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/loading.py

@@ -1,10 +1,7 @@
-import io
 import logging
-import os
-
+from skimage.morphology import skeletonize
 import cv2
 import numpy as np
-from PIL import Image
 
 from app.service.utils.new_oss_client import oss_get_image
 
@@ -47,26 +44,32 @@ class LoadImage:
         # else:
         #     result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)
 
-        result['gray'] = self.get_lines(cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY), result['path'])
+        result['gray'] = self.get_lines(cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY))
         result['keypoint'] = self.get_keypoint(result['name'])
         result['img_shape'] = result['image'].shape
         result['ori_shape'] = result['image'].shape
         return result
 
-    def get_lines(self, img, path):
+    @staticmethod
+    def get_lines(img):
         binary = cv2.adaptiveThreshold(img, 255,
                                        cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                        cv2.THRESH_BINARY_INV,
                                        25, 10)
+        binary_bool = binary > 0
+        skeleton = skeletonize(binary_bool, method='zhang')
+        mask = skeleton
+        result = np.ones_like(img) * 255
+        result[mask] = img[mask]
 
         # 步骤2：细化边缘（可选，让线条更干净）
         # kernel = np.ones((1, 1), np.uint8)
         # clean = cv2.morphologyEx(binary, cv2.MORPH_OPEN, kernel)
 
-        thinned = cv2.ximgproc.thinning(binary, thinningType=cv2.ximgproc.THINNING_ZHANGSUEN)  # thinning算法细化线条
-        mask = thinned > 0
-        result = np.ones_like(img) * 255
-        result[mask] = img[mask]
+        # thinned = cv2.ximgproc.thinning(binary, thinningType=cv2.ximgproc.THINNING_ZHANGSUEN)  # thinning算法细化线条
+        # mask = thinned > 0
+        # result = np.ones_like(img) * 255
+        # result[mask] = img[mask]
 
         # 步骤3：反转回 白底黑线
         # lines = cv2.bitwise_not(thinned)