diff --git a/app/service/generate_image/service_generate_product_image.py b/app/service/generate_image/service_generate_product_image.py
index 22f7306..287a983 100644
--- a/app/service/generate_image/service_generate_product_image.py
+++ b/app/service/generate_image/service_generate_product_image.py
@@ -247,7 +247,10 @@ class GenerateProductImage:
             self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data))
         else:
             # pil图像转成numpy数组
-            image = result.as_numpy("generated_inpaint_image")
+            if self.product_type == "single":
+                image = result.as_numpy("generated_cnet_image")
+            else:
+                image = result.as_numpy("generated_inpaint_image")
             image_result = Image.fromarray(np.squeeze(image.astype(np.uint8)))
             # cropped_image = post_processing_image(image_result, self.left, self.top)
             image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png")
@@ -269,9 +272,9 @@ class GenerateProductImage:
             images = [self.image.astype(np.uint8)] * self.batch_size
 
             if self.product_type == "single":
-                text_obj = np.array(prompts, dtype="object").reshape(-1, 1)
-                image_obj = np.array(images, dtype=np.uint8).reshape((-1, 1024, 1024, 3))
-                image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape(-1, 1)
+                text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
+                image_obj = np.array(images, dtype=np.uint8).reshape((-1, 768, 512, 3))
+                image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape((-1, 1))
             else:
                 text_obj = np.array(prompts, dtype="object").reshape((1))
                 image_obj = np.array(images, dtype=np.uint8).reshape((768, 512, 3))
@@ -290,7 +293,7 @@ class GenerateProductImage:
             inputs = [input_text, input_image, input_image_strength]
 
             if self.product_type == "single":
-                ctx = self.grpc_client.async_infer(model_name="stable_diffusion_xl_cnet_inpaint", inputs=inputs, callback=self.callback)
+                ctx = self.grpc_client.async_infer(model_name="stable_diffusion_1_5_cnet", inputs=inputs, callback=self.callback)
             else:
                 ctx = self.grpc_client.async_infer(model_name="diffusion_ensemble_all", inputs=inputs, callback=self.callback)
 
@@ -369,8 +372,8 @@ if __name__ == '__main__':
         # prompt="",
         image_strength=0.7,
         prompt="The best quality, masterpiece, real image.,high quality clothing details,8K realistic,HDR",
-        image_url="aida-users/11633/toProductImageElement/46166c36-c584-4e0f-b9fe-50615ec03ef3.png",
-        product_type="overall"
+        image_url="aida-results/result_40c7924e-e220-11ef-8ea2-0242ac150003.png",
+        product_type="single"
     )
     server = GenerateProductImage(rd)
     print(server.get_result())