diff --git a/modelscope/pipelines/cv/easycv_pipelines/segmentation_pipeline.py b/modelscope/pipelines/cv/easycv_pipelines/segmentation_pipeline.py
index 2182e3b3..bd09fc9b 100644
--- a/modelscope/pipelines/cv/easycv_pipelines/segmentation_pipeline.py
+++ b/modelscope/pipelines/cv/easycv_pipelines/segmentation_pipeline.py
@@ -1,5 +1,10 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
+from typing import Any
+
+import numpy as np
+
 from modelscope.metainfo import Pipelines
+from modelscope.outputs import OutputKeys
 from modelscope.pipelines.builder import PIPELINES
 from modelscope.utils.constant import Tasks
 from .base import EasyCVPipeline
@@ -21,3 +26,22 @@ class EasyCVSegmentationPipeline(EasyCVPipeline):
             model_file_pattern=model_file_pattern,
             *args,
             **kwargs)
+
+    def __call__(self, inputs) -> Any:
+        outputs = self.predict_op(inputs)
+
+        semantic_result = outputs[0]['seg_pred']
+
+        ids = np.unique(semantic_result)[::-1]
+        legal_indices = ids != len(self.predict_op.CLASSES)  # for VOID label
+        ids = ids[legal_indices]
+        segms = (semantic_result[None] == ids[:, None, None])
+        masks = [it.astype(np.int) for it in segms]
+        labels_txt = np.array(self.predict_op.CLASSES)[ids].tolist()
+
+        results = {
+            OutputKeys.MASKS: masks,
+            OutputKeys.LABELS: labels_txt,
+            OutputKeys.SCORES: [0.999 for _ in range(len(labels_txt))]
+        }
+        return results
diff --git a/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py b/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py
index 80ab36a6..5f6dac4b 100644
--- a/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py
+++ b/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py
@@ -2,30 +2,34 @@
 import unittest
 from distutils.version import LooseVersion
 
+import cv2
 import easycv
 import numpy as np
 from PIL import Image
 
+from modelscope.outputs import OutputKeys
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
+from modelscope.utils.cv.image_utils import semantic_seg_masks_to_image
+from modelscope.utils.demo_utils import DemoCompatibilityCheck
 from modelscope.utils.test_utils import test_level
 
 
-class EasyCVSegmentationPipelineTest(unittest.TestCase):
-
+class EasyCVSegmentationPipelineTest(unittest.TestCase,
+                                     DemoCompatibilityCheck):
     img_path = 'data/test/images/image_segmentation.jpg'
 
-    def _internal_test_(self, model_id):
-        img = np.asarray(Image.open(self.img_path))
+    def setUp(self) -> None:
+        self.task = Tasks.image_segmentation
+        self.model_id = 'damo/cv_segformer-b0_image_semantic-segmentation_coco-stuff164k'
 
+    def _internal_test_(self, model_id):
         semantic_seg = pipeline(task=Tasks.image_segmentation, model=model_id)
         outputs = semantic_seg(self.img_path)
 
-        self.assertEqual(len(outputs), 1)
-
-        results = outputs[0]
-        self.assertListEqual(
-            list(img.shape)[:2], list(results['seg_pred'].shape))
+        draw_img = semantic_seg_masks_to_image(outputs[OutputKeys.MASKS])
+        cv2.imwrite('result.jpg', draw_img)
+        print('test ' + model_id + ' DONE')
 
     def _internal_test_batch_(self, model_id, num_samples=2, batch_size=2):
         # TODO: support in the future
@@ -49,37 +53,35 @@ class EasyCVSegmentationPipelineTest(unittest.TestCase):
     def test_segformer_b0(self):
         model_id = 'damo/cv_segformer-b0_image_semantic-segmentation_coco-stuff164k'
         self._internal_test_(model_id)
-        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b1(self):
         model_id = 'damo/cv_segformer-b1_image_semantic-segmentation_coco-stuff164k'
         self._internal_test_(model_id)
-        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b2(self):
         model_id = 'damo/cv_segformer-b2_image_semantic-segmentation_coco-stuff164k'
         self._internal_test_(model_id)
-        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b3(self):
         model_id = 'damo/cv_segformer-b3_image_semantic-segmentation_coco-stuff164k'
         self._internal_test_(model_id)
-        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b4(self):
         model_id = 'damo/cv_segformer-b4_image_semantic-segmentation_coco-stuff164k'
         self._internal_test_(model_id)
-        self._internal_test_batch_(model_id)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_segformer_b5(self):
         model_id = 'damo/cv_segformer-b5_image_semantic-segmentation_coco-stuff164k'
         self._internal_test_(model_id)
-        self._internal_test_batch_(model_id)
+
+    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    def test_demo_compatibility(self):
+        self.compatibility_check()
 
 
 if __name__ == '__main__':