feat（新功能）: 1、design-print为解决sketch原图太灰导致印花颜色便暗 2、cv2.resize 插值算法更换，提升resize后图片质量 fix（修复bug）: refactor（重构）: test(增加测试):

app/service/design_fast/pipeline/loading.py

@@ -1,5 +1,6 @@
 import io
 import logging
+import os
 
 import cv2
 import numpy as np
@@ -38,12 +39,42 @@ class LoadImage:
 
     def __call__(self, result):
         result['image'], result['pre_mask'] = self.read_image(result['path'])
-        result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)
+        # if 'extract_lines' in result.keys():
+        #     if result['extract_lines']:
+        #         result['gray'] = self.get_lines(cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY), result['path'])
+        #     else:
+        #         result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)
+        # 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['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):
+        binary = cv2.adaptiveThreshold(img, 255,
+                                       cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
+                                       cv2.THRESH_BINARY_INV,
+                                       25, 10)
+
+        # 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]
+
+        # 步骤3：反转回 白底黑线
+        # lines = cv2.bitwise_not(thinned)
+        # cv2.imwrite(os.path.join('/home/user/PycharmProjects/trinity_client_aida/test/lines_original_result_5', f"Original_{path.replace('/', '-')}.png"), img)
+        # cv2.imwrite(os.path.join('/home/user/PycharmProjects/trinity_client_aida/test/lines_original_result_5', f"Line_{path.replace('/', '-')}.png"), result)
+
+        return result
+
     def read_image(self, image_path):
         image_mask = None
         image = oss_get_image(oss_client=self.minio_client, bucket=image_path.split("/", 1)[0], object_name=image_path.split("/", 1)[1], data_type="cv2")

app/service/design_fast/pipeline/split.py

@@ -32,14 +32,14 @@ class Split(object):
                     new_width = int(width * result['resize_scale'][0])
                     new_height = int(height * result['resize_scale'][1])
 
-                    front_mask = cv2.resize(result['front_mask'], (new_width, new_height))
+                    front_mask = cv2.resize(result['front_mask'], (new_width, new_height), interpolation=cv2.INTER_AREA)
-                    back_mask = cv2.resize(result['back_mask'], (new_width, new_height))
+                    back_mask = cv2.resize(result['back_mask'], (new_width, new_height), interpolation=cv2.INTER_AREA)
 
                 rgba_image = rgb_to_rgba(result['final_image'], front_mask + back_mask)
                 new_size = (int(rgba_image.shape[1] * result["scale"]), int(rgba_image.shape[0] * result["scale"]))
-                rgba_image = cv2.resize(rgba_image, new_size)
+                rgba_image = cv2.resize(rgba_image, new_size, interpolation=cv2.INTER_AREA)
                 result_front_image = np.zeros_like(rgba_image)
-                front_mask = cv2.resize(front_mask, new_size)
+                front_mask = cv2.resize(front_mask, new_size, interpolation=cv2.INTER_AREA)
                 result_front_image[front_mask != 0] = rgba_image[front_mask != 0]
                 result_front_image_pil = Image.fromarray(cvtColor(result_front_image, COLOR_BGR2RGBA))
                 if 'transparent' in result.keys():
@@ -48,7 +48,7 @@ class Split(object):
                     if transparent['mask_url'] is not None and transparent['mask_url'] != "":
                         # 预处理用户自选区mask
                         seg_mask = oss_get_image(oss_client=self.minio_client, bucket=transparent['mask_url'].split('/')[0], object_name=transparent['mask_url'][transparent['mask_url'].find('/') + 1:], data_type="cv2")
-                        seg_mask = cv2.resize(seg_mask, new_size, interpolation=cv2.INTER_NEAREST)
+                        seg_mask = cv2.resize(seg_mask, new_size, interpolation=cv2.INTER_AREA)
                         # 转换颜色空间为 RGB（OpenCV 默认是 BGR）
                         image_rgb = cv2.cvtColor(seg_mask, cv2.COLOR_BGR2RGB)
 
@@ -75,7 +75,7 @@ class Split(object):
 
                 # if result["name"] in ('blouse', 'dress', 'outwear', 'tops'):
                 #     result_back_image = np.zeros_like(rgba_image)
-                #     back_mask = cv2.resize(back_mask, new_size)
+                #     back_mask = cv2.resize(back_mask, new_size, interpolation=cv2.INTER_AREA)
                 #     result_back_image[back_mask != 0] = rgba_image[back_mask != 0]
                 #     result_back_image_pil = Image.fromarray(cvtColor(result_back_image, COLOR_BGR2RGBA))
                 #     result['back_image'], result["back_image_url"], _ = upload_png_mask(self.minio_client, result_back_image_pil, f'{generate_uuid()}', mask=None)
@@ -104,7 +104,7 @@ class Split(object):
                 #     # result['back_mask_image'] = None
 
                 result_back_image = np.zeros_like(rgba_image)
-                back_mask = cv2.resize(back_mask, new_size)
+                back_mask = cv2.resize(back_mask, new_size, interpolation=cv2.INTER_AREA)
                 result_back_image[back_mask != 0] = rgba_image[back_mask != 0]
                 result_back_image_pil = Image.fromarray(cvtColor(result_back_image, COLOR_BGR2RGBA))
                 result['back_image'], result["back_image_url"], _ = upload_png_mask(self.minio_client, result_back_image_pil, f'{generate_uuid()}', mask=None)