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resolving issue 1098
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@ -93,6 +93,7 @@ def verify(
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model: FacialRecognition = modeling.build_model(model_name)
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dims = model.output_shape
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# extract faces from img1
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if isinstance(img1_path, list):
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# given image is already pre-calculated embedding
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if not all(isinstance(dim, float) for dim in img1_path):
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@ -115,16 +116,20 @@ def verify(
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img1_embeddings = [img1_path]
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img1_facial_areas = [None]
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else:
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img1_embeddings, img1_facial_areas = __extract_faces_and_embeddings(
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img_path=img1_path,
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model_name=model_name,
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detector_backend=detector_backend,
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enforce_detection=enforce_detection,
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align=align,
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expand_percentage=expand_percentage,
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normalization=normalization,
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)
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try:
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img1_embeddings, img1_facial_areas = __extract_faces_and_embeddings(
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img_path=img1_path,
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model_name=model_name,
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detector_backend=detector_backend,
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enforce_detection=enforce_detection,
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align=align,
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expand_percentage=expand_percentage,
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normalization=normalization,
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)
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except ValueError as err:
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raise ValueError("Exception while processing img1_path") from err
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# extract faces from img2
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if isinstance(img2_path, list):
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# given image is already pre-calculated embedding
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if not all(isinstance(dim, float) for dim in img2_path):
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@ -147,15 +152,18 @@ def verify(
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img2_embeddings = [img2_path]
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img2_facial_areas = [None]
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else:
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img2_embeddings, img2_facial_areas = __extract_faces_and_embeddings(
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img_path=img2_path,
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model_name=model_name,
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detector_backend=detector_backend,
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enforce_detection=enforce_detection,
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align=align,
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expand_percentage=expand_percentage,
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normalization=normalization,
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)
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try:
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img2_embeddings, img2_facial_areas = __extract_faces_and_embeddings(
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img_path=img2_path,
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model_name=model_name,
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detector_backend=detector_backend,
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enforce_detection=enforce_detection,
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align=align,
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expand_percentage=expand_percentage,
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normalization=normalization,
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)
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except ValueError as err:
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raise ValueError("Exception while processing img2_path") from err
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no_facial_area = {
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"x": None,
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@ -218,18 +226,15 @@ def __extract_faces_and_embeddings(
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model: FacialRecognition = modeling.build_model(model_name)
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target_size = model.input_shape
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try:
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img_objs = detection.extract_faces(
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img_path=img_path,
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target_size=target_size,
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detector_backend=detector_backend,
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grayscale=False,
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enforce_detection=enforce_detection,
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align=align,
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expand_percentage=expand_percentage,
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)
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except ValueError as err:
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raise ValueError("Exception while processing img1_path") from err
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img_objs = detection.extract_faces(
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img_path=img_path,
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target_size=target_size,
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detector_backend=detector_backend,
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grayscale=False,
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enforce_detection=enforce_detection,
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align=align,
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expand_percentage=expand_percentage,
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)
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# find embeddings for each face
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for img_obj in img_objs:
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