Treble-Transformer

Quick start

1. Install CUDA

2. Install PyTorch

3. Install dependencies

pip install -r requirements.txt

4. Preparing datasets and pre-training models

(1) If training, validation and testing are done on the same dataset (Kvasir or CVC-ClinicDB is recommended for this dataset), put the dataset into "./data1", and train_with_data1.py will automatically split the dataset into training, validation and testing according to 8:1:1.
(2) The datasets used in this study are publicly available at:
Kvasir-SEG: https://datasets.simula.no/kvasir-seg/.
CVC-ClinicDB: https://polyp.grand-challenge.org/CVCClinicDB/.
(3) Pre-training models should be downloaded via their github connection and placed in location "./Models" after downloading.
https://github.com/microsoft/Swin-Transformer
https://github.com/whai362/PVT
https://github.com/zengjixiangnfft/ESFPNet (Not official MixTransformer, but ESFPNet is excellent!) \

5. run training:

python train.py