This is the Python API code for the amodal segmentation dataset proposed in Semantic Amodal Segmentation (CVPR 2017). This API code is built on COCO API.
- git clone and compile:
git clone https://github.com/wakeupbuddy/amodalAPI
cd PythonAPI; python setup.py build_ext install; cd ..
- create soft link for coco/bsds images:
ln -s /your/coco/images ./images
ln -s /your/bsds/images ./bsds_images
- dowload annotation files and untar.
- To see the annotation and some useful APIs, please run the ipython notebook demo.
-
dowload the baseline amodalMask output on coco val set and untar:
-
run the segmentation evaluation.
bash eval.sh
It measures amodal segment proposal quality using average recall. Please see details in table 3a and section 5.1 from the paper.
We also release the web tool we used for annotation in another repo here. It's modified based on OpenSurface.
If you find this dataset useful to your research, please consider citing:
@inproceedings{zhu2017semantic,
Author = {Zhu, Yan and Tian, Yuandong and Mexatas, Dimitris and Doll{\'a}r, Piotr},
Title = {Semantic Amodal Segmentation},
Booktitle = {Conference on Computer Vision and Pattern Recognition ({CVPR})},
Year = {2017}
}