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nCPS++: A Cross-pseudo Supervised Transformer-based Neural Networks for Colorectal Polyp Semantic Segmentation

Requirements

  • Unbuntu 20.04
  • Python 3.7
  • Anaconda 4.12.x

Installation

First, clone this repository:

git clone https://github.com/bui-thanh-lam/cps-segment.git

and checkout to the root directory of this project.

Then, create a new Anaconda virtual environment with Python 3.7:

conda create python=3.7 --name n-cps
conda activate n-cps

Install dependencies:

pip install -r requirements.txt

Download all datasets from this link: https://drive.google.com/drive/folders/1dnpp7xPRWX3-Qw2cmx8Q2OJR5oQw62AI?usp=sharing and place them to the desired path.

Usage

  1. Train a new model

Command example:

python train.py --model_config segformer_b1 --out_dir ../checkpoints/segformer_b1

You should learn about the hyperparemters with:

python train.py -h
  1. Evaluate a trained model

Command example:

python evaluate.py --model_config segformer_b1 --checkpoint_path ../checkpoints/segformer_b1

You should learn about the hyperparemters with:

python evaluation.py -h

An example of checkpoints can be found in: https://drive.google.com/drive/folders/127WfdW8vw4Sb75bBKGNoiUyEHKISFhIw?usp=sharing