https://github.com/getcontrol/kyc-train-model

Train TensorFlow model for KYC
https://github.com/getcontrol/kyc-train-model

kyc midv-500 python tensorflow tensorflow-examples tensorflow-models

Last synced: about 1 month ago
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Train TensorFlow model for KYC

• Host: GitHub
• URL: https://github.com/getcontrol/kyc-train-model
• Owner: getcontrol
• Created: 2020-03-02T18:09:52.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T03:43:35.000Z (almost 2 years ago)
• Last Synced: 2024-10-10T08:43:42.803Z (about 1 month ago)
• Topics: kyc, midv-500, python, tensorflow, tensorflow-examples, tensorflow-models
• Language: Python
• Size: 63.4 MB
• Stars: 32
• Watchers: 3
• Forks: 9
• Open Issues: 11
• Metadata Files:
  • Readme: README.md

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README

        
# 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](https://github.com/getcontrol/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```

![Results](https://github.com/getcontrol/KYC-train-model/blob/master/model-result.png)

### 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}

    }