{"repo":"rafaelpadilla/Object-Detection-Metrics","free":true,"listed":false,"github":"https://github.com/rafaelpadilla/Object-Detection-Metrics","clone":"git clone https://github.com/rafaelpadilla/Object-Detection-Metrics.git","description":"Most popular metrics used to evaluate object detection algorithms.","language":"Python","stars":5101,"topics":["metrics","object-detection","average-precision","mean-average-precision","bounding-boxes","precision-recall","pascal-voc"],"license":"MIT","category":"analytics","readme_excerpt":"Citation If you use this code for your research, please consider citing: Download the paper here or here. Download the paper here ----------------- Attention! A new version of this tool is available here ======= The new version includes all COCO metrics , supports other file formats , provides a User Interface (UI) to guide the evaluation process, and presents the STT-AP metric to evaluate object detection in videos. ----------------- Metrics for object detection The motivation of this project is the lack of consensus used by different works and implementations concerning the evaluation metrics of the object detection problem . Although on-line competitions use their own metrics to evaluate the task of object detection, just some of them offer reference code snippets to calculate the accuracy of the detected objects. Researchers who want to evaluate their work using different datasets than those offered by the competitions, need to implement their own version of the metrics. Sometimes a wrong or different implementation can create different and biased results. Ideally, in order to have trustworthy benchmarking among different approaches, it is necessary to have a flexible implementation that can be used by everyone regardless the dataset used. This project provides easy-to-use functions implementing the same metrics used by the the most popular competitions of object detection . Our implementation does not require modifications of your detection model to complicated input for","default_branch":null,"files":null,"tree":[],"storefront":"/r/rafaelpadilla","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/rafaelpadilla/Object-Detection-Metrics/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."}