/mlcv-readme-template

A template README/workflow for any ML based research project.

Project Acronym

Concordia University, Decathlon

Hasib Zunair

[Paper] [Project] [Demo] [BibTeX]

This is official code for our BMVC 2022 paper:
Title of Your Paper

MaskSup Design

Summarize in 3-5 sentences your project here.

1. Specification of dependencies

This code requires Python YOUR_PYTHON_VERSION and CUDA YOUR_CUDA_VERSION. Clone the project repository, then create and activate the following conda envrionment.

# clone repo
git clone https://github.com/hasibzunair/mlcv-readme-template
cd peekaboo
# create env
conda update conda
conda env create -f environment.yml
conda activate myenv

Or, you can also create a fresh environment and install the project requirements inside that environment by:

# clone repo
git clone https://github.com/hasibzunair/mlcv-readme-template
cd peekaboo
# create fresh env
conda create -n myenv python=3.8     
conda activate myenv
# install reqs
pip install -r requirements.txt

2a. Training code

Dataset details

We expect Dataset1 and Dataset2 datasets to have the following structure:

datasets/
|-- Dataset1/
|---- VOC2007/
|------ JPEGImages/
|------ Annotations/
|------ ImageSets/
......
|-- Dataset2/
|---- annotations/
|---- images/
|------ train2014/
|------ val2014/
...

Add any intructions for pre-processing data, to make it ready for training.

Dataset1 training

python train.py --dataset Dataset1

Dataset2 training

python train.py --dataset Dataset2

2b. Evaluation code

Dataset1 eval

python eval.py --dataset Dataset1

Dataset2 eval

python eval.py --dataset Dataset2

Refer to supplementary materials if any.

3. Pre-trained models

We provide pretrained models on GitHub Releases for reproducibility.

Dataset Backbone mIoU(%) Download
GLaS LeViT-UNet 384 76.06 download
Kvasir & CVC-ClinicDB LeViT-UNet 384 84.02 download
NYUDv2 U-Net++ 39.31 download

4. Demo

Add demo details here.

5. Citation

If you use X in your research, please use the following BibTeX entry.

 @inproceedings{zunair2022masked,
    title={Masked Supervised Learning for Semantic Segmentation},
    author={Zunair, Hasib and Hamza, A Ben},
    booktitle={Proc. British Machine Vision Conference},
    year={2022}
  }

Project Notes

Click to view

[July 12, 2022] Added this fancy drop down!

[March 22, 2022] I started making this template for my own reference.

Acknowledgements

Give credits to codebases you built on!

Useful resources