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avoid duplicate detections and loadings
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parent
0d18a7c2df
commit
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@ -19,7 +19,7 @@ from deepface.modules import (
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recognition,
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recognition,
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demography,
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demography,
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detection,
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detection,
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realtime,
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streaming,
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)
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)
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from deepface import __version__
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from deepface import __version__
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@ -409,7 +409,7 @@ def stream(
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time_threshold = max(time_threshold, 1)
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time_threshold = max(time_threshold, 1)
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frame_threshold = max(frame_threshold, 1)
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frame_threshold = max(frame_threshold, 1)
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realtime.analysis(
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streaming.analysis(
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db_path=db_path,
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db_path=db_path,
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model_name=model_name,
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model_name=model_name,
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detector_backend=detector_backend,
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detector_backend=detector_backend,
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@ -176,7 +176,7 @@ def analysis(
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demographies = DeepFace.analyze(
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demographies = DeepFace.analyze(
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img_path=custom_face,
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img_path=custom_face,
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detector_backend=detector_backend,
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detector_backend="skip",
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enforce_detection=False,
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enforce_detection=False,
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silent=True,
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silent=True,
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)
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)
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@ -411,7 +411,7 @@ def analysis(
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img_path=custom_face,
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img_path=custom_face,
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db_path=db_path,
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db_path=db_path,
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model_name=model_name,
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model_name=model_name,
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detector_backend=detector_backend,
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detector_backend="skip",
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distance_metric=distance_metric,
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distance_metric=distance_metric,
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enforce_detection=False,
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enforce_detection=False,
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silent=True,
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silent=True,
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@ -429,7 +429,7 @@ def analysis(
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display_img = cv2.imread(label)
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display_img = cv2.imread(label)
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# to use extracted face
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# to use extracted face
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source_objs = DeepFace.extract_faces(
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source_objs = DeepFace.extract_faces(
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img_path=label,
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img_path=display_img,
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target_size=(pivot_img_size, pivot_img_size),
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target_size=(pivot_img_size, pivot_img_size),
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detector_backend=detector_backend,
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detector_backend=detector_backend,
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enforce_detection=False,
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enforce_detection=False,
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