This repository contains only the OCR unit that is used in this repository.
Please use Anaconda or miniconda for installation.
To run this model, you would need the following steps:
conda env create -f environment.ymlwget http://ptak.felk.cvut.cz/public_datasets/SyntText/e2e-mlt.h5conda activate ocr
OR
simply run:
bash setup.shconda activate ocr
make sure that you have a GPU
now you have 2 choices.
Run the OCR on images present in input_data and save the output in output_data:
bash start.sh
Please Note: the format in which the recognition result is saved is:
<image_name>_<recogintion_result>.png
Example:
if your image name is: img_1.jpg, and your recognition result is: hello_world.
The output image name would be: img_1_hello_world.png.
how to run images present in some random <input_image_path> and store output in some random <output_image_path>?
to do this instead of bash start.sh run: python eval.py -input-path=your_random_image_path -output_path=your_random_image_path
@article{buvsta2018e2e,
title={E2E-MLT-an unconstrained end-to-end method for multi-language scene text},
author={Bu{\v{s}}ta, Michal and Patel, Yash and Matas, Jiri},
journal={arXiv preprint arXiv:1801.09919},
year={2018}
}