Most popular metrics used to evaluate object detection algorithms.
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Updated
Jun 18, 2024 - Python
Most popular metrics used to evaluate object detection algorithms.
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.
Unofficial Python implementation of "Precision and Recall for Time Series".
Evaluation of 3D detection and diagnosis performance —geared towards prostate cancer detection in MRI.
Time-series Aware Precision and Recall for Evaluating Anomaly Detection Methods
Machine learning utility functions and classes.
Classification Metric Manager is metrics calculator for machine learning classification quality such as Precision, Recall, F-score, etc.
Evaluate a detection model performance
This is the official implementation for the Generative Modeling Density Alignment (GMDA). This work was presented in the paper "Frugal Generative Modeling for Tabular Data" at ECML 2024.
Information Retrieval models implemented in Python
Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification
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