FFCNet
FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification
Our paper has been accepted by MICCAI 2022.
Prerequisites
Our code is based on python3.6 and pytorch1.1.
Training the networks
python train_test.py
train_dataset-root: Folder to which you downloaded and extracted the training data
val_datapath-root: Folder to which you downloaded and extracted the val data
record_path: The path where the training results are stored
model_path = The path where the model is stored
best_path = The path where the model with the best result on the validation set is stored
First go into the train_test and adapt all the paths to match your file system and the download locations of training and test sets.
Then python train_test.py to train your dataset.