pip install -r requirements.txt
meta
"dicom_id": {"img_path_jpg", "img_path_dcm", "transcript_egd", "gaze_egd", "transcript_reflacx", "gaze_reflacx"}
Try using the script in data_generator
or download mnist data (.csv) from https://github.com/pjreddie/mnist-csv-png
and save it same as the paths in configs/train/sample.yaml
.
Remember to set env variable before run the train.py script, and change the trainer logger to Neptune logger (currently we are using neptune logger)
export NEPTUNE_API_TOKEN="<key>"
python train.py --config configs/train/sample.yaml --gpus 0
Or if you want a quick test, change the neptune logger in the trainer to tensorboard and run this:
python train.py --config configs/train/sample.yaml --gpus 0
tensorboard --logdir=runs
{
dicom_id: [caption_1, caption_2, ...]
}