Awesome

This repo is modified according to the initial python2 version

Tools for Evaluating DAVIS Dataset (for Semi-supervised VOS)

Requirements

used packages

You can install them by pip install -r python/requirements.txt
DAVIS dataset

You need to download and unzip the DAVIS2017 trainval dataset to /data. You can run data/get_davis.sh to download it. Only need DAVIS 2017. Evaluation of DAVIS 2016 is also possible

The data structure should be:
```
- data/
  - DAVIS/
    - Annotations
    - JPEGImages
    - ImageSets
    - Scribbles
```

Evaluation Command

Before evaluation, you should add PYTHONPATH:

`export PYTHONPATH=$(pwd)/python/lib`

Evaluate on DAVIS 2017

`python tools/eval.py -i path-to-your-results -o results.yaml --year 2017 --phase val`

Evaluate on DAVIS 2016

`python tools/eval.py -i path-to-your-results -o results.yaml --year 2016 --single-object --phase val`

Code Structure

The directory is structured as follows:

/cpp: Implementation and python wrapper of the temporal stability measure.
/python/tools: contains scripts for evaluating segmentation.
- eval.py : evaluate a technique and store results in HDF5 file
- eval_view.py: read and display evaluation from HDF5.
- visualize.py: visualize segmentation results.
/python/lib/davis : library package contains helper functions for parsing and evaluating DAVIS
/data :
- get_davis.sh: download input images and annotations.

Citation

Please cite DAVIS in your publications if it helps your research:

@inproceedings{Perazzi_CVPR_2016,
  author    = {Federico Perazzi and
               Jordi Pont-Tuset and
               Brian McWilliams and
               Luc Van Gool and
               Markus Gross and
               Alexander Sorkine-Hornung},
  title     = {A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2016}
}

@article{Pont-Tuset_arXiv_2017,
  author  = {Jordi Pont-Tuset and
             Federico Perazzi and
             Sergi Caelles and
             Pablo Arbel\'aez and
             Alexander Sorkine-Hornung and
             Luc {Van Gool}},
  title   = {The 2017 DAVIS Challenge on Video Object Segmentation},
  journal = {arXiv:1704.00675},
  year    = {2017}
}

Terms of Use

DAVIS is released under the BSD License (see LICENSE for details)