Binary-Segmentation-Evaluation-Tool
This repo is developed for the evaluation of binary image segmentation results.
The Code was used for evaluation in CVPR 2019 paper 'BASNet: Boundary-Aware Salient Object Detection code', Xuebin Qin, Zichen Zhang, Chenyang Huang, Chao Gao, Masood Dehghan and Martin Jagersand.
Contact: xuebin[at]ualberta[dot]ca
Required libraries
Python 3.6.6 (version newer than 3.0)
numpy 1.15.2
scikit-image 0.14.0
matplotlib 2.2.3
Usage
Please follow the scripts in quan_eval_demo.py
Implemented measures
-
MAE Mean Absolute Error
-
Precision, Recall, F-measure (This is the python implementation of algorithm in sal_eval_toolbox)
-
Precision-recall curves
- F-measure curves
Future measures
IoU Intersection-over-Union
relax boundary F-measure
...
Citation
@InProceedings{Qin_2019_CVPR,
author = {Qin, Xuebin and Zhang, Zichen and Huang, Chenyang and Gao, Chao and Dehghan, Masood and Jagersand, Martin},
title = {BASNet: Boundary-Aware Salient Object Detection},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}