From ce41ded4237bc7e2279cf4aff10fa3a21dd1c075 Mon Sep 17 00:00:00 2001
From: "pengyu.lpy" <pengyu.lpy@alibaba-inc.com>
Date: Thu, 1 Sep 2022 15:48:40 +0800
Subject: [PATCH] [to #42322933]modify test_segmentation_pipeline.py for damo
 models
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基于easycv上线的segformer，对应上传了5个对应的达摩院的分割模型，所以修正了tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py内容让其能够便利测试
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9934634
---
 .../test_segmentation_pipeline.py             | 48 +++++++++++++++----
 1 file changed, 39 insertions(+), 9 deletions(-)

diff --git a/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py b/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py
index 0eca2a7f..6cfdacc6 100644
--- a/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py
+++ b/tests/pipelines/easycv_pipelines/test_segmentation_pipeline.py
@@ -12,24 +12,54 @@ from modelscope.utils.test_utils import test_level
 
 class EasyCVSegmentationPipelineTest(unittest.TestCase):
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
-    def test_segformer_b0(self):
-        img_path = 'data/test/images/image_segmentation.jpg'
-        model_id = 'EasyCV/EasyCV-Segformer-b0'
-        img = np.asarray(Image.open(img_path))
+    img_path = 'data/test/images/image_segmentation.jpg'
+
+    def _internal_test__(self, model_id):
+        img = np.asarray(Image.open(self.img_path))
+
+        semantic_seg = pipeline(task=Tasks.image_segmentation, model=model_id)
+        outputs = semantic_seg(self.img_path)
 
-        object_detect = pipeline(task=Tasks.image_segmentation, model=model_id)
-        outputs = object_detect(img_path)
         self.assertEqual(len(outputs), 1)
 
         results = outputs[0]
         self.assertListEqual(
             list(img.shape)[:2], list(results['seg_pred'][0].shape))
-        self.assertListEqual(results['seg_pred'][0][1, :10].tolist(),
-                             [161 for i in range(10)])
+        self.assertListEqual(results['seg_pred'][0][1, 4:10].tolist(),
+                             [161 for i in range(6)])
         self.assertListEqual(results['seg_pred'][0][-1, -10:].tolist(),
                              [133 for i in range(10)])
 
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    def test_segformer_b0(self):
+        model_id = 'damo/cv_segformer-b0_image_semantic-segmentation_coco-stuff164k'
+        self._internal_test__(model_id)
+
+    @unittest.skipUnless(test_level() >= 1, '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)
+
+    @unittest.skipUnless(test_level() >= 1, '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)
+
+    @unittest.skipUnless(test_level() >= 1, '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)
+
+    @unittest.skipUnless(test_level() >= 1, '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)
+
+    @unittest.skipUnless(test_level() >= 1, '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)
+
 
 if __name__ == '__main__':
     unittest.main()