Scribble-supervised version of OSVOS, a baseline for DAVIS Interactive Challenge
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README.md

Scribble-OSVOS

This repository contains a baseline for the interactive track of the DAVIS Challenge on Video Object Segmentation Wokshop held in CVPR 2018.

This PyTorch code is based on the original OSVOS-Pytorch implementation. It adapts the orignal OSVOS to train only on scribbles instead of the full mask.

Installation:

The code was tested with Miniconda and Python 3.6. After installing the Miniconda environment:

  1. Clone the repo:

    git clone https://github.com/kmaninis/Scribble-OSVOS
    cd Scribble-OSVOS
  2. Install dependencies:

    conda install pytorch=0.3.1 torchvision -c pytorch  # 
    conda install matplotlib opencv pillow scikit-learn scikit-image
  3. Install the DAVIS interactive package following these instructions ('PyPi Install' section), and download the scribbles ('DAVIS Dataset' section).

  4. Download the model by running the script inside models/:

    cd models/
    chmod +x download_osvos_parent.sh
    ./download_osvos_parent.sh
    cd ..
  5. Edit the path to DAVIS 2017 in mypath.py

  6. Modify any parameters in demo_interactive.py (for example the gpu_id).

  7. To run the interactive session (with the default parameters it takes ~10 hours on a Titan Xp):

    python demo_interactive.py
  8. A CSV report with all the metrics will be generated in results. The expected output after running all sequences can be found at results/result_default_settings.csv. analyze_report.py will generate an overall report of the results.

Enjoy!

Citation:

@Inproceedings{Caelles_arXiv_2018,
  Title          = {The 2018 DAVIS Challenge on Video Object Segmentation},
  Author         = {Sergi Caelles and Alberto Montes and Kevis-Kokitsi Maninis and Yuhua Chen and Luc {Van Gool} and Federico Perazzi and Jordi Pont-Tuset},
  journal        = {arXiv:1803.00557},
  Year           = {2018}
}

If you encounter any problems with the code, want to report bugs, etc. please open an issue or contact us at {kmaninis, scaelles}[at]vision[dot]ee[dot]ethz[dot]ch.