update pyramidbox_lite_mobile_mask

modules/image/face_detection/pyramidbox_lite_mobile_mask/README.md

@@ -179,6 +179,11 @@
     # 打印预测结果
     print(r.json()["results"])
     ```
+
+- ### gradio app 支持
+
+  从 PaddleHub 2.3.1 开始支持使用链接 http://127.0.0.1:8866/gradio/pyramidbox_lite_mobile_mask 在浏览器中访问 pyramidbox_lite_mobile_mask 的 Gradio APP。
+
 ## 五、Paddle Lite部署
 - ### 通过python执行以下代码，保存模型
   - ```python
@@ -209,6 +214,10 @@
 
   修复无法导出模型的问题
 
+* 1.5.0
+
+  添加 Gradio APP 的支持
+
   - ```shell
-    $ hub install pyramidbox_lite_mobile_mask==1.4.0
+    $ hub install pyramidbox_lite_mobile_mask==1.5.0
     ```

modules/image/face_detection/pyramidbox_lite_mobile_mask/README_en.md

@@ -154,6 +154,10 @@
     # print prediction results
     print(r.json()["results"])
     ```
+
+- ### Gradio APP support
+  Starting with PaddleHub 2.3.1, the Gradio APP for pyramidbox_lite_mobile_mask is supported to be accessed in the browser using the link http://127.0.0.1:8866/gradio/pyramidbox_lite_mobile_mask.
+
 ## V.Paddle Lite Deployment
 - ### Save model demo
   - ```python
@@ -185,6 +189,10 @@
 
   Fix a bug of save_inference_model
 
+* 1.5.0
+
+  Add Gradio APP support.
+
   - ```shell
-    $ hub install pyramidbox_lite_mobile_mask==1.4.0
+    $ hub install pyramidbox_lite_mobile_mask==1.5.0
     ```

modules/image/face_detection/pyramidbox_lite_mobile_mask/data_feed.py

@@ -1,6 +1,6 @@
 # coding=utf-8
-import os
 import math
+import os
 import time
 from collections import OrderedDict
 
@@ -144,12 +144,11 @@ def reader(face_detector, shrink, confs_threshold, images, paths, use_gpu, use_m
             scale_res = list()
             detect_faces = list()
             for scale in multi_scales:
-                _detect_res = face_detector.face_detection(
-                    images=[element['org_im']],
-                    use_gpu=use_gpu,
-                    visualization=False,
-                    shrink=scale,
-                    confs_threshold=confs_threshold)
+                _detect_res = face_detector.face_detection(images=[element['org_im']],
+                                                           use_gpu=use_gpu,
+                                                           visualization=False,
+                                                           shrink=scale,
+                                                           confs_threshold=confs_threshold)
 
                 _s = list()
                 for _face in _detect_res[0]['data']:
@@ -167,12 +166,11 @@ def reader(face_detector, shrink, confs_threshold, images, paths, use_gpu, use_m
                 face = {'left': data[0], 'top': data[1], 'right': data[2], 'bottom': data[3], 'confidence': data[4]}
                 detect_faces.append(face)
         else:
-            _detect_res = face_detector.face_detection(
-                images=[element['org_im']],
-                use_gpu=use_gpu,
-                visualization=False,
-                shrink=shrink,
-                confs_threshold=confs_threshold)
+            _detect_res = face_detector.face_detection(images=[element['org_im']],
+                                                       use_gpu=use_gpu,
+                                                       visualization=False,
+                                                       shrink=shrink,
+                                                       confs_threshold=confs_threshold)
             detect_faces = _detect_res[0]['data']
 
         element['preprocessed'] = list()

modules/image/face_detection/pyramidbox_lite_mobile_mask/module.py

@@ -7,14 +7,13 @@
 import os
 
 import numpy as np
-import paddle
 from paddle.inference import Config
 from paddle.inference import create_predictor
+
+import paddlehub as hub
 from .data_feed import reader
 from .processor import base64_to_cv2
 from .processor import postprocess
-
-import paddlehub as hub
 from paddlehub.module.module import moduleinfo
 from paddlehub.module.module import runnable
 from paddlehub.module.module import serving
@@ -27,8 +26,9 @@
     author_email="",
     summary=
     "Pyramidbox-Lite-Mobile-Mask is a high-performance face detection model used to detect whether people wear masks.",
-    version="1.4.0")
+    version="1.5.0")
 class PyramidBoxLiteMobileMask:
+
     def __init__(self, face_detector_module=None):
         """
         Args:
@@ -46,8 +46,8 @@ def _set_config(self):
         """
         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()
@@ -244,3 +244,28 @@ def add_module_input_arg(self):
                                           type=ast.literal_eval,
                                           default=0.6,
                                           help="confidence threshold.")
+
+    def create_gradio_app(self):
+        import gradio as gr
+        import tempfile
+        import os
+        from PIL import Image
+
+        def inference(image, shrink, confs_threshold):
+            with tempfile.TemporaryDirectory() as temp_dir:
+                self.face_detection(paths=[image],
+                                    use_gpu=False,
+                                    visualization=True,
+                                    output_dir=temp_dir,
+                                    shrink=shrink,
+                                    confs_threshold=confs_threshold)
+                return Image.open(os.path.join(temp_dir, os.listdir(temp_dir)[0]))
+
+        interface = gr.Interface(inference, [
+            gr.inputs.Image(type="filepath"),
+            gr.Slider(0.0, 1.0, 0.5, step=0.01),
+            gr.Slider(0.0, 1.0, 0.6, step=0.01)
+        ],
+                                 gr.outputs.Image(type="ndarray"),
+                                 title='pyramidbox_lite_mobile_mask')
+        return interface

modules/image/face_detection/pyramidbox_lite_mobile_mask/processor.py

@@ -3,13 +3,14 @@
 from __future__ import division
 from __future__ import print_function
 
+import base64
 import os
 import time
 
-import base64
 import cv2
 import numpy as np
-from PIL import Image, ImageDraw
+from PIL import Image
+from PIL import ImageDraw
 
 __all__ = ['base64_to_cv2', 'postprocess']
 
@@ -86,9 +87,9 @@ def draw_bounding_box_on_image(save_im_path, output_data):
             box_fill = (255)
             text_fill = (0)
 
-        draw.rectangle(
-            xy=(bbox['left'], bbox['top'] - (textsize_height + 5), bbox['left'] + textsize_width + 10, bbox['top'] - 3),
-            fill=box_fill)
+        draw.rectangle(xy=(bbox['left'], bbox['top'] - (textsize_height + 5), bbox['left'] + textsize_width + 10,
+                           bbox['top'] - 3),
+                       fill=box_fill)
         draw.text(xy=(bbox['left'], bbox['top'] - 15), text=text, fill=text_fill)
     image.save(save_im_path)
 

modules/image/face_detection/pyramidbox_lite_mobile_mask/test.py

@@ -4,13 +4,14 @@
 
 import cv2
 import requests
-import paddlehub as hub
 
+import paddlehub as hub
 
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 
 class TestHubModule(unittest.TestCase):
+
     @classmethod
     def setUpClass(cls) -> None:
         img_url = 'https://ai-studio-static-online.cdn.bcebos.com/7799a8ccc5f6471b9d56fb6eff94f82a08b70ca2c7594d3f99877e366c0a2619'
@@ -29,11 +30,7 @@ def tearDownClass(cls) -> None:
         shutil.rmtree('detection_result')
 
     def test_face_detection1(self):
-        results = self.module.face_detection(
-            paths=['tests/test.jpg'],
-            use_gpu=False,
-            visualization=False
-        )
+        results = self.module.face_detection(paths=['tests/test.jpg'], use_gpu=False, visualization=False)
         bbox = results[0]['data'][0]
 
         label = bbox['label']
@@ -42,7 +39,7 @@ def test_face_detection1(self):
         right = bbox['right']
         top = bbox['top']
         bottom = bbox['bottom']
-        
+
         self.assertEqual(label, 'NO MASK')
         self.assertTrue(confidence > 0.5)
         self.assertTrue(1000 < left < 4000)
@@ -51,11 +48,7 @@ def test_face_detection1(self):
         self.assertTrue(0 < bottom < 2000)
 
     def test_face_detection2(self):
-        results = self.module.face_detection(
-            images=[cv2.imread('tests/test.jpg')],
-            use_gpu=False,
-            visualization=False
-        )
+        results = self.module.face_detection(images=[cv2.imread('tests/test.jpg')], use_gpu=False, visualization=False)
         bbox = results[0]['data'][0]
 
         label = bbox['label']
@@ -64,7 +57,7 @@ def test_face_detection2(self):
         right = bbox['right']
         top = bbox['top']
         bottom = bbox['bottom']
-        
+
         self.assertEqual(label, 'NO MASK')
         self.assertTrue(confidence > 0.5)
         self.assertTrue(1000 < left < 4000)
@@ -73,11 +66,7 @@ def test_face_detection2(self):
         self.assertTrue(0 < bottom < 2000)
 
     def test_face_detection3(self):
-        results = self.module.face_detection(
-            images=[cv2.imread('tests/test.jpg')],
-            use_gpu=False,
-            visualization=True
-        )
+        results = self.module.face_detection(images=[cv2.imread('tests/test.jpg')], use_gpu=False, visualization=True)
         bbox = results[0]['data'][0]
 
         label = bbox['label']
@@ -86,7 +75,7 @@ def test_face_detection3(self):
         right = bbox['right']
         top = bbox['top']
         bottom = bbox['bottom']
-        
+
         self.assertEqual(label, 'NO MASK')
         self.assertTrue(confidence > 0.5)
         self.assertTrue(1000 < left < 4000)
@@ -95,11 +84,7 @@ def test_face_detection3(self):
         self.assertTrue(0 < bottom < 2000)
 
     def test_face_detection4(self):
-        results = self.module.face_detection(
-            images=[cv2.imread('tests/test.jpg')],
-            use_gpu=True,
-            visualization=False
-        )
+        results = self.module.face_detection(images=[cv2.imread('tests/test.jpg')], use_gpu=True, visualization=False)
         bbox = results[0]['data'][0]
 
         label = bbox['label']
@@ -108,7 +93,7 @@ def test_face_detection4(self):
         right = bbox['right']
         top = bbox['top']
         bottom = bbox['bottom']
-        
+
         self.assertEqual(label, 'NO MASK')
         self.assertTrue(confidence > 0.5)
         self.assertTrue(1000 < left < 4000)
@@ -117,18 +102,10 @@ def test_face_detection4(self):
         self.assertTrue(0 < bottom < 2000)
 
     def test_face_detection5(self):
-        self.assertRaises(
-            AssertionError,
-            self.module.face_detection,
-            paths=['no.jpg']
-        )
+        self.assertRaises(AssertionError, self.module.face_detection, paths=['no.jpg'])
 
     def test_face_detection6(self):
-        self.assertRaises(
-            AttributeError,
-            self.module.face_detection,
-            images=['test.jpg']
-        )
+        self.assertRaises(AttributeError, self.module.face_detection, images=['test.jpg'])
 
     def test_save_inference_model(self):
         self.module.save_inference_model('./inference/model')