feat : 代码梳理 移除所有敏感密钥 通过环境变量方式配置

app/service/design_fast/pipeline/back_perspective.py

@@ -18,11 +18,11 @@ class BackPerspective:
                 result['back_perspective_url'] = file_path
                 return result
             else:
-                seg_result = get_seg_result("1", result['image'])[0]
+                seg_result = get_seg_result(result['image'])[0]
         elif result['name'] in ['blouse', 'outwear', 'dress', 'tops']:
             seg_result = result['seg_result']
         else:
-            seg_result = get_seg_result("1", result['image'])[0]
+            seg_result = get_seg_result(result['image'])[0]
 
         m = self.thicken_contours_and_display(seg_result, thickness=10, color=(0, 0, 0))
         back_sketch = result['image'].copy()
@@ -34,7 +34,8 @@ class BackPerspective:
         result['back_perspective_url'] = f"{resp.bucket_name}/{resp.object_name}"
         return result
 
-    def thicken_contours_and_display(self, mask, thickness=10, color=(0, 0, 0)):
+    @staticmethod
+    def thicken_contours_and_display(mask, thickness=10, color=(0, 0, 0)):
         mask = mask.astype(np.uint8) * 255
         # 查找轮廓
         contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
@@ -48,9 +49,9 @@ class BackPerspective:
             # 在空白图像上绘制白色的轮廓
             cv2.drawContours(blank, [contour], -1, 255, thickness=thick)
             # 找到轮廓的中心（可以用重心等方法近似）
-            M = cv2.moments(contour)
-            cx = int(M['m10'] / M['m00'])
-            cy = int(M['m01'] / M['m00'])
+            m = cv2.moments(contour)
+            # cx = int(m['m10'] / m['m00'])
+            # cy = int(m['m01'] / m['m00'])
             # 进行距离变换，离中心越近的值越小
             dist_transform = cv2.distanceTransform(255 - blank, cv2.DIST_L2, 5)
             # 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