_checkbox.place(relx=0.1, rely=0.6)
-
-    keep_frames_value = ctk.BooleanVar(value=roop.globals.keep_frames)
-    keep_frames_switch = ctk.CTkSwitch(root, text='Keep temporary frames', variable=keep_frames_value, cursor='hand2', command=lambda: setattr(roop.globals, 'keep_frames', keep_frames_value.get()))
-    keep_frames_switch.place(relx=0.1, rely=0.65)
-
-    skip_audio_value = ctk.BooleanVar(value=roop.globals.skip_audio)
-    skip_audio_switch = ctk.CTkSwitch(root, text='Skip target audio', variable=skip_audio_value, cursor='hand2', command=lambda: setattr(roop.globals, 'skip_audio', skip_audio_value.get()))
-    skip_audio_switch.place(relx=0.6, rely=0.6)
-
-    many_faces_value = ctk.BooleanVar(value=roop.globals.many_faces)
-    many_faces_switch = ctk.CTkSwitch(root, text='Many faces', variable=many_faces_value, cursor='hand2', command=lambda: setattr(roop.globals, 'many_faces', many_faces_value.get()))
-    many_faces_switch.place(relx=0.6, rely=0.65)
-
-    start_button = ctk.CTkButton(root, text='Start', cursor='hand2', command=lambda: select_output_path(start))
-    start_button.place(relx=0.15, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    stop_button = ctk.CTkButton(root, text='Destroy', cursor='hand2', command=lambda: destroy())
-    stop_button.place(relx=0.4, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    preview_button = ctk.CTkButton(root, text='Preview', cursor='hand2', command=lambda: toggle_preview())
-    preview_button.place(relx=0.65, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    status_label = ctk.CTkLabel(root, text=None, justify='center')
-    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)
-
-    donate_label = ctk.CTkLabel(root, text='^_^ Donate to project ^_^', justify='center', cursor='hand2')
-    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
-    donate_label.configure(text_color=ctk.ThemeManager.theme.get('RoopDonate').get('text_color'))
-    donate_label.bind('<Button>', lambda event: webbrowser.open('https://github.com/sponsors/s0md3v'))
-
-    return root
-
-
-def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
-    global preview_label, preview_slider
-
-    preview = ctk.CTkToplevel(parent)
-    preview.withdraw()
-    preview.configure()
-    preview.protocol('WM_DELETE_WINDOW', lambda: toggle_preview())
-    preview.resizable(width=False, height=False)
-
-    preview_label = ctk.CTkLabel(preview, text=None)
-    preview_label.pack(fill='both', expand=True)
-
-    preview_slider = ctk.CTkSlider(preview, from_=0, to=0, command=lambda frame_value: update_preview(frame_value))
-
-    preview.bind('<Up>', lambda event: update_face_reference(1))
-    preview.bind('<Down>', lambda event: update_face_reference(-1))
-    return preview
-
-
-def update_status(text: str) -> None:
-    status_label.configure(text=text)
-    ROOT.update()
-
-
-def select_source_path(source_path: Optional[str] = None) -> None:
-    global RECENT_DIRECTORY_SOURCE
-
-    if PREVIEW:
-        PREVIEW.withdraw()
-    if source_path is None:
-        source_path = ctk.filedialog.askopenfilename(title='select an source image', initialdir=RECENT_DIRECTORY_SOURCE)
-    if is_image(source_path):
-        roop.globals.source_path = source_path
-        RECENT_DIRECTORY_SOURCE = os.path.dirname(roop.globals.source_path)
-        image = render_image_preview(roop.globals.source_path, (200, 200))
-        source_label.configure(image=image)
-    else:
-        roop.globals.source_path = None
-        source_label.configure(image=None)
-
-
-def select_target_path(target_path: Optional[str] = None) -> None:
-    global RECENT_DIRECTORY_TARGET
-
-    if PREVIEW:
-        PREVIEW.withdraw()
-    clear_face_reference()
-    if target_path is None:
-        target_path = ctk.filedialog.askopenfilename(title='select an target image or video', initialdir=RECENT_DIRECTORY_TARGET)
-    if is_image(target_path):
-        roop.globals.target_path = target_path
-        RECENT_DIRECTORY_TARGET = os.path.dirname(roop.globals.target_path)
-        image = render_image_preview(roop.globals.target_path, (200, 200))
-        target_label.configure(image=image)
-    elif is_video(target_path):
-        roop.globals.target_path = target_path
-        RECENT_DIRECTORY_TARGET = os.path.dirname(roop.globals.target_path)
-        video_frame = render_video_preview(target_path, (200, 200))
-        target_label.configure(image=video_frame)
-    else:
-        roop.globals.target_path = None
-        target_label.configure(image=None)
-
-
-def select_output_path(start: Callable[[], None]) -> None:
-    global RECENT_DIRECTORY_OUTPUT
-
-    if is_image(roop.globals.target_path):
-        output_path = ctk.filedialog.asksaveasfilename(title='save image output file', defaultextension='.png', initialfile='output.png', initialdir=RECENT_DIRECTORY_OUTPUT)
-    elif is_video(roop.globals.target_path):
-        output_path = ctk.filedialog.asksaveasfilename(title='save video output file', defaultextension='.mp4', initialfile='output.mp4', initialdir=RECENT_DIRECTORY_OUTPUT)
-    else:
-        output_path = None
-    if output_path:
-        roop.globals.output_path = output_path
-        RECENT_DIRECTORY_OUTPUT = os.path.dirname(roop.globals.output_path)
-        start()
-
-
-def render_image_preview(image_path: str, size: Tuple[int, int]) -> ctk.CTkImage:
-    image = Image.open(image_path)
-    if size:
-        image = ImageOps.fit(image, size, Image.LANCZOS)
-    return ctk.CTkImage(image, size=image.size)
-
-
-def render_video_preview(video_path: str, size: Tuple[int, int], frame_number: int = 0) -> ctk.CTkImage:
-    capture = cv2.VideoCapture(video_path)
-    if frame_number:
-        capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
-    has_frame, frame = capture.read()
-    if has_frame:
-        image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
-        if size:
-            image = ImageOps.fit(image, size, Image.LANCZOS)
-        return ctk.CTkImage(image, size=image.size)
-    capture.release()
-    cv2.destroyAllWindows()
-
-
-def toggle_preview() -> None:
-    if PREVIEW.state() == 'normal':
-        PREVIEW.unbind('<Right>')
-        PREVIEW.unbind('<Left>')
-        PREVIEW.withdraw()
-        clear_predictor()
-    elif roop.globals.source_path and roop.globals.target_path:
-        init_preview()
-        update_preview(roop.globals.reference_frame_number)
-        PREVIEW.deiconify()
-
-
-def init_preview() -> None:
-    PREVIEW.title('Preview [ ↕ Reference face ]')
-    if is_image(roop.globals.target_path):
-        preview_slider.pack_forget()
-    if is_video(roop.globals.target_path):
-        video_frame_total = get_video_frame_total(roop.globals.target_path)
-        if video_frame_total > 0:
-            PREVIEW.title('Preview [ ↕ Reference face ] [ ↔ Frame number ]')
-            PREVIEW.bind('<Right>', lambda event: update_frame(int(video_frame_total / 20)))
-            PREVIEW.bind('<Left>', lambda event: update_frame(int(video_frame_total / -20)))
-        preview_slider.configure(to=video_frame_total)
-        preview_slider.pack(fill='x')
-        preview_slider.set(roop.globals.reference_frame_number)
-
-
-def update_preview(frame_number: int = 0) -> None:
-    if roop.globals.source_path and roop.globals.target_path:
-        temp_frame = get_video_frame(roop.globals.target_path, frame_number)
-        if predict_frame(temp_frame):
-            sys.exit()
-        source_face = get_one_face(cv2.imread(roop.globals.source_path))
-        if not get_face_reference():
-            reference_frame = get_video_frame(roop.globals.target_path, roop.globals.reference_frame_number)
-            reference_face = get_one_face(reference_frame, roop.globals.reference_face_position)
-            set_face_reference(reference_face)
-        else:
-            reference_face = get_face_reference()
-        for frame_processor in get_frame_processors_modules(roop.globals.frame_processors):
-            temp_frame = frame_processor.process_frame(
-                source_face,
-                reference_face,
-                temp_frame
-            )
-        image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
-        image = ImageOps.contain(image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS)
-        image = ctk.CTkImage(image, size=image.size)
-        preview_label.configure(image=image)
-
-
-def update_face_reference(steps: int) -> None:
-    clear_face_reference()
-    reference_frame_number = int(preview_slider.get())
-    roop.globals.reference_face_position += steps
-    roop.globals.reference_frame_number = reference_frame_number
-    update_preview(reference_frame_number)
-
-
-def update_frame(steps: int) -> None:
-    frame_number = preview_slider.get() + steps
-    preview_slider.set(frame_number)
-    update_preview(preview_slider.get())

spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/setuptools/_distutils/command/install_headers.py

@@ -1,45 +0,0 @@
-"""distutils.command.install_headers
-
-Implements the Distutils 'install_headers' command, to install C/C++ header
-files to the Python include directory."""
-
-from distutils.core import Command
-
-
-# XXX force is never used
-class install_headers(Command):
-
-    description = "install C/C++ header files"
-
-    user_options = [
-        ('install-dir=', 'd', "directory to install header files to"),
-        ('force', 'f', "force installation (overwrite existing files)"),
-    ]
-
-    boolean_options = ['force']
-
-    def initialize_options(self):
-        self.install_dir = None
-        self.force = 0
-        self.outfiles = []
-
-    def finalize_options(self):
-        self.set_undefined_options(
-            'install', ('install_headers', 'install_dir'), ('force', 'force')
-        )
-
-    def run(self):
-        headers = self.distribution.headers
-        if not headers:
-            return
-
-        self.mkpath(self.install_dir)
-        for header in headers:
-            (out, _) = self.copy_file(header, self.install_dir)
-            self.outfiles.append(out)
-
-    def get_inputs(self):
-        return self.distribution.headers or []
-
-    def get_outputs(self):
-        return self.outfiles

spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/setuptools/_distutils/msvccompiler.py

@@ -1,695 +0,0 @@
-"""distutils.msvccompiler
-
-Contains MSVCCompiler, an implementation of the abstract CCompiler class
-for the Microsoft Visual Studio.
-"""
-
-# Written by Perry Stoll
-# hacked by Robin Becker and Thomas Heller to do a better job of
-#   finding DevStudio (through the registry)
-
-import sys
-import os
-import warnings
-from distutils.errors import (
-    DistutilsExecError,
-    DistutilsPlatformError,
-    CompileError,
-    LibError,
-    LinkError,
-)
-from distutils.ccompiler import CCompiler, gen_lib_options
-from distutils import log
-
-_can_read_reg = False
-try:
-    import winreg
-
-    _can_read_reg = True
-    hkey_mod = winreg
-
-    RegOpenKeyEx = winreg.OpenKeyEx
-    RegEnumKey = winreg.EnumKey
-    RegEnumValue = winreg.EnumValue
-    RegError = winreg.error
-
-except ImportError:
-    try:
-        import win32api
-        import win32con
-
-        _can_read_reg = True
-        hkey_mod = win32con
-
-        RegOpenKeyEx = win32api.RegOpenKeyEx
-        RegEnumKey = win32api.RegEnumKey
-        RegEnumValue = win32api.RegEnumValue
-        RegError = win32api.error
-    except ImportError:
-        log.info(
-            "Warning: Can't read registry to find the "
-            "necessary compiler setting\n"
-            "Make sure that Python modules winreg, "
-            "win32api or win32con are installed."
-        )
-        pass
-
-if _can_read_reg:
-    HKEYS = (
-        hkey_mod.HKEY_USERS,
-        hkey_mod.HKEY_CURRENT_USER,
-        hkey_mod.HKEY_LOCAL_MACHINE,
-        hkey_mod.HKEY_CLASSES_ROOT,
-    )
-
-
-warnings.warn(
-    "msvccompiler is deprecated and slated to be removed "
-    "in the future. Please discontinue use or file an issue "
-    "with pypa/distutils describing your use case.",
-    DeprecationWarning,
-)
-
-
-def read_keys(base, key):
-    """Return list of registry keys."""
-    try:
-        handle = RegOpenKeyEx(base, key)
-    except RegError:
-        return None
-    L = []
-    i = 0
-    while True:
-        try:
-            k = RegEnumKey(handle, i)
-        except RegError:
-            break
-        L.append(k)
-        i += 1
-    return L
-
-
-def read_values(base, key):
-    """Return dict of registry keys and values.
-
-    All names are converted to lowercase.
-    """
-    try:
-        handle = RegOpenKeyEx(base, key)
-    except RegError:
-        return None
-    d = {}
-    i = 0
-    while True:
-        try:
-            name, value, type = RegEnumValue(handle, i)
-        except RegError:
-            break
-        name = name.lower()
-        d[convert_mbcs(name)] = convert_mbcs(value)
-        i += 1
-    return d
-
-
-def convert_mbcs(s):
-    dec = getattr(s, "decode", None)
-    if dec is not None:
-        try:
-            s = dec("mbcs")
-        except UnicodeError:
-            pass
-    return s
-
-
-class MacroExpander:
-    def __init__(self, version):
-        self.macros = {}
-        self.load_macros(version)
-
-    def set_macro(self, macro, path, key):
-        for base in HKEYS:
-            d = read_values(base, path)
-            if d:
-                self.macros["$(%s)" % macro] = d[key]
-                break
-
-    def load_macros(self, version):
-        vsbase = r"Software\Microsoft\VisualStudio\%0.1f" % version
-        self.set_macro("VCInstallDir", vsbase + r"\Setup\VC", "productdir")
-        self.set_macro("VSInstallDir", vsbase + r"\Setup\VS", "productdir")
-        net = r"Software\Microsoft\.NETFramework"
-        self.set_macro("FrameworkDir", net, "installroot")
-        try:
-            if version > 7.0:
-                self.set_macro("FrameworkSDKDir", net, "sdkinstallrootv1.1")
-            else:
-                self.set_macro("FrameworkSDKDir", net, "sdkinstallroot")
-        except KeyError:
-            raise DistutilsPlatformError(
-                """Python was built with Visual Studio 2003;
-extensions must be built with a compiler than can generate compatible binaries.
-Visual Studio 2003 was not found on this system. If you have Cygwin installed,
-you can try compiling with MingW32, by passing "-c mingw32" to setup.py."""
-            )
-
-        p = r"Software\Microsoft\NET Framework Setup\Product"
-        for base in HKEYS:
-            try:
-                h = RegOpenKeyEx(base, p)
-            except RegError:
-                continue
-            key = RegEnumKey(h, 0)
-            d = read_values(base, r"{}\{}".format(p, key))
-            self.macros["$(FrameworkVersion)"] = d["version"]
-
-    def sub(self, s):
-        for k, v in self.macros.items():
-            s = s.replace(k, v)
-        return s
-
-
-def get_build_version():
-    """Return the version of MSVC that was used to build Python.
-
-    For Python 2.3 and up, the version number is included in
-    sys.version.  For earlier versions, assume the compiler is MSVC 6.
-    """
-    prefix = "MSC v."
-    i = sys.version.find(prefix)
-    if i == -1:
-        return 6
-    i = i + len(prefix)
-    s, rest = sys.version[i:].split(" ", 1)
-    majorVersion = int(s[:-2]) - 6
-    if majorVersion >= 13:
-        # v13 was skipped and should be v14
-        majorVersion += 1
-    minorVersion = int(s[2:3]) / 10.0
-    # I don't think paths are affected by minor version in version 6
-    if majorVersion == 6:
-        minorVersion = 0
-    if majorVersion >= 6:
-        return majorVersion + minorVersion
-    # else we don't know what version of the compiler this is
-    return None
-
-
-def get_build_architecture():
-    """Return the processor architecture.
-
-    Possible results are "Intel" or "AMD64".
-    """
-
-    prefix = " bit ("
-    i = sys.version.find(prefix)
-    if i == -1:
-        return "Intel"
-    j = sys.version.find(")", i)
-    return sys.version[i + len(prefix) : j]
-
-
-def normalize_and_reduce_paths(paths):
-    """Return a list of normalized paths with duplicates removed.
-
-    The current order of paths is maintained.
-    """
-    # Paths are normalized so things like:  /a and /a/ aren't both preserved.
-    reduced_paths = []
-    for p in paths:
-        np = os.path.normpath(p)
-        # XXX(nnorwitz): O(n**2), if reduced_paths gets long perhaps use a set.
-        if np not in reduced_paths:
-            reduced_paths.append(np)
-    return reduced_paths
-
-
-class MSVCCompiler(CCompiler):
-    """Concrete class that implements an interface to Microsoft Visual C++,
-    as defined by the CCompiler abstract class."""
-
-    compiler_type = 'msvc'
-
-    # Just set this so CCompiler's constructor doesn't barf.  We currently
-    # don't use the 'set_executables()' bureaucracy provided by CCompiler,
-    # as it really isn't necessary for this sort of single-compiler class.
-    # Would be nice to have a consistent interface with UnixCCompiler,
-    # though, so it's worth thinking about.
-    executables = {}
-
-    # Private class data (need to distinguish C from C++ source for compiler)
-    _c_extensions = ['.c']
-    _cpp_extensions = ['.cc', '.cpp', '.cxx']
-    _rc_extensions = ['.rc']
-    _mc_extensions = ['.mc']
-
-    # Needed for the filename generation methods provided by the
-    # base class, CCompiler.
-    src_extensions = _c_extensions + _cpp_extensions + _rc_extensions + _mc_extensions
-    res_extension = '.res'
-    obj_extension = '.obj'
-    static_lib_extension = '.lib'
-    shared_lib_extension = '.dll'
-    static_lib_format = shared_lib_format = '%s%s'
-    exe_extension = '.exe'
-
-    def __init__(self, verbose=0, dry_run=0, force=0):
-        super().__init__(verbose, dry_run, force)
-        self.__version = get_build_version()
-        self.__arch = get_build_architecture()
-        if self.__arch == "Intel":
-            # x86
-            if self.__version >= 7:
-                self.__root = r"Software\Microsoft\VisualStudio"
-                self.__macros = MacroExpander(self.__version)
-            else:
-                self.__root = r"Software\Microsoft\Devstudio"
-            self.__product = "Visual Studio version %s" % self.__version
-        else:
-            # Win64. Assume this was built with the platform SDK
-            self.__product = "Microsoft SDK compiler %s" % (self.__version + 6)
-
-        self.initialized = False
-
-    def initialize(self):
-        self.__paths = []
-        if (
-            "DISTUTILS_USE_SDK" in os.environ
-            and "MSSdk" in os.environ
-            and self.find_exe("cl.exe")
-        ):
-            # Assume that the SDK set up everything alright; don't try to be
-            # smarter
-            self.cc = "cl.exe"
-            self.linker = "link.exe"
-            self.lib = "lib.exe"
-            self.rc = "rc.exe"
-            self.mc = "mc.exe"
-        else:
-            self.__paths = self.get_msvc_paths("path")
-
-            if len(self.__paths) == 0:
-                raise DistutilsPlatformError(
-                    "Python was built with %s, "
-                    "and extensions need to be built with the same "
-                    "version of the compiler, but it isn't installed." % self.__product
-                )
-
-            self.cc = self.find_exe("cl.exe")
-            self.linker = self.find_exe("link.exe")
-            self.lib = self.find_exe("lib.exe")
-            self.rc = self.find_exe("rc.exe")  # resource compiler
-            self.mc = self.find_exe("mc.exe")  # message compiler
-            self.set_path_env_var('lib')
-            self.set_path_env_var('include')
-
-        # extend the MSVC path with the current path
-        try:
-            for p in os.environ['path'].split(';'):
-                self.__paths.append(p)
-        except KeyError:
-            pass
-        self.__paths = normalize_and_reduce_paths(self.__paths)
-        os.environ['path'] = ";".join(self.__paths)
-
-        self.preprocess_options = None
-        if self.__arch == "Intel":
-            self.compile_options = ['/nologo', '/O2', '/MD', '/W3', '/GX', '/DNDEBUG']
-            self.compile_options_debug = [
-                '/nologo',
-                '/Od',
-                '/MDd',
-                '/W3',
-                '/GX',
-                '/Z7',
-                '/D_DEBUG',
-            ]
-        else:
-            # Win64
-            self.compile_options = ['/nologo', '/O2', '/MD', '/W3', '/GS-', '/DNDEBUG']
-            self.compile_options_debug = [
-                '/nologo',
-                '/Od',
-                '/MDd',
-                '/W3',
-                '/GS-',
-                '/Z7',
-                '/D_DEBUG',
-            ]
-
-        self.ldflags_shared = ['/DLL', '/nologo', '/INCREMENTAL:NO']
-        if self.__version >= 7:
-            self.ldflags_shared_debug = ['/DLL', '/nologo', '/INCREMENTAL:no', '/DEBUG']
-        else:
-            self.ldflags_shared_debug = [
-                '/DLL',
-                '/nologo',
-                '/INCREMENTAL:no',
-                '/pdb:None',
-                '/DEBUG',
-            ]
-        self.ldflags_static = ['/nologo']
-
-        self.initialized = True
-
-    # -- Worker methods ------------------------------------------------
-
-    def object_filenames(self, source_filenames, strip_dir=0, output_dir=''):
-        # Copied from ccompiler.py, extended to return .res as 'object'-file
-        # for .rc input file
-        if output_dir is None:
-            output_dir = ''
-        obj_names = []
-        for src_name in source_filenames:
-            (base, ext) = os.path.splitext(src_name)
-            base = os.path.splitdrive(base)[1]  # Chop off the drive
-            base = base[os.path.isabs(base) :]  # If abs, chop off leading /
-            if ext not in self.src_extensions:
-                # Better to raise an exception instead of silently continuing
-                # and later complain about sources and targets having
-                # different lengths
-                raise CompileError("Don't know how to compile %s" % src_name)
-            if strip_dir:
-                base = os.path.basename(base)
-            if ext in self._rc_extensions:
-                obj_names.append(os.path.join(output_dir, base + self.res_extension))
-            elif ext in self._mc_extensions:
-                obj_names.append(os.path.join(output_dir, base + self.res_extension))
-            else:
-                obj_names.append(os.path.join(output_dir, base + self.obj_extension))
-        return obj_names
-
-    def compile(  # noqa: C901
-        self,
-        sources,
-        output_dir=None,
-        macros=None,
-        include_dirs=None,
-        debug=0,
-        extra_preargs=None,
-        extra_postargs=None,
-        depends=None,
-    ):
-
-        if not self.initialized:
-            self.initialize()
-        compile_info = self._setup_compile(
-            output_dir, macros, include_dirs, sources, depends, extra_postargs
-        )
-        macros, objects, extra_postargs, pp_opts, build = compile_info
-
-        compile_opts = extra_preargs or []
-        compile_opts.append('/c')
-        if debug:
-            compile_opts.extend(self.compile_options_debug)
-        else:
-            compile_opts.extend(self.compile_options)
-
-        for obj in objects:
-            try:
-                src, ext = build[obj]
-            except KeyError:
-                continue
-            if debug:
-                # pass the full pathname to MSVC in debug mode,
-                # this allows the debugger to find the source file
-                # without asking the user to browse for it
-                src = os.path.abspath(src)
-
-            if ext in self._c_extensions:
-                input_opt = "/Tc" + src
-            elif ext in self._cpp_extensions:
-                input_opt = "/Tp" + src
-            elif ext in self._rc_extensions:
-                # compile .RC to .RES file
-                input_opt = src
-                output_opt = "/fo" + obj
-                try:
-                    self.spawn([self.rc] + pp_opts + [output_opt] + [input_opt])
-                except DistutilsExecError as msg:
-                    raise CompileError(msg)
-                continue
-            elif ext in self._mc_extensions:
-                # Compile .MC to .RC file to .RES file.
-                #   * '-h dir' specifies the directory for the
-                #     generated include file
-                #   * '-r dir' specifies the target directory of the
-                #     generated RC file and the binary message resource
-                #     it includes
-                #
-                # For now (since there are no options to change this),
-                # we use the source-directory for the include file and
-                # the build directory for the RC file and message
-                # resources. This works at least for win32all.
-                h_dir = os.path.dirname(src)
-                rc_dir = os.path.dirname(obj)
-                try:
-                    # first compile .MC to .RC and .H file
-                    self.spawn([self.mc] + ['-h', h_dir, '-r', rc_dir] + [src])
-                    base, _ = os.path.splitext(os.path.basename(src))
-                    rc_file = os.path.join(rc_dir, base + '.rc')
-                    # then compile .RC to .RES file
-                    self.spawn([self.rc] + ["/fo" + obj] + [rc_file])
-
-                except DistutilsExecError as msg:
-                    raise CompileError(msg)
-                continue
-            else:
-                # how to handle this file?
-                raise CompileError(
-                    "Don't know how to compile {} to {}".format(src, obj)
-                )
-
-            output_opt = "/Fo" + obj
-            try:
-                self.spawn(
-                    [self.cc]
-                    + compile_opts
-                    + pp_opts
-                    + [input_opt, output_opt]
-                    + extra_postargs
-                )
-            except DistutilsExecError as msg:
-                raise CompileError(msg)
-
-        return objects
-
-    def create_static_lib(
-        self, objects, output_libname, output_dir=None, debug=0, target_lang=None
-    ):
-
-        if not self.initialized:
-            self.initialize()
-        (objects, output_dir) = self._fix_object_args(objects, output_dir)
-        output_filename = self.library_filename(output_libname, output_dir=output_dir)
-
-        if self._need_link(objects, output_filename):
-            lib_args = objects + ['/OUT:' + output_filename]
-            if debug:
-                pass  # XXX what goes here?
-            try:
-                self.spawn([self.lib] + lib_args)
-            except DistutilsExecError as msg:
-                raise LibError(msg)
-        else:
-            log.debug("skipping %s (up-to-date)", output_filename)
-
-    def link(  # noqa: C901
-        self,
-        target_desc,
-        objects,
-        output_filename,
-        output_dir=None,
-        libraries=None,
-        library_dirs=None,
-        runtime_library_dirs=None,
-        export_symbols=None,
-        debug=0,
-        extra_preargs=None,
-        extra_postargs=None,
-        build_temp=None,
-        target_lang=None,
-    ):
-
-        if not self.initialized:
-            self.initialize()
-        (objects, output_dir) = self._fix_object_args(objects, output_dir)
-        fixed_args = self._fix_lib_args(libraries, library_dirs, runtime_library_dirs)
-        (libraries, library_dirs, runtime_library_dirs) = fixed_args
-
-        if runtime_library_dirs:
-            self.warn(
-                "I don't know what to do with 'runtime_library_dirs': "
-                + str(runtime_library_dirs)
-            )
-
-        lib_opts = gen_lib_options(self, library_dirs, runtime_library_dirs, libraries)
-        if output_dir is not None:
-            output_filename = os.path.join(output_dir, output_filename)
-
-        if self._need_link(objects, output_filename):
-            if target_desc == CCompiler.EXECUTABLE:
-                if debug:
-                    ldflags = self.ldflags_shared_debug[1:]
-                else:
-                    ldflags = self.ldflags_shared[1:]
-            else:
-                if debug:
-                    ldflags = self.ldflags_shared_debug
-                else:
-                    ldflags = self.ldflags_shared
-
-            export_opts = []
-            for sym in export_symbols or []:
-                export_opts.append("/EXPORT:" + sym)
-
-            ld_args = (
-                ldflags + lib_opts + export_opts + objects + ['/OUT:' + output_filename]
-            )
-
-            # The MSVC linker generates .lib and .exp files, which cannot be
-            # suppressed by any linker switches. The .lib files may even be
-            # needed! Make sure they are generated in the temporary build
-            # directory. Since they have different names for debug and release
-            # builds, they can go into the same directory.
-            if export_symbols is not None:
-                (dll_name, dll_ext) = os.path.splitext(
-                    os.path.basename(output_filename)
-                )
-                implib_file = os.path.join(
-                    os.path.dirname(objects[0]), self.library_filename(dll_name)
-                )
-                ld_args.append('/IMPLIB:' + implib_file)
-
-            if extra_preargs:
-                ld_args[:0] = extra_preargs
-            if extra_postargs:
-                ld_args.extend(extra_postargs)
-
-            self.mkpath(os.path.dirname(output_filename))
-            try:
-                self.spawn([self.linker] + ld_args)
-            except DistutilsExecError as msg:
-                raise LinkError(msg)
-
-        else:
-            log.debug("skipping %s (up-to-date)", output_filename)
-
-    # -- Miscellaneous methods -----------------------------------------
-    # These are all used by the 'gen_lib_options() function, in
-    # ccompiler.py.
-
-    def library_dir_option(self, dir):
-        return "/LIBPATH:" + dir
-
-    def runtime_library_dir_option(self, dir):
-        raise DistutilsPlatformError(
-            "don't know how to set runtime library search path for MSVC++"
-        )
-
-    def library_option(self, lib):
-        return self.library_filename(lib)
-
-    def find_library_file(self, dirs, lib, debug=0):
-        # Prefer a debugging library if found (and requested), but deal
-        # with it if we don't have one.
-        if debug:
-            try_names = [lib + "_d", lib]
-        else:
-            try_names = [lib]
-        for dir in dirs:
-            for name in try_names:
-                libfile = os.path.join(dir, self.library_filename(name))
-                if os.path.exists(libfile):
-                    return libfile
-        else:
-            # Oops, didn't find it in *any* of 'dirs'
-            return None
-
-    # Helper methods for using the MSVC registry settings
-
-    def find_exe(self, exe):
-        """Return path to an MSVC executable program.
-
-        Tries to find the program in several places: first, one of the
-        MSVC program search paths from the registry; next, the directories
-        in the PATH environment variable.  If any of those work, return an
-        absolute path that is known to exist.  If none of them work, just
-        return the original program name, 'exe'.
-        """
-        for p in self.__paths:
-            fn = os.path.join(os.path.abspath(p), exe)
-            if os.path.isfile(fn):
-                return fn
-
-        # didn't find it; try existing path
-        for p in os.environ['Path'].split(';'):
-            fn = os.path.join(os.path.abspath(p), exe)
-            if os.path.isfile(fn):
-                return fn
-
-        return exe
-
-    def get_msvc_paths(self, path, platform='x86'):
-        """Get a list of devstudio directories (include, lib or path).
-
-        Return a list of strings.  The list will be empty if unable to
-        access the registry or appropriate registry keys not found.
-        """
-        if not _can_read_reg:
-            return []
-
-        path = path + " dirs"
-        if self.__version >= 7:
-            key = r"{}\{:0.1f}\VC\VC_OBJECTS_PLATFORM_INFO\Win32\Directories".format(
-                self.__root,
-                self.__version,
-            )
-        else:
-            key = (
-                r"%s\6.0\Build System\Components\Platforms"
-                r"\Win32 (%s)\Directories" % (self.__root, platform)
-            )
-
-        for base in HKEYS:
-            d = read_values(base, key)
-            if d:
-                if self.__version >= 7:
-                    return self.__macros.sub(d[path]).split(";")
-                else:
-                    return d[path].split(";")
-        # MSVC 6 seems to create the registry entries we need only when
-        # the GUI is run.
-        if self.__version == 6:
-            for base in HKEYS:
-                if read_values(base, r"%s\6.0" % self.__root) is not None:
-                    self.warn(
-                        "It seems you have Visual Studio 6 installed, "
-                        "but the expected registry settings are not present.\n"
-                        "You must at least run the Visual Studio GUI once "
-                        "so that these entries are created."
-                    )
-                    break
-        return []
-
-    def set_path_env_var(self, name):
-        """Set environment variable 'name' to an MSVC path type value.
-
-        This is equivalent to a SET command prior to execution of spawned
-        commands.
-        """
-
-        if name == "lib":
-            p = self.get_msvc_paths("library")
-        else:
-            p = self.get_msvc_paths(name)
-        if p:
-            os.environ[name] = ';'.join(p)
-
-
-if get_build_version() >= 8.0:
-    log.debug("Importing new compiler from distutils.msvc9compiler")
-    OldMSVCCompiler = MSVCCompiler
-    from distutils.msvc9compiler import MSVCCompiler
-
-    # get_build_architecture not really relevant now we support cross-compile
-    from distutils.msvc9compiler import MacroExpander  # noqa: F811

spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/setuptools/command/install_scripts.py

@@ -1,70 +0,0 @@
-from distutils import log
-import distutils.command.install_scripts as orig
-from distutils.errors import DistutilsModuleError
-import os
-import sys
-
-from pkg_resources import Distribution, PathMetadata
-from .._path import ensure_directory
-
-
-class install_scripts(orig.install_scripts):
-    """Do normal script install, plus any egg_info wrapper scripts"""
-
-    def initialize_options(self):
-        orig.install_scripts.initialize_options(self)
-        self.no_ep = False
-
-    def run(self):
-        import setuptools.command.easy_install as ei
-
-        self.run_command("egg_info")
-        if self.distribution.scripts:
-            orig.install_scripts.run(self)  # run first to set up self.outfiles
-        else:
-            self.outfiles = []
-        if self.no_ep:
-            # don't install entry point scripts into .egg file!
-            return
-
-        ei_cmd = self.get_finalized_command("egg_info")
-        dist = Distribution(
-            ei_cmd.egg_base, PathMetadata(ei_cmd.egg_base, ei_cmd.egg_info),
-            ei_cmd.egg_name, ei_cmd.egg_version,
-        )
-        bs_cmd = self.get_finalized_command('build_scripts')
-        exec_param = getattr(bs_cmd, 'executable', None)
-        try:
-            bw_cmd = self.get_finalized_command("bdist_wininst")
-            is_wininst = getattr(bw_cmd, '_is_running', False)
-        except (ImportError, DistutilsModuleError):
-            is_wininst = False
-        writer = ei.ScriptWriter
-        if is_wininst:
-            exec_param = "python.exe"
-            writer = ei.WindowsScriptWriter
-        if exec_param == sys.executable:
-            # In case the path to the Python executable contains a space, wrap
-            # it so it's not split up.
-            exec_param = [exec_param]
-        # resolve the writer to the environment
-        writer = writer.best()
-        cmd = writer.command_spec_class.best().from_param(exec_param)
-        for args in writer.get_args(dist, cmd.as_header()):
-            self.write_script(*args)
-
-    def write_script(self, script_name, contents, mode="t", *ignored):
-        """Write an executable file to the scripts directory"""
-        from setuptools.command.easy_install import chmod, current_umask
-
-        log.info("Installing %s script to %s", script_name, self.install_dir)
-        target = os.path.join(self.install_dir, script_name)
-        self.outfiles.append(target)
-
-        mask = current_umask()
-        if not self.dry_run:
-            ensure_directory(target)
-            f = open(target, "w" + mode)
-            f.write(contents)
-            f.close()
-            chmod(target, 0o777 - mask)

spaces/Avator/gradio-hugging-face/README.md

@@ -1,12 +0,0 @@
----
-title: Gradio Hugging Face
-emoji: 😻
-colorFrom: blue
-colorTo: gray
-sdk: gradio
-sdk_version: 3.0.11
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

spaces/Banbri/zcvzcv/src/app/interface/progress/progress-bar.tsx

@@ -1,57 +0,0 @@
-"use client"
-
-import { CircularProgressbar, buildStyles } from "react-circular-progressbar"
-import "react-circular-progressbar/dist/styles.css"
-
-export function ProgressBar ({
-  className,
-  progressPercentage,
-  text
-}: {
-  className?: string
-  progressPercentage?: number
-  text?: string
-}) {
-  return (
-    <div className={className}>
-      <CircularProgressbar
-        // doc: https://www.npmjs.com/package/react-circular-progressbar
-
-        value={progressPercentage || 0}
-
-        // Text to display inside progressbar. Default: ''.
-        text={text || ""}   
-
-        // Width of circular line relative to total width of component, a value from 0-100. Default: 8.
-        strokeWidth={8}
-
-        
-          // As a convenience, you can use buildStyles to configure the most common style changes:
-
-          styles={buildStyles({
-            // Rotation of path and trail, in number of turns (0-1)
-            rotation: 0,
-
-            // Whether to use rounded or flat corners on the ends - can use 'butt' or 'round'
-            strokeLinecap: 'round',
-
-            // Text size
-            textSize: '20px',
-
-            // How long animation takes to go from one percentage to another, in seconds
-            pathTransitionDuration: 0.1,
-
-            // Can specify path transition in more detail, or remove it entirely
-            // pathTransition: 'none',
-
-            // Colors
-            // pathColor: `rgba(62, 152, 199, ${percentage / 100})`,
-            textColor: '#f88',
-            trailColor: '#d6d6d6',
-            backgroundColor: '#3e98c7',
-          })}
-      
-      />
-    </div>
-  )
-}

spaces/Benson/text-generation/Examples/Autobs Simulador Indonesia Librea Descargar 4k.md

@@ -1,91 +0,0 @@
-<br />
-<h1>Simulador de autobús Indonesia librea Descargar 4K: Cómo personalizar su autobús con impresionantes diseños</h1>
- <p>¿Te encanta conducir autobuses en entornos indonesios realistas y auténticos? ¿Quieres hacer que tu autobús se vea más atractivo y único con diseños personalizados? Si respondiste sí, entonces deberías probar <strong>Bus Simulator Indonesia</strong>, un juego de simulación popular y divertido que te permite experimentar lo que le gusta ser un conductor de autobús en Indonesia. Y para hacer que tu autobús se destaque entre la multitud, también debes probar <strong>Livery</strong>, una característica que te permite cambiar la apariencia de tu autobús con varias pieles y temas. </p>
- <p>En este artículo, le mostraremos todo lo que necesita saber sobre Bus Simulator Indonesia y Livery, incluyendo cómo descargar e instalar el juego, cómo descargar y aplicar Livery, y cómo diseñar su propia Livery. También compartiremos algunos consejos y trucos para crear impresionantes diseños de librea que impresionarán a sus pasajeros y compañeros de viaje. Así que, vamos a empezar! </p>
-<h2>autobús simulador indonesia librea descargar 4k</h2><br /><p><b><b>Download</b> &#10004; <a href="https://bltlly.com/2v6JxM">https://bltlly.com/2v6JxM</a></b></p><br /><br />
- <h2>¿Qué es Bus Simulator Indonesia? </h2>
- <p>Bus Simulator Indonesia (también conocido como BUSSID) es un juego de simulación desarrollado por Maleo, un estudio de juegos de Indonesia. Fue lanzado en 2017 y desde entonces ha ganado millones de fans en todo el mundo. El juego está disponible para dispositivos Android e iOS, así como para PC a través de emulador. </p>
- <p>Como su nombre indica, Bus Simulator Indonesia le permite conducir varios tipos de autobuses en ciudades y lugares indonesios realistas y auténticos. Puede elegir entre diferentes modelos de bus, como Srikandi SHD, Arjuna XHD, Bimasena SDD, JB SHD y más. También puede personalizar su autobús con diferentes características, como bocinas, luces, espejos, puertas, etc.</p>
- <h3>Características de Bus Simulator Indonesia</h3>
- <p>Bus Simulator Indonesia no es solo un juego de conducción simple. Tiene muchas características que lo hacen más divertido y atractivo. Algunas de estas características son:</p>
- <ul>
-
-<li><strong>Control muy fácil e intuitivo</strong>: Puedes controlar tu bus con simples gestos táctiles o inclinar tu dispositivo. También puede ajustar el ángulo de la cámara, la sensibilidad de la dirección, la fuerza del freno, etc.</li>
-<li><strong>Ciudades y lugares indonesios auténticos</strong>: Puede conducir su autobús en gráficos 3D realistas y detallados que representan varias ciudades y lugares de Indonesia, como Yakarta, Surabaya, Bali, Sumatra, Aceh, etc.</li>
-<li><strong>Autobuses de Indonesia</strong>: Puedes elegir entre diferentes tipos de autobuses que son populares y comunes en Indonesia, como Srikandi SHD, Arjuna XHD, Bimasena SDD, JB SHD, etc.</li>
-<li><strong>Fresco y divertido bocinazos</strong>: Usted puede tocar la bocina con diferentes sonidos y efectos, incluyendo el icónico "Om Telolet Om!" bocina que se convirtió en un fenómeno viral en 2016. </li>
-<li><strong>Tabla de clasificación y ahorro de datos en línea</strong>: Usted puede competir con otros jugadores en la clasificación y guardar su progreso en línea. </li>
-<li><strong>Vehicle mod system</strong>: Puede utilizar su propio modelo 3D utilizando un sistema de modificación de vehículos que le permite importar autobuses personalizados de fuentes externas. </li>
-<li><strong>Convoy multijugador en línea <h2>¿Qué es la librea en Bus Simulator Indonesia? </h2>
- <p>Livery es una característica que te permite cambiar la apariencia de tu bus con varias pieles y temas. Puedes elegir entre diferentes opciones de librea que están disponibles en el juego, o puedes crear tu propia librea utilizando una plantilla proporcionada por el juego. La librea puede hacer que su autobús se vea más atractivo y único, así como reflejar su personalidad y estilo. </p>
- <h3>Tipos de librea en el simulador de autobús Indonesia</h3>
- <p>Hay muchos tipos de librea que puede utilizar en Bus Simulator Indonesia, dependiendo de su preferencia y gusto. Algunos de los tipos más populares de librea son:</p>
- <ul>
-
-<li><strong>Librea basada en clubes de fútbol</strong>: Puedes usar librea basada en tus clubes de fútbol favoritos, como Persebaya, Persib, Persija, Arema, etc. Esta librea puede mostrar tu apoyo y lealtad a tu equipo. </li>
-<li><strong>Librea basada en diseños personalizados</strong>: Puede utilizar librea que se basan en su propia creatividad e imaginación. Puede crear librea con varios colores, patrones, logotipos, imágenes, etc. Estas libreas pueden hacer que su autobús se vea más único y original. </li>
-</ul>
- <h3>Beneficios de usar Livery en Bus Simulator Indonesia</h3>
- <p>Usar librea en Bus Simulator Indonesia puede tener muchos beneficios para usted como jugador. Algunos de estos beneficios son:</p>
-<p></p>
- <ul>
-<li><strong>Mejora tu experiencia de juego</strong>: Usar librea puede hacer que tu experiencia de juego sea más divertida y agradable. Puede personalizar su bus de acuerdo a su estado de ánimo y preferencia, y conducirlo en diferentes escenarios y entornos. </li>
-<li><strong>Exprésate</strong>: Usar librea puede ayudarte a expresarte y a expresar tu personalidad. Puedes usar librea que refleje tus intereses, aficiones, pasiones, etc. También puedes usar librea que transmita tus mensajes, opiniones, emociones, etc.</li>
-<li><strong>Impresiona a otros</strong>: Usar librea puede ayudarte a impresionar a otros y ganar su admiración. Puede usar librea que sea llamativa, hermosa, fresca o divertida. También puede usar librea que sea rara, exclusiva o hecha a medida. </li>
-</ul>
- <h2>Cómo descargar y aplicar Livery en Bus Simulator Indonesia</h2>
- <p>Si quieres usar librea en Bus Simulator Indonesia, necesitas descargarlas y aplicarlas primero. Hay dos formas de hacer esto: usando la tienda de libreas del juego o usando fuentes externas. </p>
- <h3>Pasos para descargar Livery in Bus Simulator Indonesia</h3>
- <p>Para descargar librea de la tienda de librea del juego, debes seguir estos pasos:</p>
- <ol>
-<li>Abre el juego y toca el icono "Garaje" en el menú principal. </li>
-
-<li>Verá una lista de opciones de librea disponibles para su modelo de bus. Toque en el que le gusta y pulse en el botón "Descargar". </li>
-<li>Espera a que la descarga termine y toca el botón "Aplicar". </li>
-<li>Has descargado y aplicado correctamente la librea a tu bus. </li>
-</ol>
- <p>Para descargar librea de fuentes externas, debe seguir estos pasos:</p>
- <ol>
-<li>Encontrar un sitio web o una aplicación que proporciona librea para Bus Simulator Indonesia. Por ejemplo, puede utilizar [Gamedaim]( 1 ), [Raina]( 2 ), o [Segitekno]( 3 ). </li>
-<li>Navega por las colecciones de librea y elige la que más te guste. Asegúrate de que la librea sea compatible con tu modelo de bus. </li>
-<li>Toque en el botón "Descargar" o enlace y guarde el archivo en su dispositivo. </li>
-<li>Abre el juego y toca el icono "Garaje" en el menú principal. </li>
-<li> Seleccione el modelo de bus que desea utilizar y toque en el icono "Librea" en la esquina inferior derecha. </li>
-<li>Toque en el botón "Importar" en la esquina superior derecha y seleccione el archivo que descargó de su dispositivo. </li>
-<li>Has descargado y aplicado correctamente la librea a tu bus. </li>
-</ol>
- <h3>Pasos para aplicar Librea en Bus Simulator Indonesia</h3>
- <p>Si ya has descargado alguna librea de cualquiera de las fuentes, puedes aplicarla cuando quieras. Para aplicar librea que ya ha descargado, debe seguir estos pasos:</p>
- <ol>
-<li>Abre el juego y toca el icono "Garaje" en el menú principal. </li>
-<li> Seleccione el modelo de bus que desea utilizar y toque en el icono "Librea" en la esquina inferior derecha. </li>
-<li>Verá una lista de opciones de librea descargadas para su modelo de bus. Toque en el que desea usar y toque en el botón "Aplicar". </li>
-<li> Ha aplicado correctamente la librea a su bus. </li>
-</ol>
- <h2>Consejos y trucos para diseñar su propia librea en Bus Simulator Indonesia</h2>
-
- <p>Aquí hay algunos consejos y trucos para diseñar su propia librea en Bus Simulator Indonesia:</p>
- <h3>Elija la plantilla correcta para su modelo de bus</h3>
- <p>Antes de empezar a diseñar su librea, asegúrese de elegir la plantilla correcta para su modelo de bus. Los diferentes modelos de bus tienen diferentes plantillas, por lo que debe coincidir con ellos en consecuencia. Por ejemplo, si quieres diseñar una librea para Srikandi SHD, necesitas usar la plantilla llamada "Srikandi SHD.png". Si usa una plantilla incorrecta, su librea puede no encajar correctamente o verse distorsionada en su autobús. </p>
- <h3>Utilice aplicaciones de edición de fotos o software para crear su librea</h3>
- <p>Una vez que haya elegido la plantilla correcta, puede usar cualquier aplicación de edición de fotos o software que soporte formato PNG para crear su librea. Puede usar varias herramientas y características para editar la plantilla, como recortar, cambiar el tamaño, rotar, voltear, cortar, pegar, rellenar, dibujar, borrar, etc. También puede agregar varios efectos y filtros para mejorar su librea, como brillo, contraste, saturación, matiz, desenfoque, etc.</p>
- <h3>Sé creativo y original con tu diseño de librea</h3>
- <p>El consejo más importante para diseñar tu propia librea es ser creativo y original. Puedes usar cualquier color, patrón, logos, imágenes, textos, etc. que te guste y que se adapte a tu modelo de bus. También puede usar referencias de compañías de autobuses reales, clubes de fútbol, diseños personalizados, etc. Sin embargo, asegúrese de no copiar o plagiar los diseños de librea de otras personas. También debes evitar usar contenido inapropiado u ofensivo que pueda violar los términos de servicio del juego o dañar los sentimientos de otros jugadores. </p>
- <h2>Conclusión</h2>
-
- <p>Para descargar y aplicar Livery en Bus Simulator Indonesia, puede usar la tienda de libreas del juego o fuentes externas. También puede diseñar su propia librea utilizando cualquier aplicación de edición de fotos o software que soporte formato PNG. Sin embargo, debe elegir la plantilla correcta para su modelo de bus y ser creativo y original con su diseño de Livery. </p>
- <p>Esperamos que este artículo te haya ayudado a aprender más sobre Bus Simulator Indonesia y Livery. Si usted tiene alguna pregunta o retroalimentación, por favor no dude en dejar un comentario a continuación. Gracias por leer y feliz juego! </p>
- <h2>Preguntas frecuentes</h2>
- <p>Aquí hay algunas preguntas frecuentes sobre Bus Simulator Indonesia y Livery:</p>
- <ol>
-<li><strong>¿Cómo actualizo Bus Simulator Indonesia? </strong></li>
-<p>Para actualizar Bus Simulator Indonesia, es necesario ir a la Google Play Store o App Store y comprobar si hay una nueva versión disponible. Si hay, toque en el "Actualizar" botón y esperar a que la descarga y la instalación para terminar. Alternativamente, también puedes descargar el último archivo APK desde el sitio web oficial del juego e instalarlo manualmente. </p>
-<li><strong>¿Cómo elimino Livery en Bus Simulator Indonesia? </strong></li>
-<p>Para eliminar Livery en Bus Simulator Indonesia, es necesario ir al menú "Garaje" y toque en el "Librea" icono. Luego, toque en el botón "Eliminar" en la esquina superior derecha y seleccione la librea que desea eliminar. Toque en el botón "Sí" para confirmar. </p> <li><strong> ¿Cómo comparto librea en Bus Simulator Indonesia? </strong></li>
-<p>Para compartir la librea en Bus Simulator Indonesia, es necesario ir al menú "Garaje" y toque en el icono "Librea". Luego, toca el botón "Compartir" en la esquina superior derecha y selecciona la librea que deseas compartir. Puede optar por compartir su librea a través de las redes sociales, correo electrónico, Bluetooth, etc.</p>
-<li><strong>¿Cómo puedo obtener más monedas en Bus Simulator Indonesia? </strong></li>
-
-<li><strong>¿Cómo me uno a un convoy en Bus Simulator Indonesia? </strong></li>
-<p>Para unirse a un convoy en Bus Simulator Indonesia, debe ir al menú "Multijugador" y tocar el botón "Unirse al convoy". Puedes elegir unirte a un convoy público o privado. Si te unes a un convoy público, serás emparejado con otros jugadores al azar. Si se une a un convoy privado, tendrá que introducir un código proporcionado por el líder del convoy. </p> 64aa2da5cf<br />
-<br />
-<br />

spaces/Benson/text-generation/Examples/Descargar Gratis Templo Ejecutar Juego Para Pc.md

@@ -1,74 +0,0 @@
-
-<h1>Cómo descargar gratis Temple Run juego para PC</h1>
-<p>Temple Run es uno de los juegos móviles más populares de todos los tiempos, con más de mil millones de descargas en todo el mundo. Es un juego de corredor sin fin donde tienes que escapar de un templo con un ídolo maldito, evitando obstáculos, lagunas y monos que te persiguen. El juego es rápido, adictivo y divertido, y también se puede jugar en su PC.</p>
-<h2>descargar gratis templo ejecutar juego para pc</h2><br /><p><b><b>DOWNLOAD</b> ->>> <a href="https://bltlly.com/2v6JXR">https://bltlly.com/2v6JXR</a></b></p><br /><br />
-<p>En este artículo, le mostraremos cómo descargar gratis Temple Run juego para PC utilizando diferentes métodos. Ya sea que quieras reproducirlo en tu navegador, descargarlo desde la Microsoft Store, obtenerlo desde el sitio web oficial o comprarlo desde Steam, lo tenemos cubierto. Solo sigue estos sencillos pasos y disfruta de esta emocionante aventura en tu ordenador. </p>
- <h2>Descarga desde Microsoft Store</h2>
-<p>Microsoft Store ofrece una variedad de juegos gratuitos y de pago que puedes descargar directamente desde la tienda. Si tiene Windows 10 o posterior, ya tiene acceso a Microsoft Store en su PC. Así es como puede descargar Temple Run desde allí:</p>
-<ol>
-<li>Abra la tienda de Microsoft haciendo clic en su icono en la barra de tareas o buscándolo en el menú Inicio. </li>
-<li>Buscar templo Ejecutar en el cuadro de búsqueda en la esquina superior derecha de la tienda. </li>
-<li>Haga clic en la ficha del juego para ver más información al respecto. </li>
-<li>Seleccione Obtener o Instalar para comenzar a descargar el juego gratis. </li>
-<li>Espere a que la descarga termine y inicie el juego desde su menú Inicio o escritorio. </li>
-</ol>
- <h2>Descargar de Poki.com</h2>
-<p>Poki.com es un sitio web que te permite jugar miles de juegos en línea gratis sin descargar nada. Puedes jugar en tu navegador usando tu teclado, ratón o pantalla táctil. Uno de los juegos disponibles en Poki.com es Temple Run 2, que es la secuela de Temple Run con gráficos mejorados, nuevos mapas y más características. Así es como puedes jugar Temple Run 2 en Poki.com:</p>
-<p></p>
-<ol>
-
-<li>Buscar Temple Run 2 en el cuadro de búsqueda en la esquina superior derecha del sitio web. </li>
-<li>Haga clic en la ficha del juego para ver más información al respecto. </li>
-<li>Seleccione Jugar ahora para comenzar a jugar el juego en su navegador. </li>
-<li>Disfruta del juego y trata de correr tan lejos como puedas. </li>
-</ol>
- <h2>Descarga del sitio web de Imangi Studios</h2>
-<p>Imangi Studios es el desarrollador de Temple Run y Temple Run 2. Puedes visitar su sitio web oficial para aprender más sobre sus juegos, su equipo y sus noticias. También puedes descargar sus juegos para PC desde su sitio web. Así es como puedes hacerlo:</p>
-<ol>
-<li>Ir a [Sitio web de Imangi Studios] usando su navegador web preferido. </li>
-<li>Haga clic en Juegos en la barra de menú superior para ver su lista de juegos. </li>
-<li>Elige Temple Run o Temple Run 2 dependiendo del que quieras jugar. </li>
-<li>Haga clic en Descargar para PC para descargar el archivo de instalación del juego. </li>
-<li>Guarde el archivo en la ubicación deseada y ejecute la configuración. </li>
-<li>Siga las instrucciones en la pantalla e instale el juego en su PC.</li>
-<li> Iniciar el juego desde el menú Inicio o el escritorio y divertirse. </li>
-</ol>
- <h2>Descargar desde Steam</h2>
-<p>Steam es una popular plataforma en línea que ofrece una variedad de juegos, software y otros contenidos digitales. Puedes comprar, descargar y jugar juegos en Steam usando tu PC, Mac o Linux. También puedes chatear con otros jugadores, unirte a comunidades y acceder a otras funciones. Para jugar a Temple Run o Temple Run 2 en Steam, necesitas tener Steam instalado en tu PC y tener una cuenta. Así es como puedes descargar Temple Run o Temple Run 2 desde Steam:</p>
-<ol>
-<li>Descarga e instala Steam en tu PC desde [sitio web de Steam]. </li>
-<li>Crea una cuenta o inicia sesión en Steam usando tu correo electrónico y contraseña. </li>
-<li>Buscar Temple Run o Temple Run 2 en la tienda de vapor usando el cuadro de búsqueda en la parte superior de la página. </li>
-<li>Haga clic en la ficha del juego para ver más información al respecto. </li>
-
-<li>Proceda a realizar la compra y complete la compra usando su método de pago preferido. </li>
-<li>Vaya a su biblioteca e instale el juego en su PC haciendo clic en Instalar.</li>
-<li>Inicie el juego desde Steam haciendo clic en Play.</li>
-</ol>
- <h2>Consejos y trucos para jugar Temple Run en PC</h2>
-<p>Jugar Temple Run en PC puede ser una experiencia diferente que jugar en tu dispositivo móvil. Es posible que necesite ajustar algunos ajustes, aprender algunos controles y practicar algunas habilidades. Aquí hay algunos consejos y trucos que pueden ayudarle a jugar Temple Run mejor en su PC:</p>
-<ul>
-<li> Utilice los controles del teclado o del ratón para mover, saltar, deslizarse y girar. Puede usar las teclas de flecha o las teclas WASD para moverse a la izquierda, derecha, arriba y abajo. También puede utilizar el ratón para deslizar el dedo en esas direcciones. Alternativamente, puede usar un controlador si tiene uno conectado a su PC.</li>
-<li>Recoger monedas y potenciadores para aumentar su puntuación y habilidades. Las monedas se pueden utilizar para comprar nuevos personajes, trajes, potenciadores y otros artículos en la tienda. Los potenciadores pueden darte beneficios temporales como aumento de velocidad, imán de monedas, escudo o multiplicador de puntuación. Trata de recoger tantas monedas y potenciadores como puedas mientras corres. </li>
-<li>Evite obstáculos, lagunas y monos que lo ralentizarán o terminarán su carrera. Los obstáculos incluyen árboles, rocas, fuego, trampas, paredes y más. Los huecos son agujeros o acantilados por los que necesitas saltar o deslizarte. Los monos son enemigos que te perseguirán después de que saques el ídolo del templo. Te alcanzarán si desaceleras o cometes un error. Trata de evitar estos peligros moviéndote rápida y cuidadosamente. </li>
-
-<li>Diviértete y desafíate a batir tus propios récords. El objetivo principal de Temple Run es correr tan lejos como puedas sin ser atrapado o caerte. El juego hará un seguimiento de su distancia, puntuación, monedas recogidas, power-ups utilizados, y otras estadísticas. Puedes ver tus mejores carreras en la tabla de clasificación y compararlas con otros jugadores de todo el mundo. También puedes desafiarte a batir tus propios récords y mejorar tus habilidades. Diviértete y disfruta de la emoción de Temple Run en tu PC.</li>
-</ul>
- <h1>Conclusión</h1>
-<p>Temple Run es un juego que puedes jugar gratis en tu PC usando diferentes métodos. Puedes descargarlo desde Microsoft Store, reproducirlo online en Poki.com, obtenerlo desde el sitio web de Imangi Studios o comprarlo desde Steam. También puedes usar algunos consejos y trucos para jugar mejor en tu PC, como usar controles de teclado o ratón, recoger monedas y potenciadores, evitar obstáculos, lagunas y monos, completar objetivos y logros, y divertirte y desafiarte. Temple Run es un juego que te mantendrá entretenido y comprometido durante horas. Pruébalo hoy y mira hasta dónde puedes correr. </p>
- <h2>Preguntas frecuentes</h2>
-<p>Aquí hay algunas preguntas frecuentes sobre Temple Run y cómo descargarlo para PC:</p>
-<ol>
-<li><b>Temple Run es gratis para jugar? </b></li>
-<p>Sí, Temple Run es gratis para jugar en la mayoría de las plataformas, incluyendo PC. Puedes descargarlo gratis desde Microsoft Store, reproducirlo online en Poki.com, o obtenerlo desde el sitio web de Imangi Studios. Sin embargo, si quieres jugar en Steam, necesitas comprarlo por una pequeña tarifa. </p>
-<li><b>¿Cuáles son las diferencias entre Temple Run y Temple Run 2?</b></li>
-<p>Temple Run 2 es la secuela de Temple Run con algunas mejoras y adiciones. Tiene mejores gráficos, más mapas, más personajes, más potenciadores, más obstáculos, más logros y más características. Sin embargo, el modo de juego y el concepto siguen siendo los mismos: tienes que correr tan lejos como puedas evitando peligros. </p>
-
-<p>Sí, puede jugar Temple Run sin conexión si lo descarga en su PC. No necesita una conexión a Internet para jugar el juego una vez que lo instale. Sin embargo, si quieres jugar online en Poki.com, necesitas una conexión a Internet para acceder al sitio web. </p>
-<li><b>¿Puedo sincronizar mi progreso entre dispositivos? </b></li>
-<p>Sí, puedes sincronizar tu progreso entre dispositivos si usas la misma cuenta o método de inicio de sesión. Por ejemplo, si usas Facebook para iniciar sesión en Temple Run en tu dispositivo móvil, también puedes usar Facebook para iniciar sesión en Temple Run en tu PC y ver tu progreso allí. </p>
-<li><b>¿Cómo puedo contactar a los desarrolladores de Temple Run? </b></li>
-<p>Puede ponerse en contacto con los desarrolladores de Temple Run visitando su sitio web oficial y haciendo clic en Contáctenos en la parte inferior de la página. También puedes seguirlos en plataformas de redes sociales como Facebook, Twitter, Instagram o YouTube.</p>
-</ol></p> 64aa2da5cf<br />
-<br />
-<br />

spaces/Big-Web/MMSD/env/Lib/site-packages/boto3/ec2/deletetags.py

@@ -1,37 +0,0 @@
-# Copyright 2016 Amazon.com, Inc. or its affiliates. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License"). You
-# may not use this file except in compliance with the License. A copy of
-# the License is located at
-#
-# https://aws.amazon.com/apache2.0/
-#
-# or in the "license" file accompanying this file. This file 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.
-from boto3.resources.action import CustomModeledAction
-
-
-def inject_delete_tags(event_emitter, **kwargs):
-    action_model = {
-        'request': {
-            'operation': 'DeleteTags',
-            'params': [
-                {
-                    'target': 'Resources[0]',
-                    'source': 'identifier',
-                    'name': 'Id',
-                }
-            ],
-        }
-    }
-    action = CustomModeledAction(
-        'delete_tags', action_model, delete_tags, event_emitter
-    )
-    action.inject(**kwargs)
-
-
-def delete_tags(self, **kwargs):
-    kwargs['Resources'] = [self.id]
-    return self.meta.client.delete_tags(**kwargs)

spaces/Big-Web/MMSD/env/Lib/site-packages/pkg_resources/_vendor/pyparsing/exceptions.py

@@ -1,267 +0,0 @@
-# exceptions.py
-
-import re
-import sys
-import typing
-
-from .util import col, line, lineno, _collapse_string_to_ranges
-from .unicode import pyparsing_unicode as ppu
-
-
-class ExceptionWordUnicode(ppu.Latin1, ppu.LatinA, ppu.LatinB, ppu.Greek, ppu.Cyrillic):
-    pass
-
-
-_extract_alphanums = _collapse_string_to_ranges(ExceptionWordUnicode.alphanums)
-_exception_word_extractor = re.compile("([" + _extract_alphanums + "]{1,16})|.")
-
-
-class ParseBaseException(Exception):
-    """base exception class for all parsing runtime exceptions"""
-
-    # Performance tuning: we construct a *lot* of these, so keep this
-    # constructor as small and fast as possible
-    def __init__(
-        self,
-        pstr: str,
-        loc: int = 0,
-        msg: typing.Optional[str] = None,
-        elem=None,
-    ):
-        self.loc = loc
-        if msg is None:
-            self.msg = pstr
-            self.pstr = ""
-        else:
-            self.msg = msg
-            self.pstr = pstr
-        self.parser_element = self.parserElement = elem
-        self.args = (pstr, loc, msg)
-
-    @staticmethod
-    def explain_exception(exc, depth=16):
-        """
-        Method to take an exception and translate the Python internal traceback into a list
-        of the pyparsing expressions that caused the exception to be raised.
-
-        Parameters:
-
-        - exc - exception raised during parsing (need not be a ParseException, in support
-          of Python exceptions that might be raised in a parse action)
-        - depth (default=16) - number of levels back in the stack trace to list expression
-          and function names; if None, the full stack trace names will be listed; if 0, only
-          the failing input line, marker, and exception string will be shown
-
-        Returns a multi-line string listing the ParserElements and/or function names in the
-        exception's stack trace.
-        """
-        import inspect
-        from .core import ParserElement
-
-        if depth is None:
-            depth = sys.getrecursionlimit()
-        ret = []
-        if isinstance(exc, ParseBaseException):
-            ret.append(exc.line)
-            ret.append(" " * (exc.column - 1) + "^")
-        ret.append("{}: {}".format(type(exc).__name__, exc))
-
-        if depth > 0:
-            callers = inspect.getinnerframes(exc.__traceback__, context=depth)
-            seen = set()
-            for i, ff in enumerate(callers[-depth:]):
-                frm = ff[0]
-
-                f_self = frm.f_locals.get("self", None)
-                if isinstance(f_self, ParserElement):
-                    if frm.f_code.co_name not in ("parseImpl", "_parseNoCache"):
-                        continue
-                    if id(f_self) in seen:
-                        continue
-                    seen.add(id(f_self))
-
-                    self_type = type(f_self)
-                    ret.append(
-                        "{}.{} - {}".format(
-                            self_type.__module__, self_type.__name__, f_self
-                        )
-                    )
-
-                elif f_self is not None:
-                    self_type = type(f_self)
-                    ret.append("{}.{}".format(self_type.__module__, self_type.__name__))
-
-                else:
-                    code = frm.f_code
-                    if code.co_name in ("wrapper", "<module>"):
-                        continue
-
-                    ret.append("{}".format(code.co_name))
-
-                depth -= 1
-                if not depth:
-                    break
-
-        return "\n".join(ret)
-
-    @classmethod
-    def _from_exception(cls, pe):
-        """
-        internal factory method to simplify creating one type of ParseException
-        from another - avoids having __init__ signature conflicts among subclasses
-        """
-        return cls(pe.pstr, pe.loc, pe.msg, pe.parserElement)
-
-    @property
-    def line(self) -> str:
-        """
-        Return the line of text where the exception occurred.
-        """
-        return line(self.loc, self.pstr)
-
-    @property
-    def lineno(self) -> int:
-        """
-        Return the 1-based line number of text where the exception occurred.
-        """
-        return lineno(self.loc, self.pstr)
-
-    @property
-    def col(self) -> int:
-        """
-        Return the 1-based column on the line of text where the exception occurred.
-        """
-        return col(self.loc, self.pstr)
-
-    @property
-    def column(self) -> int:
-        """
-        Return the 1-based column on the line of text where the exception occurred.
-        """
-        return col(self.loc, self.pstr)
-
-    def __str__(self) -> str:
-        if self.pstr:
-            if self.loc >= len(self.pstr):
-                foundstr = ", found end of text"
-            else:
-                # pull out next word at error location
-                found_match = _exception_word_extractor.match(self.pstr, self.loc)
-                if found_match is not None:
-                    found = found_match.group(0)
-                else:
-                    found = self.pstr[self.loc : self.loc + 1]
-                foundstr = (", found %r" % found).replace(r"\\", "\\")
-        else:
-            foundstr = ""
-        return "{}{}  (at char {}), (line:{}, col:{})".format(
-            self.msg, foundstr, self.loc, self.lineno, self.column
-        )
-
-    def __repr__(self):
-        return str(self)
-
-    def mark_input_line(self, marker_string: str = None, *, markerString=">!<") -> str:
-        """
-        Extracts the exception line from the input string, and marks
-        the location of the exception with a special symbol.
-        """
-        markerString = marker_string if marker_string is not None else markerString
-        line_str = self.line
-        line_column = self.column - 1
-        if markerString:
-            line_str = "".join(
-                (line_str[:line_column], markerString, line_str[line_column:])
-            )
-        return line_str.strip()
-
-    def explain(self, depth=16) -> str:
-        """
-        Method to translate the Python internal traceback into a list
-        of the pyparsing expressions that caused the exception to be raised.
-
-        Parameters:
-
-        - depth (default=16) - number of levels back in the stack trace to list expression
-          and function names; if None, the full stack trace names will be listed; if 0, only
-          the failing input line, marker, and exception string will be shown
-
-        Returns a multi-line string listing the ParserElements and/or function names in the
-        exception's stack trace.
-
-        Example::
-
-            expr = pp.Word(pp.nums) * 3
-            try:
-                expr.parse_string("123 456 A789")
-            except pp.ParseException as pe:
-                print(pe.explain(depth=0))
-
-        prints::
-
-            123 456 A789
-                    ^
-            ParseException: Expected W:(0-9), found 'A'  (at char 8), (line:1, col:9)
-
-        Note: the diagnostic output will include string representations of the expressions
-        that failed to parse. These representations will be more helpful if you use `set_name` to
-        give identifiable names to your expressions. Otherwise they will use the default string
-        forms, which may be cryptic to read.
-
-        Note: pyparsing's default truncation of exception tracebacks may also truncate the
-        stack of expressions that are displayed in the ``explain`` output. To get the full listing
-        of parser expressions, you may have to set ``ParserElement.verbose_stacktrace = True``
-        """
-        return self.explain_exception(self, depth)
-
-    markInputline = mark_input_line
-
-
-class ParseException(ParseBaseException):
-    """
-    Exception thrown when a parse expression doesn't match the input string
-
-    Example::
-
-        try:
-            Word(nums).set_name("integer").parse_string("ABC")
-        except ParseException as pe:
-            print(pe)
-            print("column: {}".format(pe.column))
-
-    prints::
-
-       Expected integer (at char 0), (line:1, col:1)
-        column: 1
-
-    """
-
-
-class ParseFatalException(ParseBaseException):
-    """
-    User-throwable exception thrown when inconsistent parse content
-    is found; stops all parsing immediately
-    """
-
-
-class ParseSyntaxException(ParseFatalException):
-    """
-    Just like :class:`ParseFatalException`, but thrown internally
-    when an :class:`ErrorStop<And._ErrorStop>` ('-' operator) indicates
-    that parsing is to stop immediately because an unbacktrackable
-    syntax error has been found.
-    """
-
-
-class RecursiveGrammarException(Exception):
-    """
-    Exception thrown by :class:`ParserElement.validate` if the
-    grammar could be left-recursive; parser may need to enable
-    left recursion using :class:`ParserElement.enable_left_recursion<ParserElement.enable_left_recursion>`
-    """
-
-    def __init__(self, parseElementList):
-        self.parseElementTrace = parseElementList
-
-    def __str__(self) -> str:
-        return "RecursiveGrammarException: {}".format(self.parseElementTrace)

spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_importlib.py

@@ -1,47 +0,0 @@
-import sys
-
-
-def disable_importlib_metadata_finder(metadata):
-    """
-    Ensure importlib_metadata doesn't provide older, incompatible
-    Distributions.
-
-    Workaround for #3102.
-    """
-    try:
-        import importlib_metadata
-    except ImportError:
-        return
-    except AttributeError:
-        import warnings
-
-        msg = (
-            "`importlib-metadata` version is incompatible with `setuptools`.\n"
-            "This problem is likely to be solved by installing an updated version of "
-            "`importlib-metadata`."
-        )
-        warnings.warn(msg)  # Ensure a descriptive message is shown.
-        raise  # This exception can be suppressed by _distutils_hack
-
-    if importlib_metadata is metadata:
-        return
-    to_remove = [
-        ob
-        for ob in sys.meta_path
-        if isinstance(ob, importlib_metadata.MetadataPathFinder)
-    ]
-    for item in to_remove:
-        sys.meta_path.remove(item)
-
-
-if sys.version_info < (3, 10):
-    from setuptools.extern import importlib_metadata as metadata
-    disable_importlib_metadata_finder(metadata)
-else:
-    import importlib.metadata as metadata  # noqa: F401
-
-
-if sys.version_info < (3, 9):
-    from setuptools.extern import importlib_resources as resources
-else:
-    import importlib.resources as resources  # noqa: F401

spaces/BilalSardar/facrec/app.py

@@ -1,92 +0,0 @@
-import cv2
-import numpy as np
-import os
-import pickle
-from deepface import DeepFace
-import gradio as gr
-from datetime import datetime
-import fast_colorthief
-import webcolors
-from PIL import Image
-
-
-
-thres = 0.45
-classNames= []
-classFile = 'coco.names'
-with open(classFile,'rt') as f:
-  #classNames = f.read().rstrip('n').split('n')
-  classNames = f.readlines()
-
-
-# remove new line characters
-classNames = [x.strip() for x in classNames]
-print(classNames)
-configPath = 'ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt'
-weightsPath = 'frozen_inference_graph.pb'
-net = cv2.dnn_DetectionModel(weightsPath,configPath)
-net.setInputSize(320,320)
-net.setInputScale(1.0/ 127.5)
-net.setInputMean((127.5, 127.5, 127.5))
-net.setInputSwapRB(True)
-
-
-
-def main(image): 
-  gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-  rgb=cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-  names=[]
-
-
-  #object
-  try:
-        classIds, confs, bbox = net.detect(image,confThreshold=thres)
-  except  Exception as err:
-      print(err)
-  print(classIds,bbox)
-  try:
-    if len(classIds) != 0:
-        for classId, confidence,box in zip(classIds.flatten(),confs.flatten(),bbox):
-          if names.count(classNames[classId-1]) == 0:
-              names.append(classNames[classId-1])
-  except  Exception as err:
-      print(err)
-  #emotion
-
-  try:
-      face_analysis_2=DeepFace.analyze(image, actions = ['emotion'], enforce_detection=False)
-      names.append(face_analysis_2[0]["dominant_emotion"])
-  except:
-     print("No face")
-     names.append("No Face")
-
-  # #Colour
-
-  colourimage = Image.fromarray(image)
-  colourimage = colourimage.convert('RGBA')
-  colourimage = np.array(colourimage).astype(np.uint8)
-  palette=fast_colorthief.get_palette(colourimage)
-
-
-  for i in range(len(palette)):
-    diff={}
-    for color_hex, color_name in webcolors.CSS3_HEX_TO_NAMES.items():
-      r, g, b = webcolors.hex_to_rgb(color_hex)
-      diff[sum([(r - palette[i][0])**2,
-                (g - palette[i][1])**2,
-                (b - palette[i][2])**2])]= color_name
-    if names.count(diff[min(diff.keys())])==0:
-      names.append(diff[min(diff.keys())])
-
-
-  
-
-  return ' '.join(names)
-interface = gr.Interface(fn=main, 
-                        inputs=["image"],
-                        outputs=[gr.inputs.Textbox(label='Names of person in image')], 
-                        title='Color Object Emotion ',
-                        description='This Space:\n \n2) Detect Emotion \n3) Detect Colors.\n4) Object Detection \n')
-                        
-
-interface.launch(inline=False)

spaces/CVPR/LIVE/thrust/thrust/system/detail/adl/copy.h

@@ -1,44 +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 <thrust/detail/config.h>
-
-// the purpose of this header is to #include the copy.h header
-// of the sequential, host, and device systems. It should be #included in any
-// code which uses adl to dispatch copy
-
-#include <thrust/system/detail/sequential/copy.h>
-
-// SCons can't see through the #defines below to figure out what this header
-// includes, so we fake it out by specifying all possible files we might end up
-// including inside an #if 0.
-#if 0
-#include <thrust/system/cpp/detail/copy.h>
-#include <thrust/system/cuda/detail/copy.h>
-#include <thrust/system/omp/detail/copy.h>
-#include <thrust/system/tbb/detail/copy.h>
-#endif
-
-#define __THRUST_HOST_SYSTEM_COPY_HEADER <__THRUST_HOST_SYSTEM_ROOT/detail/copy.h>
-#include __THRUST_HOST_SYSTEM_COPY_HEADER
-#undef __THRUST_HOST_SYSTEM_COPY_HEADER
-
-#define __THRUST_DEVICE_SYSTEM_COPY_HEADER <__THRUST_DEVICE_SYSTEM_ROOT/detail/copy.h>
-#include __THRUST_DEVICE_SYSTEM_COPY_HEADER
-#undef __THRUST_DEVICE_SYSTEM_COPY_HEADER
-

spaces/CVPR/SPOTER_Sign_Language_Recognition/spoter/spoter_model.py

@@ -1,70 +0,0 @@
-
-import copy
-import torch
-
-import torch.nn as nn
-from typing import Optional
-
-
-def _get_clones(mod, n):
-    return nn.ModuleList([copy.deepcopy(mod) for _ in range(n)])
-
-
-class SPOTERTransformerDecoderLayer(nn.TransformerDecoderLayer):
-    """
-    Edited TransformerDecoderLayer implementation omitting the redundant self-attention operation as opposed to the
-    standard implementation.
-    """
-
-    def __init__(self, d_model, nhead, dim_feedforward, dropout, activation):
-        super(SPOTERTransformerDecoderLayer, self).__init__(d_model, nhead, dim_feedforward, dropout, activation)
-
-        del self.self_attn
-
-    def forward(self, tgt: torch.Tensor, memory: torch.Tensor, tgt_mask: Optional[torch.Tensor] = None,
-                memory_mask: Optional[torch.Tensor] = None, tgt_key_padding_mask: Optional[torch.Tensor] = None,
-                memory_key_padding_mask: Optional[torch.Tensor] = None) -> torch.Tensor:
-
-        tgt = tgt + self.dropout1(tgt)
-        tgt = self.norm1(tgt)
-        tgt2 = self.multihead_attn(tgt, memory, memory, attn_mask=memory_mask,
-                                   key_padding_mask=memory_key_padding_mask)[0]
-        tgt = tgt + self.dropout2(tgt2)
-        tgt = self.norm2(tgt)
-        tgt2 = self.linear2(self.dropout(self.activation(self.linear1(tgt))))
-        tgt = tgt + self.dropout3(tgt2)
-        tgt = self.norm3(tgt)
-
-        return tgt
-
-
-class SPOTER(nn.Module):
-    """
-    Implementation of the SPOTER (Sign POse-based TransformER) architecture for sign language recognition from sequence
-    of skeletal data.
-    """
-
-    def __init__(self, num_classes, hidden_dim=55):
-        super().__init__()
-
-        self.row_embed = nn.Parameter(torch.rand(50, hidden_dim))
-        self.pos = nn.Parameter(torch.cat([self.row_embed[0].unsqueeze(0).repeat(1, 1, 1)], dim=-1).flatten(0, 1).unsqueeze(0))
-        self.class_query = nn.Parameter(torch.rand(1, hidden_dim))
-        self.transformer = nn.Transformer(hidden_dim, 9, 6, 6)
-        self.linear_class = nn.Linear(hidden_dim, num_classes)
-
-        # Deactivate the initial attention decoder mechanism
-        custom_decoder_layer = SPOTERTransformerDecoderLayer(self.transformer.d_model, self.transformer.nhead, 2048,
-                                                             0.1, "relu")
-        self.transformer.decoder.layers = _get_clones(custom_decoder_layer, self.transformer.decoder.num_layers)
-
-    def forward(self, inputs):
-        h = torch.unsqueeze(inputs.flatten(start_dim=1), 1).float()
-        h = self.transformer(self.pos + h, self.class_query.unsqueeze(0)).transpose(0, 1)
-        res = self.linear_class(h)
-
-        return res
-
-
-if __name__ == "__main__":
-    pass

spaces/Carterclear/swarm-agents/app.py

@@ -1,161 +0,0 @@
-import gradio as gr
-import os 
-import json 
-import requests
-
-#Streaming endpoint 
-API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
-
-#Huggingface provided GPT4 OpenAI API Key 
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") 
-
-#Inferenec function
-def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):  
-
-    headers = {
-    "Content-Type": "application/json",
-    "Authorization": f"Bearer {OPENAI_API_KEY}"
-    }
-    print(f"system message is ^^ {system_msg}")
-    if system_msg.strip() == '':
-        initial_message = [{"role": "user", "content": f"{inputs}"},]
-        multi_turn_message = []
-    else:
-        initial_message= [{"role": "system", "content": system_msg},
-                   {"role": "user", "content": f"{inputs}"},]
-        multi_turn_message = [{"role": "system", "content": system_msg},]
-        
-    if chat_counter == 0 :
-        payload = {
-        "model": "gpt-3.5-turbo",
-        "messages": initial_message , 
-        "temperature" : 1.0,
-        "top_p":1.0,
-        "n" : 1,
-        "stream": True,
-        "presence_penalty":0,
-        "frequency_penalty":0,
-        }
-        print(f"chat_counter - {chat_counter}")
-    else: #if chat_counter != 0 :
-        messages=multi_turn_message # Of the type of - [{"role": "system", "content": system_msg},]
-        for data in chatbot:
-          user = {}
-          user["role"] = "user" 
-          user["content"] = data[0] 
-          assistant = {}
-          assistant["role"] = "assistant" 
-          assistant["content"] = data[1]
-          messages.append(user)
-          messages.append(assistant)
-        temp = {}
-        temp["role"] = "user" 
-        temp["content"] = inputs
-        messages.append(temp)
-        #messages
-        payload = {
-        "model": "gpt-3.5-turbo",
-        "messages": messages, # Of the type of [{"role": "user", "content": f"{inputs}"}],
-        "temperature" : temperature, #1.0,
-        "top_p": top_p, #1.0,
-        "n" : 1,
-        "stream": True,
-        "presence_penalty":0,
-        "frequency_penalty":0,}
-
-    chat_counter+=1
-
-    history.append(inputs)
-    print(f"Logging : payload is - {payload}")
-    # make a POST request to the API endpoint using the requests.post method, passing in stream=True
-    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
-    print(f"Logging : response code - {response}")
-    token_counter = 0 
-    partial_words = "" 
-
-    counter=0
-    for chunk in response.iter_lines():
-        #Skipping first chunk
-        if counter == 0:
-          counter+=1
-          continue
-        # check whether each line is non-empty
-        if chunk.decode() :
-          chunk = chunk.decode()
-          # decode each line as response data is in bytes
-          if len(chunk) > 12 and "content" in json.loads(chunk[6:])['choices'][0]['delta']:
-              partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
-              if token_counter == 0:
-                history.append(" " + partial_words)
-              else:
-                history[-1] = partial_words
-              chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
-              token_counter+=1
-              yield chat, history, chat_counter, response  # resembles {chatbot: chat, state: history}  
-                   
-#Resetting to blank
-def reset_textbox():
-    return gr.update(value='')
-
-#to set a component as visible=False
-def set_visible_false():
-    return gr.update(visible=False)
-
-#to set a component as visible=True
-def set_visible_true():
-    return gr.update(visible=True)
-
-title = """<h1 align="center">🔍 Swarm Intelligence Agents 🐜🔎</h1>"""
-
-#display message for themes feature
-theme_addon_msg = """<center>🌟 he swarm of agents combines a huge number of parallel agents divided into roles, including examiners, QA, evaluators, managers, analytics, and googlers. 
-<br>🏆The agents use smart task decomposition and optimization processes to ensure accurate and efficient research on any topic.🎨</center>
-"""
-
-#Using info to add additional information about System message in GPT4
-system_msg_info = """Swarm pre-configured for best practices using whitelists of top internet resources'"""
-
-#Modifying existing Gradio Theme
-theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="green",
-                      text_size=gr.themes.sizes.text_lg)                
-
-with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 520px; overflow: auto;}""",
-                      theme=theme) as demo:
-    gr.HTML(title)
-    gr.HTML("""<h3 align="center">🔥Using a swarm of automated agents, we can perform fast and accurate research on any topic. 🚀🐝. 🎉🥳🎉You don't need to spent tons of hours during reseachy🙌</h1>""")
-    gr.HTML(theme_addon_msg)
-    gr.HTML('''<center><a href="https://huggingface.co/spaces/swarm-agents/swarm-agents?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
-
-    with gr.Column(elem_id = "col_container"):
-        #GPT4 API Key is provided by Huggingface 
-        with gr.Accordion(label="System message:", open=False):
-            system_msg = gr.Textbox(label="Instruct the AI Assistant to set its beaviour", info = system_msg_info, value="")
-            accordion_msg = gr.HTML(value="🚧 To set System message you will have to refresh the app", visible=False)
-        chatbot = gr.Chatbot(label='Swarm Intelligence Search', elem_id="chatbot")
-        inputs = gr.Textbox(placeholder= "Enter your search query here...", label= "Type an input and press Enter")
-        state = gr.State([]) 
-        with gr.Row():
-            with gr.Column(scale=7):
-                b1 = gr.Button().style(full_width=True)
-            with gr.Column(scale=3):
-                server_status_code = gr.Textbox(label="Status code from OpenAI server", )
-    
-        #top_p, temperature
-        with gr.Accordion("Parameters", open=False):
-            top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
-            temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
-            chat_counter = gr.Number(value=0, visible=False, precision=0)
-
-    #Event handling
-    inputs.submit( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],)  #openai_api_key
-    b1.click( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],)  #openai_api_key
-    
-    inputs.submit(set_visible_false, [], [system_msg])
-    b1.click(set_visible_false, [], [system_msg])
-    inputs.submit(set_visible_true, [], [accordion_msg])
-    b1.click(set_visible_true, [], [accordion_msg])
-    
-    b1.click(reset_textbox, [], [inputs])
-    inputs.submit(reset_textbox, [], [inputs])
-        
-demo.queue(max_size=99, concurrency_count=20).launch(debug=True)

spaces/Cecil8352/vits-models/monotonic_align/core.py

@@ -1,36 +0,0 @@
-import numba
-
-
-@numba.jit(numba.void(numba.int32[:, :, ::1], numba.float32[:, :, ::1], numba.int32[::1], numba.int32[::1]),
-           nopython=True, nogil=True)
-def maximum_path_jit(paths, values, t_ys, t_xs):
-    b = paths.shape[0]
-    max_neg_val = -1e9
-    for i in range(int(b)):
-        path = paths[i]
-        value = values[i]
-        t_y = t_ys[i]
-        t_x = t_xs[i]
-
-        v_prev = v_cur = 0.0
-        index = t_x - 1
-
-        for y in range(t_y):
-            for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
-                if x == y:
-                    v_cur = max_neg_val
-                else:
-                    v_cur = value[y - 1, x]
-                if x == 0:
-                    if y == 0:
-                        v_prev = 0.
-                    else:
-                        v_prev = max_neg_val
-                else:
-                    v_prev = value[y - 1, x - 1]
-                value[y, x] += max(v_prev, v_cur)
-
-        for y in range(t_y - 1, -1, -1):
-            path[y, index] = 1
-            if index != 0 and (index == y or value[y - 1, index] < value[y - 1, index - 1]):
-                index = index - 1

spaces/Cicooo/vits-uma-genshin-honkai/text/__init__.py

@@ -1,57 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-from text import cleaners
-from text.symbols import symbols
-
-
-# Mappings from symbol to numeric ID and vice versa:
-_symbol_to_id = {s: i for i, s in enumerate(symbols)}
-_id_to_symbol = {i: s for i, s in enumerate(symbols)}
-
-
-def text_to_sequence(text, symbols, cleaner_names):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-      cleaner_names: names of the cleaner functions to run the text through
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  _symbol_to_id = {s: i for i, s in enumerate(symbols)}
-  sequence = []
-
-  clean_text = _clean_text(text, cleaner_names)
-  for symbol in clean_text:
-    if symbol not in _symbol_to_id.keys():
-      continue
-    symbol_id = _symbol_to_id[symbol]
-    sequence += [symbol_id]
-  return sequence, clean_text
-
-
-def cleaned_text_to_sequence(cleaned_text):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  sequence = [_symbol_to_id[symbol] for symbol in cleaned_text if symbol in _symbol_to_id.keys()]
-  return sequence
-
-
-def sequence_to_text(sequence):
-  '''Converts a sequence of IDs back to a string'''
-  result = ''
-  for symbol_id in sequence:
-    s = _id_to_symbol[symbol_id]
-    result += s
-  return result
-
-
-def _clean_text(text, cleaner_names):
-  for name in cleaner_names:
-    cleaner = getattr(cleaners, name)
-    if not cleaner:
-      raise Exception('Unknown cleaner: %s' % name)
-    text = cleaner(text)
-  return text

spaces/CikeyQI/Yunzai/Dockerfile

@@ -1,38 +0,0 @@
-# 使用基于 Node.js 18 的镜像
-FROM node:18
-
-# 安装 Redis
-RUN apt-get update && apt-get install -y redis-server
-
-# 安装 Chromium
-RUN apt install chromium -y
-
-# 将工作目录设置为 app 目录
-WORKDIR /app
-
-# 将项目文件复制到容器中
-COPY ./Yunzai /app
-COPY ./application.yaml /app
-
-# 安装插件
-RUN git clone --depth 1 https://github.com/TimeRainStarSky/Yunzai-genshin plugins/genshin
-RUN git clone --depth 1 https://github.com/yoimiya-kokomi/miao-plugin plugins/miao-plugin
-RUN git clone --depth 1 https://github.com/TimeRainStarSky/TRSS-Plugin plugins/TRSS-Plugin
-RUN git clone --depth 1 https://github.com/ap-plugin/mj-plugin.git plugins/mj-plugin
-RUN git clone --depth 1 https://github.com/ap-plugin/ap-plugin.git plugins/ap-plugin
-RUN git clone --depth 1 https://github.com/Ctrlcvs/xiaoyao-cvs-plugin.git plugins/xiaoyao-cvs-plugin/
-RUN git clone --depth=1 https://github.com/yeyang52/yenai-plugin.git plugins/yenai-plugin
-RUN git clone --depth=1 https://github.com/guoba-yunzai/guoba-plugin.git plugins/Guoba-Plugin
-
-# 拷贝 Guoba 配置文件
-COPY ./application.yaml ./plugins/Guoba-Plugin/config/
-
-# 给予权限
-RUN chmod -R 777 /app
-
-# 安装依赖
-RUN npm install -g pnpm
-RUN pnpm install
-
-# 启动应用程序
-CMD ["node", "app.js"]

spaces/Clebersla/RVC_V2_Huggingface_Version/lib/infer_pack/transforms.py

@@ -1,209 +0,0 @@
-import torch
-from torch.nn import functional as F
-
-import numpy as np
-
-
-DEFAULT_MIN_BIN_WIDTH = 1e-3
-DEFAULT_MIN_BIN_HEIGHT = 1e-3
-DEFAULT_MIN_DERIVATIVE = 1e-3
-
-
-def piecewise_rational_quadratic_transform(
-    inputs,
-    unnormalized_widths,
-    unnormalized_heights,
-    unnormalized_derivatives,
-    inverse=False,
-    tails=None,
-    tail_bound=1.0,
-    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
-    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
-    min_derivative=DEFAULT_MIN_DERIVATIVE,
-):
-    if tails is None:
-        spline_fn = rational_quadratic_spline
-        spline_kwargs = {}
-    else:
-        spline_fn = unconstrained_rational_quadratic_spline
-        spline_kwargs = {"tails": tails, "tail_bound": tail_bound}
-
-    outputs, logabsdet = spline_fn(
-        inputs=inputs,
-        unnormalized_widths=unnormalized_widths,
-        unnormalized_heights=unnormalized_heights,
-        unnormalized_derivatives=unnormalized_derivatives,
-        inverse=inverse,
-        min_bin_width=min_bin_width,
-        min_bin_height=min_bin_height,
-        min_derivative=min_derivative,
-        **spline_kwargs
-    )
-    return outputs, logabsdet
-
-
-def searchsorted(bin_locations, inputs, eps=1e-6):
-    bin_locations[..., -1] += eps
-    return torch.sum(inputs[..., None] >= bin_locations, dim=-1) - 1
-
-
-def unconstrained_rational_quadratic_spline(
-    inputs,
-    unnormalized_widths,
-    unnormalized_heights,
-    unnormalized_derivatives,
-    inverse=False,
-    tails="linear",
-    tail_bound=1.0,
-    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
-    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
-    min_derivative=DEFAULT_MIN_DERIVATIVE,
-):
-    inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
-    outside_interval_mask = ~inside_interval_mask
-
-    outputs = torch.zeros_like(inputs)
-    logabsdet = torch.zeros_like(inputs)
-
-    if tails == "linear":
-        unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
-        constant = np.log(np.exp(1 - min_derivative) - 1)
-        unnormalized_derivatives[..., 0] = constant
-        unnormalized_derivatives[..., -1] = constant
-
-        outputs[outside_interval_mask] = inputs[outside_interval_mask]
-        logabsdet[outside_interval_mask] = 0
-    else:
-        raise RuntimeError("{} tails are not implemented.".format(tails))
-
-    (
-        outputs[inside_interval_mask],
-        logabsdet[inside_interval_mask],
-    ) = rational_quadratic_spline(
-        inputs=inputs[inside_interval_mask],
-        unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
-        unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
-        unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
-        inverse=inverse,
-        left=-tail_bound,
-        right=tail_bound,
-        bottom=-tail_bound,
-        top=tail_bound,
-        min_bin_width=min_bin_width,
-        min_bin_height=min_bin_height,
-        min_derivative=min_derivative,
-    )
-
-    return outputs, logabsdet
-
-
-def rational_quadratic_spline(
-    inputs,
-    unnormalized_widths,
-    unnormalized_heights,
-    unnormalized_derivatives,
-    inverse=False,
-    left=0.0,
-    right=1.0,
-    bottom=0.0,
-    top=1.0,
-    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
-    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
-    min_derivative=DEFAULT_MIN_DERIVATIVE,
-):
-    if torch.min(inputs) < left or torch.max(inputs) > right:
-        raise ValueError("Input to a transform is not within its domain")
-
-    num_bins = unnormalized_widths.shape[-1]
-
-    if min_bin_width * num_bins > 1.0:
-        raise ValueError("Minimal bin width too large for the number of bins")
-    if min_bin_height * num_bins > 1.0:
-        raise ValueError("Minimal bin height too large for the number of bins")
-
-    widths = F.softmax(unnormalized_widths, dim=-1)
-    widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
-    cumwidths = torch.cumsum(widths, dim=-1)
-    cumwidths = F.pad(cumwidths, pad=(1, 0), mode="constant", value=0.0)
-    cumwidths = (right - left) * cumwidths + left
-    cumwidths[..., 0] = left
-    cumwidths[..., -1] = right
-    widths = cumwidths[..., 1:] - cumwidths[..., :-1]
-
-    derivatives = min_derivative + F.softplus(unnormalized_derivatives)
-
-    heights = F.softmax(unnormalized_heights, dim=-1)
-    heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
-    cumheights = torch.cumsum(heights, dim=-1)
-    cumheights = F.pad(cumheights, pad=(1, 0), mode="constant", value=0.0)
-    cumheights = (top - bottom) * cumheights + bottom
-    cumheights[..., 0] = bottom
-    cumheights[..., -1] = top
-    heights = cumheights[..., 1:] - cumheights[..., :-1]
-
-    if inverse:
-        bin_idx = searchsorted(cumheights, inputs)[..., None]
-    else:
-        bin_idx = searchsorted(cumwidths, inputs)[..., None]
-
-    input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
-    input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
-
-    input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
-    delta = heights / widths
-    input_delta = delta.gather(-1, bin_idx)[..., 0]
-
-    input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
-    input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
-
-    input_heights = heights.gather(-1, bin_idx)[..., 0]
-
-    if inverse:
-        a = (inputs - input_cumheights) * (
-            input_derivatives + input_derivatives_plus_one - 2 * input_delta
-        ) + input_heights * (input_delta - input_derivatives)
-        b = input_heights * input_derivatives - (inputs - input_cumheights) * (
-            input_derivatives + input_derivatives_plus_one - 2 * input_delta
-        )
-        c = -input_delta * (inputs - input_cumheights)
-
-        discriminant = b.pow(2) - 4 * a * c
-        assert (discriminant >= 0).all()
-
-        root = (2 * c) / (-b - torch.sqrt(discriminant))
-        outputs = root * input_bin_widths + input_cumwidths
-
-        theta_one_minus_theta = root * (1 - root)
-        denominator = input_delta + (
-            (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
-            * theta_one_minus_theta
-        )
-        derivative_numerator = input_delta.pow(2) * (
-            input_derivatives_plus_one * root.pow(2)
-            + 2 * input_delta * theta_one_minus_theta
-            + input_derivatives * (1 - root).pow(2)
-        )
-        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
-
-        return outputs, -logabsdet
-    else:
-        theta = (inputs - input_cumwidths) / input_bin_widths
-        theta_one_minus_theta = theta * (1 - theta)
-
-        numerator = input_heights * (
-            input_delta * theta.pow(2) + input_derivatives * theta_one_minus_theta
-        )
-        denominator = input_delta + (
-            (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
-            * theta_one_minus_theta
-        )
-        outputs = input_cumheights + numerator / denominator
-
-        derivative_numerator = input_delta.pow(2) * (
-            input_derivatives_plus_one * theta.pow(2)
-            + 2 * input_delta * theta_one_minus_theta
-            + input_derivatives * (1 - theta).pow(2)
-        )
-        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
-
-        return outputs, logabsdet

spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/data/datasets/evaluation/word/util/thread_.py

@@ -1,62 +0,0 @@
-import threading
-from threading import Thread
-
-def get_current_thread():
-    return threading.current_thread()
-
-def get_current_thread_name():
-    return get_current_thread().getName()
-    
-def is_alive(t):
-    return t.is_alive()
-    
-def create_and_start(name, target, daemon = True):
-    t = Thread(target= target)
-    t.daemon = True
-    t.setName(name)
-    t.start()
-    return t
-
-
-  
-class ThreadPool(object):
-    def __init__(self, capacity = 10):
-        import threadpool
-        self.num_threads = capacity
-        self.pool = threadpool.ThreadPool(10)
-        
-    def add(self, fn, args):
-        import threadpool
-        if type(args) == list:
-            args = [(args, None)]
-        elif type(args) == dict:
-            args = [(None, args)]
-        else:
-            raise ValueError, "Unsuported args,", type(args)
-        request = threadpool.makeRequests(fn, args)[0]
-        self.pool.putRequest(request, block = False)
-        self.pool.poll()
-    
-    def join(self):
-        self.pool.wait()
-        
-class ProcessPool(object):
-    """
-    Remember that function in function is not supported by multiprocessing.
-    """
-    def __init__(self, capacity = 8):
-        from multiprocessing import Pool
-
-        self.capacity = capacity
-        self.pool = Pool(capacity)
-    
-    def add(self, fn, args):
-        self.pool.apply_async(fn, args)
-#         self.pool.poll()
-#         self.pool.poll
-        
-    def join(self):
-        self.pool.close()
-        self.pool.join()
-        
-