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PySODMetrics: A Simple and Efficient Implementation of Grayscale/Binary Segmentation Metrcis

Home Page: https://pypi.org/project/pysodmetrics/

License: MIT License

Python 100.00%
saliency saliency-detection saliency-prediction saliency-methods metrics metrics-library metrics-evaluation metrics-reported salient-object-detection saliency-map

pysodmetrics's Introduction

Logo

PySODMetrics: A simple and efficient implementation of SOD metrics

Introduction

A simple and efficient implementation of SOD metrics.

Your improvements and suggestions are welcome.

Related Projects

  • PySODEvalToolkit: A Python-based Evaluation Toolbox for Salient Object Detection and Camouflaged Object Detection

Supported Metrics

Metric Sample-based Whole-based Related Class
MAE soft MAE
S-measure $S_{m}$ soft Smeasure
weighted F-measure ($F^{\omega}_{\beta}$) soft WeightedFmeasure
Multi-Scale IoU bin MSIoU
E-measure ($E_{m}$) max,avg,adp Emeasure
F-measure (old) ($F_{beta}$) max,avg,adp Fmeasure
F-measure (new) ($F_{beta}$, $F_{1}$) max,avg,adp,bin bin FmeasureV2+FmeasureHandler
BER max,avg,adp,bin bin FmeasureV2+BERHandler
Dice max,avg,adp,bin bin FmeasureV2+DICEHandler
FPR max,avg,adp,bin bin FmeasureV2+FPRHandler
IoU max,avg,adp,bin bin FmeasureV2+IOUHandler
Kappa max,avg,adp,bin bin FmeasureV2+KappaHandler
Overall Accuracy max,avg,adp,bin bin FmeasureV2+OverallAccuracyHandler
Precision max,avg,adp,bin bin FmeasureV2+PrecisionHandler
Recall max,avg,adp,bin bin FmeasureV2+RecallHandler
Sensitivity max,avg,adp,bin bin FmeasureV2+SensitivityHandler
Specificity max,avg,adp,bin bin FmeasureV2+SpecificityHandler
TNR max,avg,adp,bin bin FmeasureV2+TNRHandler
TPR max,avg,adp,bin bin FmeasureV2+TPRHandler

Usage

The core files are in the folder py_sod_metrics.

  • [Latest, but may be unstable] Install from the source code: pip install git+https://github.com/lartpang/PySODMetrics.git
  • [More stable] Install from PyPI: pip install pysodmetrics

Examples

Reference

@inproceedings{Fmeasure,
    title={Frequency-tuned salient region detection},
    author={Achanta, Radhakrishna and Hemami, Sheila and Estrada, Francisco and S{\"u}sstrunk, Sabine},
    booktitle=CVPR,
    number={CONF},
    pages={1597--1604},
    year={2009}
}

@inproceedings{MAE,
    title={Saliency filters: Contrast based filtering for salient region detection},
    author={Perazzi, Federico and Kr{\"a}henb{\"u}hl, Philipp and Pritch, Yael and Hornung, Alexander},
    booktitle=CVPR,
    pages={733--740},
    year={2012}
}

@inproceedings{Smeasure,
    title={Structure-measure: A new way to evaluate foreground maps},
    author={Fan, Deng-Ping and Cheng, Ming-Ming and Liu, Yun and Li, Tao and Borji, Ali},
    booktitle=ICCV,
    pages={4548--4557},
    year={2017}
}

@inproceedings{Emeasure,
    title="Enhanced-alignment Measure for Binary Foreground Map Evaluation",
    author="Deng-Ping {Fan} and Cheng {Gong} and Yang {Cao} and Bo {Ren} and Ming-Ming {Cheng} and Ali {Borji}",
    booktitle=IJCAI,
    pages="698--704",
    year={2018}
}

@inproceedings{wFmeasure,
  title={How to evaluate foreground maps?},
  author={Margolin, Ran and Zelnik-Manor, Lihi and Tal, Ayellet},
  booktitle=CVPR,
  pages={248--255},
  year={2014}
}

@inproceedings{MSIoU,
    title = {Multiscale IOU: A Metric for Evaluation of Salient Object Detection with Fine Structures},
    author = {Ahmadzadeh, Azim and Kempton, Dustin J. and Chen, Yang and Angryk, Rafal A.},
    booktitle = ICIP,
    year = {2021},
}

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pysodmetrics's Issues

The running error in linux

Traceback (most recent call last):
File "test_metrics.py", line 29, in
FM.step(pred=pred, gt=mask)
File "/usr/local/lib/python3.6/dist-packages/py_sod_metrics/sod_metrics.py", line 65, in step
pred, gt = _prepare_data(pred, gt)
File "/usr/local/lib/python3.6/dist-packages/py_sod_metrics/sod_metrics.py", line 21, in _prepare_data
gt = gt > 128
TypeError: '>' not supported between instances of 'NoneType' and 'int'

How can I fix it?

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