update user_guided_colorization (#1994)

* update user_guided_colorization

* add clean func

modules/image/Image_editing/colorization/user_guided_colorization/README.md

@@ -201,4 +201,8 @@
 
   初始发布
 
+  - ```shell
+    $ hub install user_guided_colorization==1.0.0
+    ```
+
 

modules/image/Image_editing/colorization/user_guided_colorization/README_en.md

@@ -203,3 +203,8 @@
 * 1.0.0
 
   First release
+
+
+  - ```shell
+    $ hub install user_guided_colorization==1.0.0
+    ```

modules/image/Image_editing/colorization/user_guided_colorization/module.py

@@ -20,7 +20,7 @@ from paddle.nn import Conv2D, Conv2DTranspose
 from paddlehub.module.module import moduleinfo
 import paddlehub.vision.transforms as T
 from paddlehub.module.cv_module import ImageColorizeModule
-from user_guided_colorization.data_feed import ColorizePreprocess
+from .data_feed import ColorizePreprocess
 
 
 @moduleinfo(

modules/image/Image_editing/colorization/user_guided_colorization/test.py

+import os
+import shutil
+import unittest
+
+import cv2
+import requests
+import numpy as np
+import paddlehub as hub
+
+
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
+
+class TestHubModule(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls) -> None:
+        img_url = 'https://unsplash.com/photos/1sLIu1XKQrY/download?ixid=MnwxMjA3fDB8MXxhbGx8MTJ8fHx8fHwyfHwxNjYyMzQxNDUx&force=true&w=640'
+        if not os.path.exists('tests'):
+            os.makedirs('tests')
+        response = requests.get(img_url)
+        assert response.status_code == 200, 'Network Error.'
+        with open('tests/test.jpg', 'wb') as f:
+            f.write(response.content)
+        cls.module = hub.Module(name="user_guided_colorization")
+
+    @classmethod
+    def tearDownClass(cls) -> None:
+        shutil.rmtree('tests')
+        shutil.rmtree('colorization')
+
+    def test_predict1(self):
+        results = self.module.predict(
+            images=['tests/test.jpg'],
+            visualization=False
+        )
+        gray = results[0]['gray']
+        hint = results[0]['hint']
+        real = results[0]['real']
+        fake_reg = results[0]['fake_reg']
+
+        self.assertIsInstance(gray, np.ndarray)
+        self.assertIsInstance(hint, np.ndarray)
+        self.assertIsInstance(real, np.ndarray)
+        self.assertIsInstance(fake_reg, np.ndarray)
+
+    def test_predict2(self):
+        results = self.module.predict(
+            images=[cv2.imread('tests/test.jpg')],
+            visualization=False
+        )
+        gray = results[0]['gray']
+        hint = results[0]['hint']
+        real = results[0]['real']
+        fake_reg = results[0]['fake_reg']
+
+        self.assertIsInstance(gray, np.ndarray)
+        self.assertIsInstance(hint, np.ndarray)
+        self.assertIsInstance(real, np.ndarray)
+        self.assertIsInstance(fake_reg, np.ndarray)
+
+    def test_predict3(self):
+        results = self.module.predict(
+            images=[cv2.imread('tests/test.jpg')],
+            visualization=True
+        )
+        gray = results[0]['gray']
+        hint = results[0]['hint']
+        real = results[0]['real']
+        fake_reg = results[0]['fake_reg']
+
+        self.assertIsInstance(gray, np.ndarray)
+        self.assertIsInstance(hint, np.ndarray)
+        self.assertIsInstance(real, np.ndarray)
+        self.assertIsInstance(fake_reg, np.ndarray)
+    
+    def test_predict4(self):
+        self.assertRaises(
+            IndexError,
+            self.module.predict,
+            images=['no.jpg'],
+            visualization=False
+        )
+
+if __name__ == "__main__":
+    unittest.main()