feat 结果图宽度自适应

fix

app/service/design/service.py

@@ -97,9 +97,9 @@ def process_object(cfg, process_id, total):
         #         uploaded_images.append({'image_obj': layer['pattern_image'], 'image_url': layer['pattern_image_url'], 'image_type': 'pattern_image'})
         #     if 'mask' in layer.keys() and layer['mask'] is not None and layer['mask_url'] is not None:
         #         uploaded_images.append({'image_obj': layer['mask'], 'image_url': layer['mask_url'], 'image_type': 'mask'})
-
+        layers, new_size = update_base_size_priority(layers, body_size)
         # 合成
-        items_response['synthesis_url'] = synthesis(layers, body_size, basic_info)
+        items_response['synthesis_url'] = synthesis(layers, new_size, basic_info)
 
         for lay in layers:
             items_response['layers'].append({
@@ -177,3 +177,19 @@ def upload_images(image_obj):
         rgba_image[rgba_image[:, :, 0] == 0] = [0, 0, 0, 0]
         req = oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=cv2.imencode('.png', rgba_image)[1])
         return image_obj['image_url']
+
+
+def update_base_size_priority(layers, size):
+    # 计算透明背景图片的宽度
+    min_x = min(info['position'][1] for info in layers)
+    x_list = []
+    for info in layers:
+        if info['image'] is not None:
+            x_list.append(info['position'][1] + info['image'].width)
+    max_x = max(x_list)
+    new_width = max_x - min_x
+    new_height = 700
+    # 更新坐标
+    for info in layers:
+        info['position'] = (info['position'][0], info['position'][1] - min_x)
+    return layers, (new_width, new_height)

app/service/design/utils/synthesis_item.py

@@ -63,14 +63,18 @@ def synthesis(data, size, basic_info):
     # 创建底图
     base_image = Image.new('RGBA', size, (0, 0, 0, 0))
     try:
-
         all_mask_shape = (size[1], size[0])
         body_mask = None
         for d in data:
             if d['name'] == 'body':
-                body_mask = np.array(d['image'].split()[3])
+                # 创建一个新的宽高透明图像， 把模特贴上去获取mask
-                left_shoulder = basic_info['body_point_test']['shoulder_left']
+                transparent_image = Image.new("RGBA", size, (0, 0, 0, 0))
-                right_shoulder = basic_info['body_point_test']['shoulder_right']
+                transparent_image.paste(d['image'], (d['position'][1], d['position'][0]), d['image'])  # 此处可变数组会被paste篡改值，所以使用下标获取position
+                body_mask = np.array(transparent_image.split()[3])
+
+                # 根据新的坐标获取新的肩点
+                left_shoulder = [x + y for x, y in zip(basic_info['body_point_test']['shoulder_left'], [d['position'][1], d['position'][0]])]
+                right_shoulder = [x + y for x, y in zip(basic_info['body_point_test']['shoulder_right'], [d['position'][1], d['position'][0]])]
                 body_mask[:min(left_shoulder[1], right_shoulder[1]), left_shoulder[0]:right_shoulder[0]] = 255
         _, binary_body_mask = cv2.threshold(body_mask, 127, 255, cv2.THRESH_BINARY)
         top_outer_mask = np.array(binary_body_mask)
@@ -118,7 +122,7 @@ def synthesis(data, size, basic_info):
                     mask_data = np.where(all_mask > 0, 255, 0).astype(np.uint8)
                     mask_alpha = Image.fromarray(mask_data)
                     cropped_image = Image.composite(test_image, Image.new("RGBA", test_image.size, (255, 255, 255, 0)), mask_alpha)
-                    base_image.paste(test_image, (0, 0), cropped_image)
+                    base_image.paste(test_image, (0, 0), cropped_image)  # test_image 已经按照坐标贴到最大宽值的图片上 坐着这里坐标为00
                 else:
                     base_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image'])