Train Tensorflow Model for Tensorflow Verification

This repo contains the Python code to produce the dataset and train the Tensorflow model for use in KYC-tensorflow. This training model transfers learning from a previously trained model mobilenet_v2.

Installation Instructions

1. Clone the repo.

git clone https://github.com/getcontrol/KYC-train-model

cd KYC-train-model

2. Download and unzip the the MIDV-500 formatted dataset to 'verification-train-model' directory.

https://www.dropbox.com/s/dmjbat0e1re5rkf/midv_500.zip?dl=0

3. Make a 'data' directory in verification-train-model for the dataset generation and an 'output' folder for testing.

mkdir data

mkdir output

4. Create and activate a Python 3 Virtual environment.

python3 -m venv env

source env/bin/activate

5. Install Requirements.

pip install -r requirements.txt

6. Synthesize training data.

python synthesis_data.py

python receipt_dataset.py

7. Train model.

python train.py

Test Model

Samples are included in 'test_samples_600*800'.

python test.py

Citation

Please cite this paper, if using midv dataset, link for dataset provided in paper

@article{DBLP:journals/corr/abs-1807-05786,
  author    = {Vladimir V. Arlazarov and
               Konstantin Bulatov and
               Timofey S. Chernov and
               Vladimir L. Arlazarov},
  title     = {{MIDV-500:} {A} Dataset for Identity Documents Analysis and Recognition
               on Mobile Devices in Video Stream},
  journal   = {CoRR},
  volume    = {abs/1807.05786},
  year      = {2018},
  url       = {http://arxiv.org/abs/1807.05786},
  archivePrefix = {arXiv},
  eprint    = {1807.05786},
  timestamp = {Mon, 13 Aug 2018 16:46:35 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1807-05786},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}