62 lines
2.6 KiB
Python
62 lines
2.6 KiB
Python
import math
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import cv2
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class Scaling:
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def __call__(self, result):
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if result['keypoint'] in ['waistband', 'shoulder', 'head_point']:
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# milvus_db_keypoint_cache
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distance_clo = math.sqrt(
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(int(result['clothes_keypoint'][result['keypoint'] + '_left'][0]) - int(result['clothes_keypoint'][result['keypoint'] + '_right'][0])) ** 2
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+
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(int(result['clothes_keypoint'][result['keypoint'] + '_left'][1]) - int(result['clothes_keypoint'][result['keypoint'] + '_right'][1])) ** 2
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)
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distance_bdy = math.sqrt(
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(int(result['body_point_test'][result['keypoint'] + '_left'][0])
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-
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int(result['body_point_test'][result['keypoint'] + '_right'][0])) ** 2 + 1
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)
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if distance_clo == 0:
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result['scale'] = 1
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else:
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result['scale'] = distance_bdy / distance_clo
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elif result['keypoint'] == 'toe':
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distance_bdy = math.sqrt(
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(int(result['body_point_test']['foot_length'][0]) - int(result['body_point_test']['foot_length'][2])) ** 2
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+
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(int(result['body_point_test']['foot_length'][1]) - int(result['body_point_test']['foot_length'][3])) ** 2
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)
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Blur = cv2.GaussianBlur(result['gray'], (3, 3), 0)
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Edge = cv2.Canny(Blur, 10, 200)
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Edge = cv2.dilate(Edge, None)
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Edge = cv2.erode(Edge, None)
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Contour, _ = cv2.findContours(Edge, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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Contours = sorted(Contour, key=cv2.contourArea, reverse=True)
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Max_contour = Contours[0]
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x, y, w, h = cv2.boundingRect(Max_contour)
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width = w
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distance_clo = width
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result['scale'] = distance_bdy / distance_clo
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elif result['keypoint'] == 'hand_point':
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result['scale'] = result['scale_bag']
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elif result['keypoint'] == 'ear_point':
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result['scale'] = result['scale_earrings']
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elif result['keypoint'] == 'others':
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# 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)
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# 模特的关键点设定为(0,0) (0,320/2) 距离比例简写为 160 / img.width
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distance_clo = result['img_shape'][1]
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distance_bdy = 320 / 2
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if distance_clo == 0:
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result['scale'] = 1
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else:
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result['scale'] = distance_bdy / distance_clo
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else:
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result['scale'] = 1
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return result
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