python3 label_image.py
python3 -m scripts.retrain \
--bottleneck_dir=tf_files/bottlenecks \
--how_many_training_steps=500 \
--model_dir=tf_files/models/ \
--summaries_dir=tf_files/training_summaries/"${ARCHITECTURE}" \
--output_graph=tf_files/retrained_graph.pb \
--output_labels=tf_files/retrained_labels.txt \
--architecture="${ARCHITECTURE}" \
--image_dir=CXR
python3 -m scripts.retrain \
--bottleneck_dir=tf_files/bottlenecks \
--learning_rate=0.001 \
--how_many_training_steps=5000 \
--model_dir=tf_files/models/ \
--summaries_dir=tf_files/training_summaries/"${ARCHITECTURE}" \
--output_graph=tf_files/retrained_graph.pb \
--output_labels=tf_files/retrained_labels.txt \
--architecture="${ARCHITECTURE}" \
--image_dir=/CXR
Library: https://github.com/googlecodelabs/tensorflow-for-poets-2
Data set: https://ceb.nlm.nih.gov/repositories/tuberculosis-chest-x-ray-image-data-sets/