diff --git a/modelscope/pipeline_inputs.py b/modelscope/pipeline_inputs.py
index 77940c3c..13560229 100644
--- a/modelscope/pipeline_inputs.py
+++ b/modelscope/pipeline_inputs.py
@@ -91,6 +91,10 @@ TASK_INPUTS = {
     InputType.IMAGE,
     Tasks.crowd_counting:
     InputType.IMAGE,
+    Tasks.image_inpainting: {
+        'img': InputType.IMAGE,
+        'mask': InputType.IMAGE,
+    },
 
     # image generation task result for a single image
     Tasks.image_to_image_generation:
diff --git a/modelscope/pipelines/cv/image_inpainting_pipeline.py b/modelscope/pipelines/cv/image_inpainting_pipeline.py
index 6ae0d63e..aff9788d 100644
--- a/modelscope/pipelines/cv/image_inpainting_pipeline.py
+++ b/modelscope/pipelines/cv/image_inpainting_pipeline.py
@@ -77,21 +77,22 @@ class ImageInpaintingPipeline(Pipeline):
             img, ((0, 0), (0, out_height - height), (0, out_width - width)),
             mode='symmetric')
 
-    def preprocess(self, input: Input) -> Dict[str, Any]:
-        if isinstance(input, str):
-            image_name, mask_name = input.split('+')
+    def preprocess(self, input: Dict[str, Any]) -> Dict[str, Any]:
+        if isinstance(input['img'], str):
+            image_name, mask_name = input['img'], input['mask']
             img = LoadImage.convert_to_ndarray(image_name)
             img = self.transforms(img)
             mask = np.array(LoadImage(mode='L')(mask_name)['img'])
             mask = self.transforms(mask)
-        elif isinstance(input, PIL.Image.Image):
-            img = input.crop((0, 0, int(input.width / 2), input.height))
+        elif isinstance(input['img'], PIL.Image.Image):
+            img = input['img']
             img = self.transforms(np.array(img))
-            mask = input.crop((int(input.width / 2), 0, input.width,
-                               input.height)).convert('L')
+            mask = input['mask'].convert('L')
             mask = self.transforms(np.array(mask))
         else:
-            raise TypeError('input should be either str or PIL.Image')
+            raise TypeError(
+                'input should be either str or PIL.Image, and both inputs should have the same type'
+            )
         result = dict(image=img, mask=mask[None, ...])
 
         if self.pad_out_to_modulo is not None and self.pad_out_to_modulo > 1:
diff --git a/tests/pipelines/test_image_inpainting.py b/tests/pipelines/test_image_inpainting.py
index b89ce399..a8b704b7 100644
--- a/tests/pipelines/test_image_inpainting.py
+++ b/tests/pipelines/test_image_inpainting.py
@@ -20,6 +20,10 @@ class ImageInpaintingTest(unittest.TestCase):
         self.input_location = 'data/test/images/image_inpainting/image_inpainting.png'
         self.input_mask_location = 'data/test/images/image_inpainting/image_inpainting_mask.png'
         self.model_id = 'damo/cv_fft_inpainting_lama'
+        self.input = {
+            'img': self.input_location,
+            'mask': self.input_mask_location
+        }
 
     def save_result(self, result):
         vis_img = result[OutputKeys.OUTPUT_IMG]
@@ -28,8 +32,7 @@ class ImageInpaintingTest(unittest.TestCase):
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_inpainting(self):
         inpainting = pipeline(Tasks.image_inpainting, model=self.model_id)
-        result = inpainting(self.input_location + '+'
-                            + self.input_mask_location)
+        result = inpainting(self.input)
         if result:
             self.save_result(result)
         else:
@@ -41,8 +44,7 @@ class ImageInpaintingTest(unittest.TestCase):
         # if input image is HR, set refine=True is more better
         inpainting = pipeline(
             Tasks.image_inpainting, model=self.model_id, refine=True)
-        result = inpainting(self.input_location + '+'
-                            + self.input_mask_location)
+        result = inpainting(self.input)
         if result:
             self.save_result(result)
         else:
@@ -53,10 +55,7 @@ class ImageInpaintingTest(unittest.TestCase):
         inpainting = pipeline(Tasks.image_inpainting, model=self.model_id)
         img = Image.open(self.input_location).convert('RGB')
         mask = Image.open(self.input_mask_location).convert('RGB')
-        img_new = Image.new('RGB', (img.width + mask.width, img.height))
-        img_new.paste(img, (0, 0))
-        img_new.paste(mask, (img.width, 0))
-        result = inpainting(img_new)
+        result = inpainting({'img': img, 'mask': mask})
         if result:
             self.save_result(result)
         else:
@@ -65,8 +64,7 @@ class ImageInpaintingTest(unittest.TestCase):
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_inpainting_with_default_task(self):
         inpainting = pipeline(Tasks.image_inpainting)
-        result = inpainting(self.input_location + '+'
-                            + self.input_mask_location)
+        result = inpainting(self.input)
         if result:
             self.save_result(result)
         else: