Module for utilizing Detectron 2 to train models on radiological images.

• Requirements to recreate environment.
• Detectron2 0.4 (version relevant to your Cuda version and pytorch version)

• Data should be present as processed .png's in chosen directories specified in flags.
• Example of data directory structure and form.
• Include test_meta.csv if you wish to predict on testset.

• flags_dict has temporarily been shifted to the main script
• Any other changes to be made to Detectron 2 config should be added to Flags class first.

python Detectron2_train/detectron2_train.py

• Some linux servers may require switching off torch.cuda.synchronize calls in Loss Hook and Detectron2 Evaluator
• Change Device flag and directories.

• If left uncommented, after training is completed, metrics.json from output directory will be used to generate loss curves and AP values if validation set is present.
• Predictions on test set in requisite Kaggle submissions format will automatically be generated.
• From the formed csv submission, annotations will be drawn on sample with confidence bounds on BBs.