54 lines
1.4 KiB
Markdown
54 lines
1.4 KiB
Markdown
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ref: https://github.com/serengil/deepface
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# model store
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model checkpoint 放在了 `C:\Users\User\.deepface\weights`
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# installation
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```
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$ pip install deepface
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```
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# Usage:
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```
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(deepface_v2) PS path/to/workspace> python
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Python 3.7.16 (default, Jan 17 2023, 16:06:28) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
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Type "help", "copyright", "credits" or "license" for more information.
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>>> from deepface import DeepFace
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```
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# Model introduce
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```
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Deepface is a hybrid face recognition package. It currently wraps many state-of-the-art face recognition models:
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model_name Declared LFW Score
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VGG-Face 98.9%
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Facenet 99.2%
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Facenet512 99.6% drop
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OpenFace 92.9%
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DeepID 97.4%
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Dlib 99.3%
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SFace 99.5%
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ArcFace 99.5% 阈值调整为1.00 **
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GhostFaceNet 99.7% **
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Human-beings 97.5%
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The default configuration uses VGG-Face model.
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```
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```
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backends = {
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"opencv": OpenCv.OpenCvClient,
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"mtcnn": MtCnn.MtCnnClient,
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"ssd": Ssd.SsdClient,
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"dlib": Dlib.DlibClient,
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"retinaface": RetinaFace.RetinaFaceClient,
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"mediapipe": MediaPipe.MediaPipeClient,
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"yolov8": Yolo.YoloClient,
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"yunet": YuNet.YuNetClient,
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"fastmtcnn": FastMtCnn.FastMtCnnClient,
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}
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```
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```
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distance_metric = ['euclidean_l2','cosine','euclidean']
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author: Euclidean L2 form seems to be more stable than cosine and regular Euclidean distance based on experiments.
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```
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