{"repo":"lartpang/PySODMetrics","free":true,"listed":false,"github":"https://github.com/lartpang/PySODMetrics","clone":"git clone https://github.com/lartpang/PySODMetrics.git","description":"PySODMetrics: A Simple and Efficient Implementation of Grayscale/Binary Segmentation Metrics","language":"Python","stars":449,"topics":["saliency","saliency-detection","saliency-prediction","saliency-methods","metrics","metrics-library","metrics-evaluation","metrics-reported","salient-object-detection","saliency-map"],"license":"MIT","category":"analytics","readme_excerpt":"PySODMetrics: A simple and efficient implementation of SOD metrics [!important] Our exploration in this field continues with PyIRSTDMetrics, a project born from the same core motivation. ​​Think of them as twin initiatives: this project maps the landscape of current evaluation, while its sibling takes the next step to expand upon and rethink it. We'd love your star! 🌟 Introduction A simple and efficient implementation of SOD metrics. - Based on numpy and scipy - Verification based on Fan's matlab code - The code structure is simple and easy to extend - The code is lightweight and fast Your improvements and suggestions are welcome. Citation If you use this library in your research, please consider citing the following paper: 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,si-soft MAE S-measure $S {m}$ soft Smeasure weighted F-measure ($F^{\\omega} {\\beta}$) soft WeightedFmeasure Human Correction Effort Measure soft HumanCorrectionEffortMeasure Context-Measure ($C {\\beta}$, $C^{\\omega} {\\beta}$) soft ContextMeasure , CamouflageContextMeasure Multi-Scale IoU max,avg,adp,bin MSIoU E-measure ($E {m}$) max,avg,adp Emeasure F-measure (old) ($F {\\beta}$) max,avg,adp","default_branch":null,"files":null,"tree":[],"storefront":"/r/lartpang","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/lartpang/PySODMetrics/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}