update falsr_b (#2185)

modules/image/Image_editing/super_resolution/falsr_b/README.md

@@ -149,20 +149,23 @@
         print("save image as falsr_b_X2.png")
         ```
 
+- ### Gradio APP 支持
+  从 PaddleHub 2.3.1 开始支持使用链接 http://127.0.0.1:8866/gradio/falsr_b 在浏览器中访问 falsr_b 的 Gradio APP。
 
 ## 五、更新历史
 
-
 * 1.0.0
 
   初始发布
 
-
 * 1.1.0
 
   移除 fluid API
 
+* 1.2.0
+
+  添加 Gradio APP 支持
+
   ```shell
-  $ hub install falsr_b == 1.1.0
+  $ hub install falsr_b == 1.2.0
   ```
-

modules/image/Image_editing/super_resolution/falsr_b/README_en.md

@@ -153,20 +153,23 @@
         print("save image as falsr_b_X2.png")
         ```
 
+- ### Gradio APP support
+  Starting with PaddleHub 2.3.1, the Gradio APP for falsr_b is supported to be accessed in the browser using the link http://127.0.0.1:8866/gradio/falsr_b.
 
 ## V. Release Note
 
-- 1.0.0
+* 1.0.0
 
   First release
 
-
-- 1.1.0
+* 1.1.0
 
   Remove Fluid API
 
+* 1.2.0
+
+  Add Gradio APP support.
 
   ```shell
-  $ hub install falsr_b == 1.1.0
+  $ hub install falsr_b == 1.2.0
   ```
-

modules/image/Image_editing/super_resolution/falsr_b/data_feed.py

-# -*- coding:utf-8 -*-
 import os
 import time
 from collections import OrderedDict
@@ -6,7 +5,6 @@ from collections import OrderedDict
 import cv2
 import numpy as np
 
-
 __all__ = ['reader']
 
 

modules/image/Image_editing/super_resolution/falsr_b/module.py

-# -*- coding:utf-8 -*-
 # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"
@@ -12,30 +11,32 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+import argparse
 import ast
 import os
-import argparse
 
 import numpy as np
-import paddle
-import paddle.jit
-import paddle.static
-from paddle.inference import Config, create_predictor
-from paddlehub.module.module import moduleinfo, runnable, serving
+from paddle.inference import Config
+from paddle.inference import create_predictor
 
 from .data_feed import reader
-from .processor import postprocess, base64_to_cv2, cv2_to_base64, check_dir
+from .processor import base64_to_cv2
+from .processor import check_dir
+from .processor import cv2_to_base64
+from .processor import postprocess
+from paddlehub.module.module import moduleinfo
+from paddlehub.module.module import runnable
+from paddlehub.module.module import serving
 
 
-@moduleinfo(
-    name="falsr_b",
+@moduleinfo(name="falsr_b",
             type="CV/image_editing",
             author="paddlepaddle",
             author_email="",
             summary="falsr_b is a super resolution model.",
-    version="1.1.0")
+            version="1.2.0")
 class Falsr_B:
+
     def __init__(self):
         self.default_pretrained_model_path = os.path.join(self.directory, "falsr_b_model", "model")
         self._set_config()
@@ -44,8 +45,8 @@ class Falsr_B:
         """
         predictor config setting
         """
-        model = self.default_pretrained_model_path+'.pdmodel'
-        params = self.default_pretrained_model_path+'.pdiparams'
+        model = self.default_pretrained_model_path + '.pdmodel'
+        params = self.default_pretrained_model_path + '.pdiparams'
         cpu_config = Config(model, params)
         cpu_config.disable_glog_info()
         cpu_config.disable_gpu()
@@ -110,8 +111,7 @@ class Falsr_B:
             output_names = predictor.get_output_names()
             output_handle = predictor.get_output_handle(output_names[0])
             output = np.expand_dims(output_handle.copy_to_cpu(), axis=1)
-            out = postprocess(
-                data_out=output,
+            out = postprocess(data_out=output,
                               org_im=all_data[i]['org_im'],
                               org_im_shape=all_data[i]['org_im_shape'],
                               org_im_path=all_data[i]['org_im_path'],
@@ -135,8 +135,7 @@ class Falsr_B:
         """
         Run as a command.
         """
-        self.parser = argparse.ArgumentParser(
-            description="Run the {} module.".format(self.name),
+        self.parser = argparse.ArgumentParser(description="Run the {} module.".format(self.name),
                                               prog='hub run {}'.format(self.name),
                                               usage='%(prog)s',
                                               add_help=True)
@@ -147,8 +146,10 @@ class Falsr_B:
         self.add_module_config_arg()
         self.add_module_input_arg()
         args = self.parser.parse_args(argvs)
-        results = self.reconstruct(
-            paths=[args.input_path], use_gpu=args.use_gpu, output_dir=args.output_dir, visualization=args.visualization)
+        results = self.reconstruct(paths=[args.input_path],
+                                   use_gpu=args.use_gpu,
+                                   output_dir=args.output_dir,
+                                   visualization=args.visualization)
         if args.save_dir is not None:
             check_dir(args.save_dir)
             self.save_inference_model(args.save_dir)
@@ -159,14 +160,22 @@ class Falsr_B:
         """
         Add the command config options.
         """
-        self.arg_config_group.add_argument(
-            '--use_gpu', type=ast.literal_eval, default=False, help="whether use GPU or not")
-        self.arg_config_group.add_argument(
-            '--output_dir', type=str, default='falsr_b_output', help="The directory to save output images.")
-        self.arg_config_group.add_argument(
-            '--save_dir', type=str, default='falsr_b_save_model', help="The directory to save model.")
-        self.arg_config_group.add_argument(
-            '--visualization', type=ast.literal_eval, default=True, help="whether to save output as images.")
+        self.arg_config_group.add_argument('--use_gpu',
+                                           type=ast.literal_eval,
+                                           default=False,
+                                           help="whether use GPU or not")
+        self.arg_config_group.add_argument('--output_dir',
+                                           type=str,
+                                           default='falsr_b_output',
+                                           help="The directory to save output images.")
+        self.arg_config_group.add_argument('--save_dir',
+                                           type=str,
+                                           default='falsr_b_save_model',
+                                           help="The directory to save model.")
+        self.arg_config_group.add_argument('--visualization',
+                                           type=ast.literal_eval,
+                                           default=True,
+                                           help="whether to save output as images.")
 
     def add_module_input_arg(self):
         """
@@ -174,8 +183,20 @@ class Falsr_B:
         """
         self.arg_input_group.add_argument('--input_path', type=str, help="path to image.")
 
-
-if __name__ == "__main__":
-    module = Falsr_B()
-    module.reconstruct(paths=["BSD100_001.png", "BSD100_002.png", "Set5_003.png"])
-    module.save_inference_model()
+    def create_gradio_app(self):
+        import gradio as gr
+        import tempfile
+        import os
+        from PIL import Image
+
+        def inference(image, use_gpu=False):
+            with tempfile.TemporaryDirectory() as temp_dir:
+                self.reconstruct(paths=[image], use_gpu=use_gpu, visualization=True, output_dir=temp_dir)
+                return Image.open(os.path.join(temp_dir, os.listdir(temp_dir)[0]))
+
+        interface = gr.Interface(
+            inference,
+            [gr.inputs.Image(type="filepath"), gr.Checkbox(label='use_gpu')],
+            gr.outputs.Image(type="ndarray"),
+            title='falsr_b')
+        return interface

modules/image/Image_editing/super_resolution/falsr_b/processor.py

-# -*- coding:utf-8 -*-
+import base64
 import os
 import time
-import base64
 
 import cv2
 import numpy as np

modules/image/Image_editing/super_resolution/falsr_b/test.py

@@ -3,18 +3,19 @@ import shutil
 import unittest
 
 import cv2
-import requests
 import numpy as np
-import paddlehub as hub
+import requests
 
+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'
+        img_url = 'https://unsplash.com/photos/1sLIu1XKQrY/download?ixid=MnwxMjA3fDB8MXxhbGx8MTJ8fHx8fHwyfHwxNjYyMzQxNDUx&force=true&w=120'
         if not os.path.exists('tests'):
             os.makedirs('tests')
         response = requests.get(img_url)
@@ -30,50 +31,26 @@ class TestHubModule(unittest.TestCase):
         shutil.rmtree('falsr_b_output')
 
     def test_reconstruct1(self):
-        results = self.module.reconstruct(
-            paths=['tests/test.jpg'],
-            use_gpu=False,
-            visualization=False
-        )
+        results = self.module.reconstruct(paths=['tests/test.jpg'], use_gpu=False, visualization=False)
         self.assertIsInstance(results[0]['data'], np.ndarray)
 
     def test_reconstruct2(self):
-        results = self.module.reconstruct(
-            images=[cv2.imread('tests/test.jpg')],
-            use_gpu=False,
-            visualization=False
-        )
+        results = self.module.reconstruct(images=[cv2.imread('tests/test.jpg')], use_gpu=False, visualization=False)
         self.assertIsInstance(results[0]['data'], np.ndarray)
 
     def test_reconstruct3(self):
-        results = self.module.reconstruct(
-            images=[cv2.imread('tests/test.jpg')],
-            use_gpu=False,
-            visualization=True
-        )
+        results = self.module.reconstruct(images=[cv2.imread('tests/test.jpg')], use_gpu=False, visualization=True)
         self.assertIsInstance(results[0]['data'], np.ndarray)
 
     def test_reconstruct4(self):
-        results = self.module.reconstruct(
-            images=[cv2.imread('tests/test.jpg')],
-            use_gpu=True,
-            visualization=False
-        )
+        results = self.module.reconstruct(images=[cv2.imread('tests/test.jpg')], use_gpu=True, visualization=False)
         self.assertIsInstance(results[0]['data'], np.ndarray)
 
     def test_reconstruct5(self):
-        self.assertRaises(
-            AssertionError,
-            self.module.reconstruct,
-            paths=['no.jpg']
-        )
+        self.assertRaises(AssertionError, self.module.reconstruct, paths=['no.jpg'])
 
     def test_reconstruct6(self):
-        self.assertRaises(
-            AttributeError,
-            self.module.reconstruct,
-            images=['test.jpg']
-        )
+        self.assertRaises(AttributeError, self.module.reconstruct, images=['test.jpg'])
 
     def test_save_inference_model(self):
         self.module.save_inference_model('./inference/model')