AiDA_Python/app/service/design_fast/pipeline/scale.py

import math

import cv2


class Scaling:
    def __call__(self, result):
        if result['keypoint'] in ['waistband', 'shoulder', 'head_point']:
            # milvus_db_keypoint_cache
            distance_clo = math.sqrt(
                (int(result['clothes_keypoint'][result['keypoint'] + '_left'][0]) - int(result['clothes_keypoint'][result['keypoint'] + '_right'][0])) ** 2
                +
                (int(result['clothes_keypoint'][result['keypoint'] + '_left'][1]) - int(result['clothes_keypoint'][result['keypoint'] + '_right'][1])) ** 2
            )

            distance_bdy = math.sqrt(
                (int(result['body_point_test'][result['keypoint'] + '_left'][0])
                 -
                 int(result['body_point_test'][result['keypoint'] + '_right'][0])) ** 2 + 1
            )

            if distance_clo == 0:
                result['scale'] = 1
            else:
                result['scale'] = distance_bdy / distance_clo
        elif result['keypoint'] == 'toe':
            distance_bdy = math.sqrt(
                (int(result['body_point_test']['foot_length'][0]) - int(result['body_point_test']['foot_length'][2])) ** 2
                +
                (int(result['body_point_test']['foot_length'][1]) - int(result['body_point_test']['foot_length'][3])) ** 2
            )

            Blur = cv2.GaussianBlur(result['gray'], (3, 3), 0)
            Edge = cv2.Canny(Blur, 10, 200)
            Edge = cv2.dilate(Edge, None)
            Edge = cv2.erode(Edge, None)
            Contour, _ = cv2.findContours(Edge, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
            Contours = sorted(Contour, key=cv2.contourArea, reverse=True)

            Max_contour = Contours[0]
            x, y, w, h = cv2.boundingRect(Max_contour)
            width = w
            distance_clo = width
            result['scale'] = distance_bdy / distance_clo
        elif result['keypoint'] == 'hand_point':
            result['scale'] = result['scale_bag']
        elif result['keypoint'] == 'ear_point':
            result['scale'] = result['scale_earrings']
        elif result['keypoint'] == 'accessories':
            # 由于没有识别配饰keypoint的模型  所以统一将配饰的两个关键点设定为 (0,0) (0,img.width)
            # 模特的关键点设定为(0,0) (0,320/2) 距离比例简写为 160 / img.width
            distance_clo = result['img_shape'][1]
            distance_bdy = 320 / 2

            if distance_clo == 0:
                result['scale'] = 1
            else:
                result['scale'] = distance_bdy / distance_clo
        else:
            result['scale'] = 1
        return result