diff --git a/app/service/design/service.py b/app/service/design/service.py
index 37fdbde..b8c5a8c 100644
--- a/app/service/design/service.py
+++ b/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, new_size, basic_info)
+        items_response['synthesis_url'] = synthesis(layers, body_size, basic_info)
 
         for lay in layers:
             items_response['layers'].append({
@@ -177,17 +177,3 @@ 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):
-    # 计算新图片的宽度和高度
-    max_x = max([layer["position"][1] + layer["image"].size[0] for layer in layers])
-    min_x = min([layer["position"][1] for layer in layers])
-    new_width = max(size[0], max_x - min_x)
-    new_height = size[1]
-
-    # 更新图片的坐标
-    for layer in layers:
-        updated_coords = [layer["position"][1] - min_x, layer["position"][0]]
-        layer['position'] = updated_coords
-    return layers, (new_width, new_height)
diff --git a/app/service/design/utils/synthesis_item.py b/app/service/design/utils/synthesis_item.py
index c8be2c7..d560f37 100644
--- a/app/service/design/utils/synthesis_item.py
+++ b/app/service/design/utils/synthesis_item.py
@@ -63,18 +63,14 @@ 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':
-                # 创建一个新的宽高透明图像， 把模特贴上去获取mask
-                transparent_image = Image.new("RGBA", size, (0, 0, 0, 0))
-                transparent_image.paste(d['image'], d['position'], d['image'])
-                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'])]
-                right_shoulder = [x + y for x, y in zip(basic_info['body_point_test']['shoulder_right'], d['position'])]
+                body_mask = np.array(d['image'].split()[3])
+                left_shoulder = basic_info['body_point_test']['shoulder_left']
+                right_shoulder = basic_info['body_point_test']['shoulder_right']
                 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)
@@ -118,13 +114,13 @@ def synthesis(data, size, basic_info):
             if layer['image'] is not None:
                 if layer['name'] != "body":
                     test_image = Image.new('RGBA', size, (0, 0, 0, 0))
-                    test_image.paste(layer['image'], layer['position'], layer['image'])
+                    test_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image'])
                     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)
                 else:
-                    base_image.paste(layer['image'], layer['position'], layer['image'])
+                    base_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image'])
 
         result_image = base_image