项目作者: prodeveloper0

项目描述 :
Synthesizing Fingerprint from Pattern Type Analysis Features using cGAN - WITC 2019
高级语言: Python
项目地址: git://github.com/prodeveloper0/UniquePrintV1.git
创建时间: 2019-02-25T04:17:07Z
项目社区:https://github.com/prodeveloper0/UniquePrintV1

开源协议:MIT License

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UniquePrint v1

This is an implemntation of UniquePrintV1. UniquePrintV1 can synthesize the fingerprint from pattern type analysis features (e.g. left, whorl, right, tent arch, arch) using conditional GAN.

Synthesized Fingerprint Images

Paper

Synthesizing Fingerprint from Pattern Type Analysis Features using cGAN

Samuel Lee, Jae-Gab Choi, Jin-Ho Park and Gye-Young Kim

School of Software, Soongsil University

World IT Congress 2019 Jeju (WITC 2019)

Dependencies

  • Python 3.6.7
  • OpenCV-Python 3.4.4.19
  • TensorFlow 1.10.0

Usage

Training

Decompress regularized NIST Special Database 4.

  1. $ cd Resources/nist-sd4/
  2. $ unzip nistsd4.part1.zip
  3. $ unzip nistsd4.part2.zip
  4. $ unzip nistsd4.index.zip

Change opt variable to train in UniquePrintV1.py file.

  1. # Parameters
  2. os.environ['CUDA_VISIBLE_DEVICES'] = '0'
  3. database_path = r'Resources/nist-sd4'
  4. name = 'UniquePrintV1_FingerNet'
  5. opt = 'demo' # Change this to 'train' to train UniquePrintV1
  6. checkpoint_epoch = None
  7. batch_size = 150
  8. epoch = 2000
  9. D_learning_rate = 0.0005
  10. G_learning_rate = 0.0005
  11. max_to_keep = 999

And, Run UniquePrintV1.py

  1. $ python3 UniquePrintV1.py

Testing

Change opt variable to demo in UniquePrintV1.py file after training.

  1. # Parameters
  2. os.environ['CUDA_VISIBLE_DEVICES'] = '0'
  3. database_path = r'Resources/nist-sd4'
  4. name = 'UniquePrintV1_FingerNet'
  5. opt = 'demo' # Change this to 'demo' to demonstrate UniquePrintV1
  6. checkpoint_epoch = None
  7. batch_size = 150
  8. epoch = 2000
  9. D_learning_rate = 0.0005
  10. G_learning_rate = 0.0005
  11. max_to_keep = 999

And, Run UniquePrintV1.py

  1. $ python3 UniquePrintV1.py

Results

Trained 2,000 epoch with NIST Special Database 4.

Sample Images per Epoch
Sample Images per Type

Output images per epoch (Left) and final output images (Right)

Thanks

I referenced some codes from https://github.com/YadiraF/GAN