80 lines
3.4 KiB
Python
80 lines
3.4 KiB
Python
import cv2
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import numpy as np
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from app.service.design_fast.utils.design_ensemble import get_seg_result
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from app.service.utils.new_oss_client import oss_upload_image
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class BackPerspective:
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def __init__(self, minio_client):
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self.minio_client = minio_client
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def __call__(self, result):
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# 如果sketch为系统图 查看是否有对应的 背后视角图
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if result['path'].split('/')[0] == 'aida-sys-image':
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file_path = result['path'].replace("images", 'images_back', 1)
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if self.is_file_exists(bucket_name='aida-sys-image', file_name=file_path[file_path.find('/') + 1:]):
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result['back_perspective_url'] = file_path
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return result
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else:
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seg_result = get_seg_result("1", result['image'])[0]
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elif result['name'] in ['blouse', 'outwear', 'dress', 'tops']:
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seg_result = result['seg_result']
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else:
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seg_result = get_seg_result("1", result['image'])[0]
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m = self.thicken_contours_and_display(seg_result, thickness=10, color=(0, 0, 0))
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back_sketch = result['image'].copy()
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back_sketch[m > 100] = 255
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# 上传背后视角图
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_, img_encoded = cv2.imencode(".jpg", back_sketch)
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resp = oss_upload_image(self.minio_client, bucket='test', object_name=result['path'], image_bytes=img_encoded.tobytes())
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result['back_perspective_url'] = f"{resp.bucket_name}/{resp.object_name}"
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return result
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def thicken_contours_and_display(self, mask, thickness=10, color=(0, 0, 0)):
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mask = mask.astype(np.uint8) * 255
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# 查找轮廓
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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# 创建一个彩色副本用于绘制轮廓
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mask_color = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
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def thicken_contour_inward(contour, thick):
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# 创建一个空白的黑色图像与原始掩码大小相同
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blank = np.zeros_like(mask)
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# 在空白图像上绘制白色的轮廓
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cv2.drawContours(blank, [contour], -1, 255, thickness=thick)
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# 找到轮廓的中心（可以用重心等方法近似）
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M = cv2.moments(contour)
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cx = int(M['m10'] / M['m00'])
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cy = int(M['m01'] / M['m00'])
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# 进行距离变换，离中心越近的值越小
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dist_transform = cv2.distanceTransform(255 - blank, cv2.DIST_L2, 5)
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# 根据距离变换的值来决定是否保留像素，离中心近的像素更容易被保留
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result = np.zeros_like(mask)
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for i in range(dist_transform.shape[0]):
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for j in range(dist_transform.shape[1]):
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if dist_transform[i, j] < thick:
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result[i, j] = 255
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return result
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for contour in contours:
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thickened_contour = thicken_contour_inward(contour, thickness)
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mask_color[thickened_contour > 0] = color
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_, binary_result = cv2.threshold(mask_color, 127, 255, cv2.THRESH_BINARY)
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# 转换为掩码形式
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mask_result = cv2.cvtColor(binary_result, cv2.COLOR_BGR2GRAY)
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return mask_result
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def is_file_exists(self, bucket_name, file_name):
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try:
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self.minio_client.stat_object(bucket_name, file_name)
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return True
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except Exception:
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return False
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