fix export python path

deploy/hubserving/ocr_det/module.py

@@ -3,11 +3,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import os
+import sys
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
+
 import argparse
 import ast
 import copy
 import math
-import os
 import time
 
 from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
@@ -67,9 +72,7 @@ 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 +90,7 @@ 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 +102,9 @@ 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 +117,7 @@ class OCRDet(hub.Module):
         results = self.predict(images_decode, **kwargs)
         return results
 
-   
+
 if __name__ == '__main__':
     ocr = OCRDet()
     image_path = [
@@ -124,4 +125,4 @@ if __name__ == '__main__':
         './doc/imgs/12.jpg',
     ]
     res = ocr.predict(paths=image_path)
-    print(res)
+    print(res)

deploy/hubserving/ocr_rec/module.py

@@ -3,11 +3,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import os
+import sys
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
+
 import argparse
 import ast
 import copy
 import math
-import os
 import time
 
 from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
@@ -67,9 +72,7 @@ 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 +90,28 @@ 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 +121,7 @@ class OCRRec(hub.Module):
         results = self.predict(images_decode, **kwargs)
         return results
 
-   
+
 if __name__ == '__main__':
     ocr = OCRRec()
     image_path = [
@@ -130,4 +130,4 @@ if __name__ == '__main__':
         './doc/imgs_words/ch/word_3.jpg',
     ]
     res = ocr.predict(paths=image_path)
-    print(res)
+    print(res)

deploy/hubserving/ocr_system/module.py

@@ -3,11 +3,17 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import os
+import sys
+
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
+
 import argparse
 import ast
 import copy
 import math
-import os
 import time
 
 from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
@@ -52,7 +58,7 @@ 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 +73,7 @@ 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 +108,11 @@ 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 +125,7 @@ class OCRSystem(hub.Module):
         results = self.predict(images_decode, **kwargs)
         return results
 
-   
+
 if __name__ == '__main__':
     ocr = OCRSystem()
     image_path = [
@@ -131,4 +133,4 @@ if __name__ == '__main__':
         './doc/imgs/12.jpg',
     ]
     res = ocr.predict(paths=image_path)
-    print(res)
+    print(res)