Installation

# Download the code
git clone https://github.com/PGSmall/DAVIS-Evaluation.git && cd davis2017-evaluation
# Install it - Python 3.6 or higher required
python setup.py install

If you don't want to specify the DAVIS path every time, you can modify the default value in the variable default_davis_path in evaluation_method.py(the following examples assume that you have set it). Otherwise, you can specify the path in every call using using the flag --davis_path /path/to/DAVIS when calling evaluation_method.py.

DAVIS-Evaluation

I modified the source code DAVIS2017-Evaluation, and the revised code can evaluate the davis 2016, 2017 and 2019 datasets.

Evaluate DAVIS 2017 Semi-supervised

In order to evaluate your semi-supervised method in DAVIS 2017, execute the following command substituting results/semi-supervised/osvos by the folder path that contains your results:

python evaluation_method.py --task semi-supervised --results_path results/semi-supervised/osvos --year 2017

The semi-supervised results have been generated using OSVOS.

Evaluate DAVIS 2017 Unsupervised

In order to evaluate your unsupervised method in DAVIS 2017, execute the following command substituting results/unsupervised/rvos by the folder path that contains your results:

python evaluation_method.py --task unsupervised --results_path results/unsupervised/rvos --2017

The unsupervised results example have been generated using RVOS.

Evaluate DAVIS 2016 Unsupervised

In order to evaluate your unsupervised method in DAVIS 2016, execute the following command substituting results/unsupervised/rvos by the folder path that contains your results:

python evaluation_method.py --task unsupervised --results_path results/unsupervised/rvos --2016

The unsupervised results example have been generated using RVOS.

Thanks a lot these issues.