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@@ -46,7 +46,7 @@ dataset_summary: '
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  # Note: other available arguments include ''max_samples'', etc
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- dataset = fouh.load_from_hub("dgural/Thermal-Person-Detector")
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  # Launch the App
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  # Dataset Card for ThermalPersonDetector
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- <!-- Provide a quick summary of the dataset. -->
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  ### Dataset Description
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- <!-- Provide a longer summary of what this dataset is. -->
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- - **Curated by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Language(s) (NLP):** en
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- - **License:** [More Information Needed]
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- ### Dataset Sources [optional]
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- <!-- Provide the basic links for the dataset. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the dataset is intended to be used. -->
 
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- ### Direct Use
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- <!-- This section describes suitable use cases for the dataset. -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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- [More Information Needed]
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  ## Dataset Structure
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- <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- [More Information Needed]
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- ## Dataset Creation
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- ### Curation Rationale
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- <!-- Motivation for the creation of this dataset. -->
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  [More Information Needed]
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  ### Source Data
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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- #### Data Collection and Processing
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- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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- [More Information Needed]
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  #### Who are the source data producers?
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- <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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- [More Information Needed]
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- ### Annotations [optional]
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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- #### Annotation process
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- <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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  #### Who are the annotators?
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- <!-- This section describes the people or systems who created the annotations. -->
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- [More Information Needed]
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- #### Personal and Sensitive Information
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- <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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  **BibTeX:**
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- [More Information Needed]
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Dataset Card Authors [optional]
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- ## Dataset Card Contact
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- [More Information Needed]
 
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  # Note: other available arguments include ''max_samples'', etc
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+ dataset = fouh.load_from_hub("Voxel51/Thermal-Person-Detector")
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  # Launch the App
 
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  # Dataset Card for ThermalPersonDetector
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+ A thermal image dataset for detecting people in a scene. The dataset contains only one class `person`
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  ### Dataset Description
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+ Here are a few use cases for this project:
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+ Sports Analytics: The "PersonDetection" model could be used to analyze individual athletes' performances in various sports such as skateboarding, basketball, or soccer, by detecting and tracking the movements of players.
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+ Surveillance Security: It could be utilized in CCTV systems and security cameras. By recognizing people in real-time, it could alert security personnel when unauthorized individuals are detected in restricted areas.
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+ Social Distancing Detection: In light of the Covid-19 pandemic, this model could be used to enforce social distancing measures by tracking the number of people and their relative distances in public spaces like parks, malls, or transportation systems.
 
 
 
 
 
 
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+ Smart Home Management: It can be deployed in smart homes devices to recognize the home occupants and subsequently adapt the environment to their preferences such as lighting, temperature or even play their favorite music upon entry.
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+ Motion Capture and Gaming: In the gaming and animation industry, this model could be used for real-time motion capture, allowing developers to create more realistic and immersive human characters.
 
 
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+ - **Language(s) (NLP):** en
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+ - **License:** CC 4.0
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  ## Dataset Structure
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+ One ground_truth field with a person class
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  [More Information Needed]
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  ### Source Data
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+ [Roboflow Univers](https://universe.roboflow.com/smart2/persondection-61bc2)
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  #### Who are the source data producers?
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+ [SMART2](https://universe.roboflow.com/smart2)
 
 
 
 
 
 
 
 
 
 
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  [More Information Needed]
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  #### Who are the annotators?
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+ SMART2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  **BibTeX:**
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+ @misc{
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+ persondection-61bc2_dataset,
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+ title = { PersonDection Dataset },
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+ type = { Open Source Dataset },
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+ author = { SMART2 },
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+ howpublished = { \url{ https://universe.roboflow.com/smart2/persondection-61bc2 } },
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+ url = { https://universe.roboflow.com/smart2/persondection-61bc2 },
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+ journal = { Roboflow Universe },
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+ publisher = { Roboflow },
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+ year = { 2023 },
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+ month = { may },
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+ note = { visited on 2024-07-19 },
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+ }