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target_size in detectFace
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@ -800,7 +800,7 @@ def stream(db_path = '', model_name ='VGG-Face', detector_backend = 'opencv', di
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realtime.analysis(db_path, model_name, detector_backend, distance_metric, enable_face_analysis
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, source = source, time_threshold = time_threshold, frame_threshold = frame_threshold)
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def detectFace(img_path, detector_backend = 'opencv', enforce_detection = True, align = True):
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def detectFace(img_path, target_size = (224, 224), detector_backend = 'opencv', enforce_detection = True, align = True):
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"""
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This function applies pre-processing stages of a face recognition pipeline including detection and alignment
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@ -814,7 +814,7 @@ def detectFace(img_path, detector_backend = 'opencv', enforce_detection = True,
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deteced and aligned face in numpy format
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"""
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img = functions.preprocess_face(img = img_path, detector_backend = detector_backend
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img = functions.preprocess_face(img = img_path, target_size = target_size, detector_backend = detector_backend
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, enforce_detection = enforce_detection, align = align)[0] #preprocess_face returns (1, 224, 224, 3)
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return img[:, :, ::-1] #bgr to rgb
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