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README.md
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- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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# Dataset Card for
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:** https://
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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10,000 People - Re-ID Data in Surveillance Scenes. The data includes indoor scenes and outdoor scenes. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different shooting angles, different human body orientations and postures, clothing for different seasons. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. The data can be used for re-id and other tasks.
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For more details, please refer to the link: https://
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### Supported Tasks and Leaderboards
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face-detection, computer-vision: The dataset can be used to train a model for face detection.
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- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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# Dataset Card for Nexdata/Re-ID_Data_in_Surveillance_Scenes
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:** https://www.nexdata.ai/datasets/1129?source=Huggingface
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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10,000 People - Re-ID Data in Surveillance Scenes. The data includes indoor scenes and outdoor scenes. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different shooting angles, different human body orientations and postures, clothing for different seasons. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. The data can be used for re-id and other tasks.
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For more details, please refer to the link: https://www.nexdata.ai/datasets/1129?source=Huggingface
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### Supported Tasks and Leaderboards
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face-detection, computer-vision: The dataset can be used to train a model for face detection.
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