diff --git a/app/service/generate_batch_image/service_batch_generate_relight_image.py b/app/service/generate_batch_image/service_batch_generate_relight_image.py
index e75c0cc..0a039d5 100644
--- a/app/service/generate_batch_image/service_batch_generate_relight_image.py
+++ b/app/service/generate_batch_image/service_batch_generate_relight_image.py
@@ -48,7 +48,7 @@ def batch_generate_relight(batch_request_data):
         prompt = data['prompt']
         product_type = data['product_type']
         image_url = data['image_url']
-        image = oss_get_image(bucket=image_url.split('/')[0], object_name=image_url.split('/', 1)[1], data_type="cv2")
+        image = pre_processing_image(image_url)
         tasks_id = data['tasks_id']
 
         prompts = [prompt] * 1
@@ -149,6 +149,48 @@ def batch_generate_relight(batch_request_data):
         logger.info(f" [x]Queue : {BATCH_GRI_RABBITMQ_QUEUES} | batch_tasks_id：{batch_tasks_id} | progress：OK | result_data_list：{result_data_list}")
 
 
+def pre_processing_image(image_url):
+    image = oss_get_image(bucket=image_url.split('/')[0], object_name=image_url[image_url.find('/') + 1:], data_type="PIL")
+    # 目标图片的尺寸
+    target_width = 512
+    target_height = 768
+
+    # 原始图片的尺寸
+    original_width, original_height = image.size
+
+    # 计算宽度和高度的缩放比例
+    width_ratio = target_width / original_width
+    height_ratio = target_height / original_height
+
+    # 选择较小的缩放比例，确保图片能完整放入目标图片中
+    scale_ratio = min(width_ratio, height_ratio)
+
+    # 计算调整后的尺寸
+    new_width = int(original_width * scale_ratio)
+    new_height = int(original_height * scale_ratio)
+
+    # 调整图片大小
+    resized_image = image.resize((new_width, new_height))
+
+    # 创建一个 512x768 的透明图片
+    result_image = Image.new("RGBA", (target_width, target_height), (255, 255, 255, 0))
+
+    # 计算需要粘贴的位置，使图片居中
+    x_offset = (target_width - new_width) // 2
+    y_offset = (target_height - new_height) // 2
+
+    # 将调整大小后的图片粘贴到透明图片上
+    if resized_image.mode == "RGBA":
+        result_image.paste(resized_image, (x_offset, y_offset), mask=resized_image.split()[3])
+    else:
+        result_image.paste(resized_image, (x_offset, y_offset))
+
+    image = np.array(result_image)
+
+    # image = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA)
+    return image
+
+
 def publish_status(task_id, progress, result):
     connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
     channel = connection.channel()
@@ -171,14 +213,14 @@ if __name__ == '__main__':
             RelightItemModel(
                 tasks_id="123-5464",
                 product_type="overall",
-                image_url="aida-users/89/product_image/02894523-19b5-46eb-a9c6-2f512f5fec84-0-89.png",
+                image_url="test/703190759.png",
                 prompt="Colorful black",
                 direction="Right Light",
             ),
             RelightItemModel(
                 tasks_id="123-5464123",
                 product_type="overall",
-                image_url="aida-users/89/product_image/02894523-19b5-46eb-a9c6-2f512f5fec84-0-89.png",
+                image_url="test/703190759.png",
                 direction="Right Light",
                 prompt="Colorful black",
             )