diff --git a/app/api/api_test.py b/app/api/api_test.py
index 0f8b98f..a7b965c 100644
--- a/app/api/api_test.py
+++ b/app/api/api_test.py
@@ -4,7 +4,7 @@ import logging
 from fastapi import APIRouter
 from fastapi import HTTPException
 
-from app.core.config import SR_RABBITMQ_QUEUES, GI_RABBITMQ_QUEUES, GPI_RABBITMQ_QUEUES, GRI_RABBITMQ_QUEUES, OSS, JAVA_STREAM_API_URL, GMV_RABBITMQ_QUEUES, SLOGAN_RABBITMQ_QUEUES, GEN_SINGLE_LOGO_RABBITMQ_QUEUES
+from app.core.config import SR_RABBITMQ_QUEUES, GI_RABBITMQ_QUEUES, GPI_RABBITMQ_QUEUES, GRI_RABBITMQ_QUEUES, OSS, JAVA_STREAM_API_URL, GMV_RABBITMQ_QUEUES, SLOGAN_RABBITMQ_QUEUES, GEN_SINGLE_LOGO_RABBITMQ_QUEUES, PS_RABBITMQ_QUEUES, BATCH_GPI_RABBITMQ_QUEUES, BATCH_GRI_RABBITMQ_QUEUES, BATCH_PS_RABBITMQ_QUEUES
 from app.schemas.response_template import ResponseModel
 
 logger = logging.getLogger()
@@ -16,10 +16,17 @@ def test(id: int):
     data = {
         "超分 SR_RABBITMQ_QUEUES": SR_RABBITMQ_QUEUES,
         "多视角 GMV_RABBITMQ_QUEUES": GMV_RABBITMQ_QUEUES,
+        "pose transform PS_RABBITMQ_QUEUES": PS_RABBITMQ_QUEUES,
         "logan SLOGAN_RABBITMQ_QUEUES": SLOGAN_RABBITMQ_QUEUES,
         "image and single logo GI_RABBITMQ_QUEUES": GI_RABBITMQ_QUEUES,
         "to product image GPI_RABBITMQ_QUEUES": GPI_RABBITMQ_QUEUES,
         "relight GRI_RABBITMQ_QUEUES": GRI_RABBITMQ_QUEUES,
+
+        # batch
+        "batch product BATCH_GPI_RABBITMQ_QUEUES": BATCH_GPI_RABBITMQ_QUEUES,
+        "batch relight BATCH_GRI_RABBITMQ_QUEUES": BATCH_GRI_RABBITMQ_QUEUES,
+        "batch pose transform BATCH_PS_RABBITMQ_QUEUES": BATCH_PS_RABBITMQ_QUEUES,
+
         "JAVA_STREAM_API_URL": JAVA_STREAM_API_URL,
         "local_oss_server": OSS
     }
diff --git a/app/service/generate_image/service_generate_relight_image.py b/app/service/generate_image/service_generate_relight_image.py
index 3723ee9..7db12c2 100644
--- a/app/service/generate_image/service_generate_relight_image.py
+++ b/app/service/generate_image/service_generate_relight_image.py
@@ -39,7 +39,7 @@ class GenerateRelightImage:
         self.negative_prompt = 'lowres, bad anatomy, bad hands, cropped, worst quality'
         self.direction = request_data.direction
         self.image_url = request_data.image_url
-        self.image = oss_get_image(bucket=self.image_url.split('/')[0], object_name=self.image_url[self.image_url.find('/') + 1:], data_type="cv2")
+        self.image = pre_processing_image(self.image_url)
         self.tasks_id = request_data.tasks_id
         self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:]
         self.gen_product_data = {'tasks_id': self.tasks_id, 'status': 'PENDING', 'message': "pending", 'image_url': ''}
@@ -137,6 +137,46 @@ class GenerateRelightImage:
             if not DEBUG:
                 publish_status(str_gen_product_data, GRI_RABBITMQ_QUEUES)
 
+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 infer_cancel(tasks_id):
     redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True)
@@ -153,7 +193,7 @@ if __name__ == '__main__':
         prompt="Colorful black",
         image_url='aida-results/result_0000b606-1902-11ef-9424-0242ac180002.png',
         direction="Right Light",
-        product_type="single"
+        product_type="overall"
     )
     server = GenerateRelightImage(rd)
     print(server.get_result())