• oxnnet_core is a light weight python program designed to be extended to create more complex neural networks for patch based image analysis
• Version 0.01

Create a set of test cases

python3 -m tests.utils ~/Desktop/TestVolumes

Write out the TensorFlowRecords

python3 main.py --model oxnnet.model.simplenet write --save_dir ~/Desktop/TestRect-tfr --data_dir ~/Desktop/TestVolumes/

Train the model

python3 main.py --model oxnnet.model.simplenet train --tfr_dir ~/Desktop/TestRect-tfr --save_dir ~/Desktop/TestRect-out --num_epochs 10 --batch_size 100

Test the model

python3 main.py --model oxnnet.model.simplenet test --save_dir ~/Desktop/TestRect-out/test --test_data_file ~/Desktop/TestRect-tfr/meta_data.txt --model_file ~/Desktop/TestRect-out/epoch_model.ckpt-<iteration_no> --batch_size 100

Dependencies

tflearn (v0.3), tensorflow (v1.5), pandas, nibabel

Python 3.5 recommended.

** How to run tests **

python3 -m unittest