average-precision

Most popular metrics used to evaluate object detection algorithms.

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

Function to calculate mAP for set of detected boxes and annotated boxes.

PyTorch-Based Evaluation Tool for Co-Saliency Detection

This repository contains the official implementation of the NeurIPS'21 paper, ROADMAP: Robust and Decomposable Average Precision for Image Retrieval.

A Python evaluation metrics package for surgical action triplet recognition

Unified framework to parse, create and evaluate object detections from many frameworks (COCO, YOLO, PascalVOC, ImageNet, LabelMe, ...).

ML/CNN Evaluation Metrics Package

PR曲線を用いた平均適合率の計算の方法についての説明と、実装による理解の確認を行います。

Understanding of use of mAP as a metric for Objects Detection problems

This is a novel average precision calculation named hybrid N-point interpolation method to eliminate the average precision distortion in KITTI 3D Object Detection Benchmark.

A simple script to calculate the mAP using PascalVOC2012 and COCO standards for object detection