feat 新增sketch 背后视角图

fix

app/service/design_fast/design_generate.py

@@ -81,6 +81,7 @@ def design_generate(request_data):
                     'mask_url': lay['mask_url'],
                     'image_url': lay['image_url'] if 'image_url' in lay.keys() else None,
                     'pattern_image_url': lay['pattern_image_url'] if 'pattern_image_url' in lay.keys() else None,
+                    'back_perspective_url': lay['back_perspective_url'] if 'back_perspective_url' in lay.keys() else None,
                 })
             items_response['synthesis_url'] = synthesis(layers, new_size, basic)
         else:

app/service/design_fast/item.py

@@ -1,4 +1,4 @@
-from app.service.design_fast.pipeline import LoadImage, KeyPoint, Segmentation, Color, PrintPainting, Scaling, Split, LoadBodyImage, ContourDetection
+from app.service.design_fast.pipeline import LoadImage, KeyPoint, Segmentation, Color, PrintPainting, Scaling, Split, LoadBodyImage, ContourDetection, BackPerspective
 
 
 class BaseItem:
@@ -16,6 +16,7 @@ class TopItem(BaseItem):
             LoadImage(minio_client),
             KeyPoint(),
             Segmentation(minio_client),
+            BackPerspective(minio_client),
             Color(minio_client),
             PrintPainting(minio_client),
             Scaling(),
@@ -36,6 +37,7 @@ class BottomItem(BaseItem):
             KeyPoint(),
             ContourDetection(),
             # Segmentation(),
+            BackPerspective(minio_client),
             Color(minio_client),
             PrintPainting(minio_client),
             Scaling(),

app/service/design_fast/pipeline/__init__.py

@@ -1,3 +1,4 @@
+from .back_perspective import BackPerspective
 from .color import Color
 from .contour_detection import ContourDetection
 from .keypoint import KeyPoint
@@ -13,6 +14,7 @@ __all__ = [
     'KeyPoint',
     'ContourDetection',
     'Segmentation',
+    'BackPerspective',
     'Color',
     'PrintPainting',
     'Scaling',

app/service/design_fast/pipeline/back_perspective.py

@@ -0,0 +1,79 @@
+import cv2
+import numpy as np
+
+from app.service.design_fast.utils.design_ensemble import get_seg_result
+from app.service.utils.new_oss_client import oss_upload_image
+
+
+class BackPerspective:
+    def __init__(self, minio_client):
+        self.minio_client = minio_client
+
+    def __call__(self, result):
+
+        # 如果sketch为系统图 查看是否有对应的 背后视角图
+        if result['path'].split('/')[0] == 'aida-sys-image':
+            file_path = result['path'].replace("images", 'images_back', 1)
+            if self.is_file_exists(bucket_name='aida-sys-image', file_name=file_path[file_path.find('/') + 1:]):
+                result['back_perspective_url'] = file_path
+                return result
+            else:
+                seg_result = get_seg_result("1", 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]
+
+        m = self.thicken_contours_and_display(seg_result, thickness=10, color=(0, 0, 0))
+        back_sketch = result['image'].copy()
+        back_sketch[m > 100] = 255
+        # 上传背后视角图
+        _, img_encoded = cv2.imencode(".jpg", back_sketch)
+
+        resp = oss_upload_image(self.minio_client, bucket='test', object_name=result['path'], image_bytes=img_encoded.tobytes())
+        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)):
+        mask = mask.astype(np.uint8) * 255
+        # 查找轮廓
+        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        # 创建一个彩色副本用于绘制轮廓
+        mask_color = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
+
+        def thicken_contour_inward(contour, thick):
+            # 创建一个空白的黑色图像与原始掩码大小相同
+            blank = np.zeros_like(mask)
+            # 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'])
+            # 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
+            result = np.zeros_like(mask)
+            for i in range(dist_transform.shape[0]):
+                for j in range(dist_transform.shape[1]):
+                    if dist_transform[i, j] < thick:
+                        result[i, j] = 255
+            return result
+
+        for contour in contours:
+            thickened_contour = thicken_contour_inward(contour, thickness)
+            mask_color[thickened_contour > 0] = color
+
+        _, binary_result = cv2.threshold(mask_color, 127, 255, cv2.THRESH_BINARY)
+
+        # 转换为掩码形式
+        mask_result = cv2.cvtColor(binary_result, cv2.COLOR_BGR2GRAY)
+        return mask_result
+
+    def is_file_exists(self, bucket_name, file_name):
+        try:
+            self.minio_client.stat_object(bucket_name, file_name)
+            return True
+        except Exception:
+            return False

app/service/design_fast/utils/organize.py

@@ -33,8 +33,8 @@ def organize_clothing(layer):
                        mask=cv2.resize(layer['mask'], layer["front_image"].size),
                        gradient_string=layer['gradient_string'] if 'gradient_string' in layer.keys() else "",
                        pattern_image_url=layer['pattern_image_url'],
-                       pattern_image=layer['pattern_image']
-
+                       pattern_image=layer['pattern_image'],
+                       back_perspective_url=layer['back_perspective_url'] if 'back_perspective_url' in layer.keys() else ""
                        )
     # 后片数据
     back_layer = dict(priority=-layer.get("priority", 0) if layer.get("layer_order", False) else PRIORITY_DICT.get(f'{layer["name"].lower()}_back', None),
@@ -50,6 +50,7 @@ def organize_clothing(layer):
                       mask=cv2.resize(layer['mask'], layer["front_image"].size),
                       gradient_string=layer['gradient_string'] if 'gradient_string' in layer.keys() else "",
                       pattern_image_url=layer['pattern_image_url'],
+                      back_perspective_url=layer['back_perspective_url'] if 'back_perspective_url' in layer.keys() else ""
                       )
     return front_layer, back_layer