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common confidence scales
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@ -90,6 +90,7 @@ class DlibClient(Detector):
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left_eye = (shape.part(2).x, shape.part(2).y)
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right_eye = (shape.part(0).x, shape.part(0).y)
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# never saw confidence higher than +3.5 github.com/davisking/dlib/issues/761
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confidence = scores[idx]
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facial_area = FacialAreaRegion(
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@ -99,7 +100,7 @@ class DlibClient(Detector):
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h=h,
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left_eye=left_eye,
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right_eye=right_eye,
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confidence=confidence,
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confidence=min(max(0, confidence), 1.0),
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)
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resp.append(facial_area)
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@ -60,7 +60,7 @@ class OpenCvClient(Detector):
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h=h,
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left_eye=left_eye,
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right_eye=right_eye,
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confidence=confidence,
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confidence=(100 - confidence) / 100,
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)
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resp.append(facial_area)
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@ -31,6 +31,7 @@ detector_backends = [
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"yolov8",
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]
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# verification
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for model_name in model_names:
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obj = DeepFace.verify(
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@ -46,6 +47,7 @@ for model_name in model_names:
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embedding = embedding_obj["embedding"]
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logger.info(f"{model_name} produced {len(embedding)}D vector")
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# find
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dfs = DeepFace.find(
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img_path="dataset/img1.jpg", db_path="dataset", model_name="Facenet", detector_backend="mtcnn"
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@ -54,6 +56,7 @@ for df in dfs:
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logger.info(df)
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# img_paths = ["dataset/img11.jpg", "dataset/img11_reflection.jpg", "dataset/couple.jpg"]
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img_paths = ["dataset/img11.jpg"]
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for img_path in img_paths:
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@ -84,6 +87,8 @@ for img_path in img_paths:
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assert isinstance(face_obj["facial_area"]["right_eye"][1], int)
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assert isinstance(face_obj["confidence"], float)
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assert face_obj["confidence"] <= 1
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plt.imshow(face)
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plt.axis("off")
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plt.show()
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