def detect_and_align()

in source/containers/face-comparison/recognizer/predictor.py [0:0]

• 46 lines of code
• 6 McCabe index (conditional complexity)

    def detect_and_align(cls, raw_input_image, is_source_image=False, threshold=0.70):
        face_detector, _ = cls.get_model()

        height, width, _ = raw_input_image.shape
        short_size = height if height < width else width
        scale = 1.0 if short_size < 480.0 else 480.0 / short_size

        bbox_list, pts5_list = face_detector.detect(raw_input_image, threshold=threshold, scale=scale)

        if bbox_list.shape[0] == 0:
            return None

        if is_source_image:
            max_face_index = cls.get_largest_face(bbox_list)
            bbox = bbox_list[max_face_index, :]
            pts5 = pts5_list[max_face_index, :]
            aligned_source_face = face_align.norm_crop(raw_input_image, pts5)

            face = Face(
                bbox=[float(bbox[0]), float(bbox[1]), float(bbox[2]), float(bbox[3])],
                aligned_face_img=aligned_source_face,
                confidence=float(bbox[-1]),
                key_points={
                    'eyeLeft': [float(pts5[0][0]), float(pts5[0][1])],
                    'eyeRight': [float(pts5[1][0]), float(pts5[1][1])],
                    'nose': [float(pts5[2][0]), float(pts5[2][1])],
                    'mouthLeft': [float(pts5[3][0]), float(pts5[3][1])],
                    'mouthRight': [float(pts5[4][0]), float(pts5[4][1])],
                }
            )

            return face
        else:
            face_list = list()
            for index in range(len(bbox_list)):
                bbox = bbox_list[index]
                pts5 = pts5_list[index]

                aligned_target_face = face_align.norm_crop(raw_input_image, pts5)

                face = Face(
                    bbox=[float(bbox[0]), float(bbox[1]), float(bbox[2]), float(bbox[3])],
                    aligned_face_img=aligned_target_face,
                    confidence=float(bbox[-1]),
                    key_points={
                        'eyeLeft': [float(pts5[0][0]), float(pts5[0][1])],
                        'eyeRight': [float(pts5[1][0]), float(pts5[1][1])],
                        'nose': [float(pts5[2][0]), float(pts5[2][1])],
                        'mouthLeft': [float(pts5[3][0]), float(pts5[3][1])],
                        'mouthRight': [float(pts5[4][0]), float(pts5[4][1])],
                    }
                )

                face_list.append(face)
            return face_list