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

PyTorch-Based Evaluation Tool for Co-Saliency Detection

An Evaluation Toolbox for Salient Object Detection

Clustering Algorithms and their Application to Facial Image Analysis

Extremely fast evaluation of the extrinsic clustering measures: various (mean) F1 measures and Omega Index (Fuzzy Adjusted Rand Index) for the multi-resolution clustering with overlaps/covers, standard NMI, clusters labeling

ML/CNN Evaluation Metrics Package

Information Retrieval with Lucene and CISI dataset. Index documents and search between them with IB, DFR, BM-25, TF-IDF, Boolean, Axiomatic, LM-Dirichlet similarity and calculate Recall, Precision, MAP (Mean Average Precision) and F-Measure

Networks Anomaly Detection using Supervised learning Algorithms such as Kmeans implementation , Spectral clustering implementation, DBMS implementation and Agglomerative Hierarchical Clustering. We also used external and internal measures to evaluate the clustering such as F1-score, purity, precision, recall and pairwise measures.

Calculate Precision & Recall & F-Measure & Accuracy with Confusion Matrix (TP, TN, FP, FN)

Threshold optimization for F measure of macro-averaged precision and recall

Sample of metrics by GoLang