[to #42322933]formalize test data storage

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9251871

docs/source/quick_start.md

@@ -25,7 +25,7 @@ pip install --upgrade tensorflow
 ### pip安装
 执行如下命令：
 ```shell
-pip install model_scope[all] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
+pip install model_scope[all] -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/0.2/repo.html
 ```
 ### 使用源码安装
 适合本地开发调试使用，修改源码后可以直接执行

docs/source/tutorials/pipeline.md

@@ -54,9 +54,8 @@ print(word_seg(input))
 下面以一个图像任务：人像抠图（'image-matting'）为例，进一步说明pipeline的用法
 ```python
 import cv2
-import os.path as osp
 from modelscope.pipelines import pipeline
 img_matting = pipeline('image-matting')
-result = img_matting('http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/data/test/maas/image_matting/test.png')
+result = img_matting('https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/image_matting.png')
 cv2.imwrite('result.png', result['output_png'])
 ```

tests/fileio/test_file.py

@@ -26,8 +26,7 @@ class FileTest(unittest.TestCase):
 
     def test_http_storage(self):
         storage = HTTPStorage()
-        url = 'http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com' \
-            '/data/test/data.txt'
+        url = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/texts/data.txt'
         content = 'this is test data'
         self.assertEqual(content.encode('utf8'), storage.read(url))
         self.assertEqual(content, storage.read_text(url))
@@ -43,8 +42,7 @@ class FileTest(unittest.TestCase):
             storage.read(url + 'df')
 
     def test_file(self):
-        url = 'http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com'\
-            '/data/test/data.txt'
+        url = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/texts/data.txt'
         content = 'this is test data'
         self.assertEqual(content.encode('utf8'), File.read(url))
 

tests/pipelines/test_animal_recognation.py

@@ -12,7 +12,7 @@ class MultiModalFeatureTest(unittest.TestCase):
         animal_recog = pipeline(
             Tasks.image_classification,
             model='damo/cv_resnest101_animal_recognition')
-        result = animal_recog('data/test/images/image1.jpg')
+        result = animal_recog('data/test/images/dogs.jpg')
         print(result)
 
 

tests/pipelines/test_base.py

@@ -81,7 +81,7 @@ class CustomPipelineTest(unittest.TestCase):
         pipe2 = pipeline(dummy_task)
         self.assertTrue(type(pipe) is type(pipe2))
 
-        img_url = 'data/test/images/image1.jpg'
+        img_url = 'data/test/images/dogs.jpg'
         output = pipe(img_url)
         self.assertEqual(output['filename'], img_url)
         self.assertEqual(output[OutputKeys.OUTPUT_IMG].shape, (318, 512, 3))

tests/pipelines/test_person_image_cartoon.py

@@ -16,9 +16,7 @@ class ImageCartoonTest(unittest.TestCase):
 
     def setUp(self) -> None:
         self.model_id = 'damo/cv_unet_person-image-cartoon_compound-models'
-        self.test_image = \
-            'http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com' \
-            '/data/test/maas/image_carton/test.png'
+        self.test_image = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/image_cartoon.png'
 
     def pipeline_inference(self, pipeline: Pipeline, input_location: str):
         result = pipeline(input_location)