Package: pysodmetrics
PySODMetrics: A simple and efficient implementation of SOD metricsIntroductionA simple and efficient implementation of SOD metrics.Based onnumpyandscipyVerification based on Fan's matlab codehttps://github.com/DengPingFan/CODToolboxThe code structure is simple and easy to extendThe code is lightweight and fastYour improvements and suggestions are welcome.Related ProjectsPySODEvalToolkit: A Python-based Evaluation Toolbox for Salient Object Detection and Camouflaged Object DetectionSupported MetricsMetricSample-basedWhole-basedRelated ClassMAEsoftMAES-measure $S_{m}$softSmeasureweighted F-measure ($F^{\omega}_{\beta}$)softWeightedFmeasureMulti-Scale IoUbinMSIoUE-measure ($E_{m}$)max,avg,adpEmeasureF-measure (old) ($F_{beta}$)max,avg,adpFmeasureF-measure (new) ($F_{beta}$, $F_{1}$)max,avg,adp,binbinFmeasureV2+FmeasureHandlerBERmax,avg,adp,binbinFmeasureV2+BERHandlerDicemax,avg,adp,binbinFmeasureV2+DICEHandlerFPRmax,avg,adp,binbinFmeasureV2+FPRHandlerIoUmax,avg,adp,binbinFmeasureV2+IOUHandlerKappamax,avg,adp,binbinFmeasureV2+KappaHandlerOverall Accuracymax,avg,adp,binbinFmeasureV2+OverallAccuracyHandlerPrecisionmax,avg,adp,binbinFmeasureV2+PrecisionHandlerRecallmax,avg,adp,binbinFmeasureV2+RecallHandlerSensitivitymax,avg,adp,binbinFmeasureV2+SensitivityHandlerSpecificitymax,avg,adp,binbinFmeasureV2+SpecificityHandlerTNRmax,avg,adp,binbinFmeasureV2+TNRHandlerTPRmax,avg,adp,binbinFmeasureV2+TPRHandlerUsageThe core files are in the folderpy_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 pysodmetricsExamplesexamples/test_metrics.pyexamples/metric_recorder.pyReferenceMatlab Codeby DengPingFan(https://github.com/DengPingFan): In our comparison (the test code can be seen under thetestfolder), the result is consistent with the code.The matlab code needs to changeBi_sal(sal>threshold)=1;toBi_sal(sal>=threshold)=1;inhttps://github.com/DengPingFan/CODToolbox/blob/910358910c7824a4237b0ea689ac9d19d1958d11/Onekey_Evaluation_Code/OnekeyEvaluationCode/main.m#L102. For related discussion, please seethe issue.2021-12-20 (version1.3.0): Due to the difference between numpy and matlab, in version1.2.x, there are very slight differences on some metrics between the results of the matlab code and ours. Therecent PRalleviated this problem. However, there are still very small differences on E-measure. The results in most papers are rounded off to three or four significant figures, so, there is no obvious difference between the new version and the version1.2.xfor them.https://en.wikipedia.org/wiki/Precision_and_recall@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},
}