These scrips are updated ones from the neuralnetworksanddeeplearning.com gitHub repository in order to work with Python 3.5.2
The testing file (test.py) contains all three networks (network.py, network2.py, network3.py) from the book and it is the starting point to run (i.e. train and evaluate) them.
In test.py there are examples of networks configurations with proper comments. I did that to relate with particular chapters from the book.
Please run the following command to setup the samples for the network to be built against:
python generate_samples.py --default_good=1 --default_bad=1 --default_ipsum=1 --default_good_permutations=1 --shuffle_samples=1 --x_size=23 --y_size=23
Please run the following command to compile the samples to the correct format:
python format_samples.py --default_good_permutations=1
Please run the following command (using any specific hyper-parameters you wish):
python setup_network.py 30 30 --default_input=1 --monitor_training=1 --eta=0.84 --lmbda=0.0 --binary_classifier=1 --shuffle_input=1 --default_good_permutations=1 --early_stopping_n=5 --x_size=23 --y_size=23
To run the network on a given image:
python run_evaluation.py network_name image_file_name