Object Detection
ultralytics
ONNX
yolo
yolo11
anime
foot-detection
adetailer
comfyui
Eval Results (legacy)
Instructions to use Claquasse/foot_anime_yolo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Claquasse/foot_anime_yolo with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("Claquasse/foot_anime_yolo") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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license: agpl-3.0
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library_name: ultralytics
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pipeline_tag: object-detection
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tags:
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- yolo
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- yolo11
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- foot-detection
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- adetailer
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- comfyui
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---
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# Anime foot detector (YOLO11m)
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license: agpl-3.0
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library_name: ultralytics
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pipeline_tag: object-detection
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base_model: Ultralytics/YOLO11
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datasets:
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- deepghs/danbooru2024
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metrics:
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- mAP
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tags:
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- yolo
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- yolo11
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- foot-detection
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- adetailer
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- comfyui
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model-index:
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- name: foot_anime_yolo11m_v3
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results:
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- task:
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type: object-detection
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dataset:
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name: Anime foot held-out (generated, 100 images / 185 feet)
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type: custom
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metrics:
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- type: mAP50
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value: 0.81
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name: mAP@50
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- type: mAP50-95
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value: 0.59
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name: mAP@50-95
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---
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# Anime foot detector (YOLO11m)
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