Merge pull request #1025 from littletomatodonkey/dev/fix_hb_export

fix export python path

deploy/hubserving/ocr_det/module.py

@@ -3,11 +3,14 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import os
+import sys
+sys.path.insert(0, ".")
+
 import argparse
 import ast
 import copy
 import math
-import os
 import time
 
 from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
@@ -67,9 +70,7 @@ class OCRDet(hub.Module):
             images.append(img)
         return images
 
-    def predict(self,
-                images=[],
-                paths=[]):
+    def predict(self, images=[], paths=[]):
         """
         Get the text box in the predicted images.
         Args:
@@ -87,7 +88,7 @@ class OCRDet(hub.Module):
             raise TypeError("The input data is inconsistent with expectations.")
 
         assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
-        
+
         all_results = []
         for img in predicted_data:
             if img is None:
@@ -99,11 +100,9 @@ class OCRDet(hub.Module):
 
             rec_res_final = []
             for dno in range(len(dt_boxes)):
-                rec_res_final.append(
-                    {
-                        'text_region': dt_boxes[dno].astype(np.int).tolist()
-                    }
-                )
+                rec_res_final.append({
+                    'text_region': dt_boxes[dno].astype(np.int).tolist()
+                })
             all_results.append(rec_res_final)
         return all_results
 
@@ -116,7 +115,7 @@ class OCRDet(hub.Module):
         results = self.predict(images_decode, **kwargs)
         return results
 
-   
+
 if __name__ == '__main__':
     ocr = OCRDet()
     image_path = [
@@ -124,4 +123,4 @@ if __name__ == '__main__':
         './doc/imgs/12.jpg',
     ]
     res = ocr.predict(paths=image_path)
-    print(res)
\ No newline at end of file
+    print(res)

deploy/hubserving/ocr_rec/module.py

@@ -3,11 +3,14 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import os
+import sys
+sys.path.insert(0, ".")
+
 import argparse
 import ast
 import copy
 import math
-import os
 import time
 
 from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
@@ -67,9 +70,7 @@ class OCRRec(hub.Module):
             images.append(img)
         return images
 
-    def predict(self,
-                images=[],
-                paths=[]):
+    def predict(self, images=[], paths=[]):
         """
         Get the text box in the predicted images.
         Args:
@@ -87,31 +88,28 @@ class OCRRec(hub.Module):
             raise TypeError("The input data is inconsistent with expectations.")
 
         assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
-        
+
         img_list = []
         for img in predicted_data:
             if img is None:
                 continue
             img_list.append(img)
-            
+
         rec_res_final = []
         try:
             rec_res, predict_time = self.text_recognizer(img_list)
             for dno in range(len(rec_res)):
                 text, score = rec_res[dno]
-                rec_res_final.append(
-                    {
-                        'text': text,
-                        'confidence': float(score),
-                    }
-                )
+                rec_res_final.append({
+                    'text': text,
+                    'confidence': float(score),
+                })
         except Exception as e:
             print(e)
             return [[]]
 
         return [rec_res_final]
 
-
     @serving
     def serving_method(self, images, **kwargs):
         """
@@ -121,7 +119,7 @@ class OCRRec(hub.Module):
         results = self.predict(images_decode, **kwargs)
         return results
 
-   
+
 if __name__ == '__main__':
     ocr = OCRRec()
     image_path = [
@@ -130,4 +128,4 @@ if __name__ == '__main__':
         './doc/imgs_words/ch/word_3.jpg',
     ]
     res = ocr.predict(paths=image_path)
-    print(res)
\ No newline at end of file
+    print(res)

deploy/hubserving/ocr_system/module.py

@@ -3,11 +3,14 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import os
+import sys
+sys.path.insert(0, ".")
+
 import argparse
 import ast
 import copy
 import math
-import os
 import time
 
 from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
@@ -52,7 +55,7 @@ class OCRSystem(hub.Module):
                 )
         cfg.ir_optim = True
         cfg.enable_mkldnn = enable_mkldnn
-        
+
         self.text_sys = TextSystem(cfg)
 
     def read_images(self, paths=[]):
@@ -67,9 +70,7 @@ class OCRSystem(hub.Module):
             images.append(img)
         return images
 
-    def predict(self,
-                       images=[],
-                       paths=[]):
+    def predict(self, images=[], paths=[]):
         """
         Get the chinese texts in the predicted images.
         Args:
@@ -104,13 +105,11 @@ class OCRSystem(hub.Module):
 
             for dno in range(dt_num):
                 text, score = rec_res[dno]
-                rec_res_final.append(
-                    {
-                        'text': text,
-                        'confidence': float(score),
-                        'text_region': dt_boxes[dno].astype(np.int).tolist()
-                    }
-                )
+                rec_res_final.append({
+                    'text': text,
+                    'confidence': float(score),
+                    'text_region': dt_boxes[dno].astype(np.int).tolist()
+                })
             all_results.append(rec_res_final)
         return all_results
 
@@ -123,7 +122,7 @@ class OCRSystem(hub.Module):
         results = self.predict(images_decode, **kwargs)
         return results
 
-   
+
 if __name__ == '__main__':
     ocr = OCRSystem()
     image_path = [
@@ -131,4 +130,4 @@ if __name__ == '__main__':
         './doc/imgs/12.jpg',
     ]
     res = ocr.predict(paths=image_path)
-    print(res)
\ No newline at end of file
+    print(res)

deploy/hubserving/readme.md

@@ -29,12 +29,6 @@ deploy/hubserving/ocr_system/
 ```shell
 # 安装paddlehub  
 pip3 install paddlehub --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple
-
-# 在Linux下设置环境变量
-export PYTHONPATH=.
-
-# 或者，在Windows下设置环境变量
-SET PYTHONPATH=.
 ```
 
 ### 2. 下载推理模型

deploy/hubserving/readme_en.md

 English | [简体中文](readme.md)
 
-PaddleOCR provides 2 service deployment methods: 
-- Based on **PaddleHub Serving**: Code path is "`./deploy/hubserving`". Please follow this tutorial. 
+PaddleOCR provides 2 service deployment methods:
+- Based on **PaddleHub Serving**: Code path is "`./deploy/hubserving`". Please follow this tutorial.
 - Based on **PaddleServing**: Code path is "`./deploy/pdserving`". Please refer to the [tutorial](../../doc/doc_ch/serving_inference.md) for usage.
 
 # Service deployment based on PaddleHub Serving  
@@ -30,12 +30,6 @@ The following steps take the 2-stage series service as an example. If only the d
 ```shell
 # Install paddlehub  
 pip3 install paddlehub --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple
-
-# Set environment variables on Linux
-export PYTHONPATH=.
-
-# Set environment variables on Windows
-SET PYTHONPATH=.
 ```
 
 ### 2. Download inference model