/SwinMCNet

Primary LanguagePython

MCNet

SwinMCNet: Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection

Prerequisites

Benchmark Datasets

Download the following datasets and unzip them into data folder

The Proposed Dataset

Our proposed RGBT SOD dataset VT723 that contain common challenging scenes of real world.

Training & Testing & Evaluate

  • Split the ground truth into skeleton map and contour map, which will be saved into data/VT5000/skeleton and data/VT5000/contour.
    python3 utils.py
  • Train the model and get the pretrained model, which will be saved into res folder.
    python3 train.py
  • If you just want to evaluate the performance of MCNet without training, please download the pretrained model into res folder.
  • Test the model and get the predicted saliency maps, which will be saved into maps folder.
   python3 test.py
  • Evaluate the predicted results.
    cd eval
    matlab
    main

Saliency maps & Trained model