Uncertainty Estimation on Histopathological Slides with Pytorch Lightning

Setup data

1. Download Camlyon17 slides from https://camelyon17.grand-challenge.org/Data/

2. From CAMELYON17/training extract the 50 slides with lesion-level annotations contained in lesion_annotations.zip

3. Generate tiles by using the preprocessing pipeline from https://github.com/DBO-DKFZ/wsi_preprocessing v0.1
   Use the config provided under configs/preprocessing/config.json and set the correct paths for slides, annotations and output

Setup system

1. Set the system's path variables for "DATASET_LOCATION" and "EXPERIMENT_LOCATION". One way is to insert the following lines into your .bashrc file:

export DATASET_LOCATION=YOUR_PATH 
export EXPERIMENT_LOCATION=YOUR_PATH

Setup repo

1. Install Miniconda

2. Create conda environment
   conda env create -f environment.yml

3. Run train script
   Example: python train.py --config configs/final/strong/resnet.yaml
   The train script by default runs evaluation on the best performing model checkpoint. Predicitions on test splits are stored in {env:EXPERIMENT_LOCATION}/RUN_NAME/VERSION/predictions/