fix export python path
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db6f83de78
commit
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@ -3,11 +3,16 @@ from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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__dir__ = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(__dir__)
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sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
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import argparse
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import ast
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import copy
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import math
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import os
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import time
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from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
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@ -67,9 +72,7 @@ class OCRDet(hub.Module):
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images.append(img)
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return images
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def predict(self,
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images=[],
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paths=[]):
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def predict(self, images=[], paths=[]):
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"""
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Get the text box in the predicted images.
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Args:
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@ -87,7 +90,7 @@ class OCRDet(hub.Module):
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raise TypeError("The input data is inconsistent with expectations.")
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assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
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all_results = []
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for img in predicted_data:
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if img is None:
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@ -99,11 +102,9 @@ class OCRDet(hub.Module):
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rec_res_final = []
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for dno in range(len(dt_boxes)):
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rec_res_final.append(
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{
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'text_region': dt_boxes[dno].astype(np.int).tolist()
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}
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)
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rec_res_final.append({
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'text_region': dt_boxes[dno].astype(np.int).tolist()
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})
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all_results.append(rec_res_final)
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return all_results
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@ -116,7 +117,7 @@ class OCRDet(hub.Module):
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results = self.predict(images_decode, **kwargs)
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return results
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if __name__ == '__main__':
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ocr = OCRDet()
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image_path = [
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@ -124,4 +125,4 @@ if __name__ == '__main__':
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'./doc/imgs/12.jpg',
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]
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res = ocr.predict(paths=image_path)
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print(res)
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print(res)
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@ -3,11 +3,16 @@ from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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__dir__ = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(__dir__)
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sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
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import argparse
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import ast
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import copy
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import math
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import os
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import time
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from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
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@ -67,9 +72,7 @@ class OCRRec(hub.Module):
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images.append(img)
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return images
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def predict(self,
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images=[],
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paths=[]):
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def predict(self, images=[], paths=[]):
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"""
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Get the text box in the predicted images.
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Args:
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@ -87,31 +90,28 @@ class OCRRec(hub.Module):
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raise TypeError("The input data is inconsistent with expectations.")
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assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
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img_list = []
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for img in predicted_data:
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if img is None:
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continue
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img_list.append(img)
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rec_res_final = []
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try:
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rec_res, predict_time = self.text_recognizer(img_list)
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for dno in range(len(rec_res)):
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text, score = rec_res[dno]
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rec_res_final.append(
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{
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'text': text,
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'confidence': float(score),
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}
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)
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rec_res_final.append({
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'text': text,
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'confidence': float(score),
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})
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except Exception as e:
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print(e)
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return [[]]
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return [rec_res_final]
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@serving
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def serving_method(self, images, **kwargs):
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"""
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@ -121,7 +121,7 @@ class OCRRec(hub.Module):
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results = self.predict(images_decode, **kwargs)
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return results
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if __name__ == '__main__':
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ocr = OCRRec()
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image_path = [
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@ -130,4 +130,4 @@ if __name__ == '__main__':
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'./doc/imgs_words/ch/word_3.jpg',
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]
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res = ocr.predict(paths=image_path)
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print(res)
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print(res)
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@ -3,11 +3,17 @@ from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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__dir__ = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(__dir__)
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sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
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import argparse
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import ast
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import copy
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import math
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import os
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import time
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from paddle.fluid.core import AnalysisConfig, create_paddle_predictor, PaddleTensor
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@ -52,7 +58,7 @@ class OCRSystem(hub.Module):
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)
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cfg.ir_optim = True
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cfg.enable_mkldnn = enable_mkldnn
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self.text_sys = TextSystem(cfg)
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def read_images(self, paths=[]):
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@ -67,9 +73,7 @@ class OCRSystem(hub.Module):
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images.append(img)
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return images
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def predict(self,
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images=[],
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paths=[]):
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def predict(self, images=[], paths=[]):
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"""
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Get the chinese texts in the predicted images.
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Args:
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@ -104,13 +108,11 @@ class OCRSystem(hub.Module):
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for dno in range(dt_num):
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text, score = rec_res[dno]
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rec_res_final.append(
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{
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'text': text,
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'confidence': float(score),
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'text_region': dt_boxes[dno].astype(np.int).tolist()
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}
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)
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rec_res_final.append({
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'text': text,
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'confidence': float(score),
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'text_region': dt_boxes[dno].astype(np.int).tolist()
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})
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all_results.append(rec_res_final)
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return all_results
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@ -123,7 +125,7 @@ class OCRSystem(hub.Module):
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results = self.predict(images_decode, **kwargs)
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return results
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if __name__ == '__main__':
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ocr = OCRSystem()
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image_path = [
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@ -131,4 +133,4 @@ if __name__ == '__main__':
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'./doc/imgs/12.jpg',
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]
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res = ocr.predict(paths=image_path)
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print(res)
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print(res)
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