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DocUNet: Document Image Unwarping via A Stacked U-Net

paper zhihu

how to run

  1. prepare some scans and background images
  2. use flow scipt to generated some images and labels
python3 data_generator/generator.py -i scan_images_path -b background_images_path -o output_path
  1. change trainroot in config.py
  2. use flow scipt to train
python3 train.py

how to eval

  1. change model_path and img_path in predict.py
  2. use flow scipt to train
python3 predict.py

generated images sample

data

result

result on training data

left:input, right output result1

result on really data

left:output, right input result1

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This is a pytorch implementation of DocUNet: Document Image Unwarping via A Stacked U-Net

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  • Jupyter Notebook 57.4%
  • Python 19.5%
  • C++ 11.0%
  • Makefile 4.8%
  • C 3.9%
  • CMake 3.4%