Signature Detection
Requirements
- Python 3.6
- 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>