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These models are trained on deepghs/animefacedetection and open-sourced real photos datasets.
Fonte do modelo
Descrição da fonte
These models are trained on deepghs/anime_face_detection and open-sourced real photos datasets.
So both anime and photos are supported.
Use this with dghs-realutils
pip install dghs-realutils
Fontes
1 fonteVerificado 9 de set.
Artefatos de modelo
20 artefatosTrechos de fonte
2 trechosfrom realutils.detect import detect_faces
print(detect_faces('yolo/solo.jpg'))
# [((157, 94, 252, 208), 'face', 0.8836570382118225)]
print(detect_faces('yolo/2girls.jpg'))
# [((718, 154, 1110, 728), 'face', 0.8841166496276855), ((157, 275, 519, 715), 'face', 0.8668240904808044)]
print(detect_faces('yolo/3+cosplay.jpg'))
# [((349, 227, 413, 305), 'face', 0.8543888330459595), ((383, 61, 432, 117), 'face', 0.8080574870109558), ((194, 107, 245, 162), 'face', 0.8035706877708435)]
print(detect_faces('yolo/multiple.jpg'))
# [((1070, 728, 1259, 985), 'face', 0.8765808939933777), ((548, 286, 760, 558), 'face', 0.8693087697029114), ((896, 315, 1067, 520), 'face', 0.8671919107437134), ((1198, 220, 1342, 406), 'face', 0.8485829830169678), ((1376, 526, 1546, 719), 'face', 0.8469308018684387)]
For more information, see documentation of realutils.
| Model | Type | FLOPS | Params | F1 Score | Threshold | precision(B) | recall(B) | mAP50(B) | mAP50-95(B) | F1 Plot | Confusion | Labels |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| face_detect_v0_s_yv12 | yolo | 21.5G | 9.25M | 0.74 | 0.272 | 0.86931 | 0.6404 | 0.73074 | 0.42652 | plot | confusion | face |
| face_detect_v0_n_yv12 | yolo | 6.48G | 2.57M | 0.7 | 0.258 | 0.85246 | 0.59089 |
face_detect_v0_l/model.onnx
onnx · 167 MB · SHA-256 7a384cfd1b5d…b27f · Hugging Face
--- datasets: - deepghs/real_face_detection - deepghs/anime_face_detection pipeline_tag: object-detection library_name: dghs-imgutils tags: - art - anime - photo - face --- These models are trained on [deepghs/anime_face_detection](https://huggingface.co/deepghs/anime_face_detection) and open-sourced real photos datasets. So both anime and photos are supported. Use this with `dghs-realutils` ```shell pip install dghs-realutils ``` ```python from realutils.detect import detect_faces print(detect_faces('yolo/solo.jpg')) # [((157, 94, 252, 208), 'face', 0.8836570382118225)] print(detect_faces('yolo/2girls.jpg')) # [((718, 154, 1110, 728), 'face', 0.8841166496276855), ((157, 275, 519, 715), 'face', 0.8668240904808044)] print(detect_faces('yolo/3+cosplay.jpg')) # [((349, 227, 413, 305), 'face', 0.8543888330459595), ((383, 61, 432, 117), 'face', 0.8080574870109558), ((194, 107, 245, 162), 'face', 0.8035706877708435)] print(detect_faces('yolo/multiple.jpg')) # [((1070, 728, 1259, 985), 'face', 0.8765808939933777), ((548, 286, 760, 558), 'face', 0.8693087697029114), ((896, 315, 1067, 520), 'face', 0.8671919107437134), ((1198, 220, 1342, 406), 'face', 0.8485829830169678), ((1376, 526, 1546, 719), 'face', 0.8469308018684387)] ``` For more information, see [documentation of realutils](https://dghs-realutils.deepghs.org/main/api_doc/detect/face.html). | Model | Type | FLOPS | Params | F1 Score | Threshold | precision(B) | recall(B) | mAP50(B) | mAP50-95(B) | F1 Plot | Confusion | Labels | |:---------------------:|:------:|:-------:|:--------:|:----------:|:-----------:|:--------------:|:-----------:|:----------:|:-------------:|:-------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------:|:--------:| | face_detect_v0_s_yv12 | yolo | 21.5G | 9.25M | 0.74 | 0.272 | 0.86931 | 0.6404 | 0.73074 | 0.42652 | [plot](https://huggingface.co/deepghs/real_face_detection/blob/main/face_detect_v0_s_yv12/F1_curve.png) | [confusion](https://huggingface.co/deepghs/real_face_detection/blob/main/face_detect_v0_s_yv12/confusion_matrix_normalized.png) | `face` | | face_detect_v0_n_yv12 | yolo | 6.48G | 2.57M | 0.7 | 0.258 | 0.85246 | 0.59089 | 0.6793 | 0.39182 | [plot](https://huggingface.co/deepghs/real_face...
Source context: 0 downloads · 0 likes · Pipeline object-detection · Library dghs-imgutils · Repo Library-Mutsumi/real_face_detection
| 0.6793 |
| 0.39182 |
| plot |
| confusion |
face |
| face_detect_v0_l_yv11 | yolo | 87.3G | 25.3M | 0.77 | 0.291 | 0.88458 | 0.67474 | 0.76666 | 0.45722 | plot | confusion | face |
| face_detect_v0_m_yv11 | yolo | 68.2G | 20.1M | 0.76 | 0.262 | 0.87947 | 0.67315 | 0.76073 | 0.45288 | plot | confusion | face |
| face_detect_v0_s_yv11 | yolo | 21.5G | 9.43M | 0.73 | 0.271 | 0.87001 | 0.63572 | 0.72683 | 0.42706 | plot | confusion | face |
| face_detect_v0_n_yv11 | yolo | 6.44G | 2.59M | 0.7 | 0.263 | 0.86044 | 0.58577 | 0.67641 | 0.38975 | plot | confusion | face |
| face_detect_v0_l | yolo | 165G | 43.6M | 0.76 | 0.277 | 0.87894 | 0.67335 | 0.76313 | 0.4532 | plot | confusion | face |
| face_detect_v0_m | yolo | 79.1G | 25.9M | 0.75 | 0.277 | 0.87687 | 0.66265 | 0.75114 | 0.44262 | plot | confusion | face |
| face_detect_v0_s | yolo | 28.6G | 11.1M | 0.73 | 0.282 | 0.86932 | 0.63557 | 0.72494 | 0.42219 | plot | confusion | face |
| face_detect_v0_n | yolo | 8.19G | 3.01M | 0.7 | 0.257 | 0.85337 | 0.58877 | 0.67471 | 0.38692 | plot | confusion | face |