All training and independent datasets are given in Dataset folder and Bladder Cancer

OS: Pop!_OS 22.04 LTS

Python version: Python 3.9.19

Used libraries:

numpy==1.26.4
pandas==2.2.1
pytorch==2.4.1
xgboost==2.0.3
pickle5==0.0.11
scikit-learn==1.2.2
matplotlib==3.8.2
timm==1.0.11
torchvision==0.19.1
pillow==10.4.0
huggingface-hub==0.24.6
torcheval==0.0.7
opencv-python==4.10.0.84
scikit-image==0.24.0

1. Reproducable codes are given. Training, validation and testing scripts are also provided in Training, Validation and Testing folders respectively. See the examples with 'sample_1.png', 'sample_2.png', 'sample_3.png' and 'sample_4.png'.
2. Additional files that were not given due to the size, are provided in Google drive

Firsly, you need to add the image file in Prediction folder. Then, run the predict.py file.

Firsly, you need to add the image file in Heatmap folder. Then, run the main.py file.

In prev_paper, scripts are provided for reproducing the results of the previous papers.