Signature Detection

Requirements

1. Python 3.6
2. tensorflow v.1.7.0

Training the model

Prepare the training dataset by segregating the images to categories, real or fake in this case. The folder structure looks like below.

  ├── tf_files          
  │   ├── signatures   
  │       ├── real      
  │       ├── fake            
  └── ...

To begin the training process, execute the following script,

python -m scripts.retrain \
--bottleneck_dir=/tf_files/bottlenecks \
--model_dir=/tf_files/inception \
--output_graph=/tf_files/retrained_graph.pb \
--output_labels=/tf_files/retrained_labels.txt \
--image_dir /tf_files/signatures

Testing the model

To test the model run,

python -m scripts.label_image --graph=tf_files/retrained_graph.pb --image=< path to test image>