{"repo":"EMalagoli92/OD-Metrics","free":true,"listed":false,"github":"https://github.com/EMalagoli92/OD-Metrics","clone":"git clone https://github.com/EMalagoli92/OD-Metrics.git","description":"Python library for Object Detection metrics.","language":"Python","stars":10,"topics":["computer-vision","deeplearning","machinelearning","neural-networks","object-detection","vision","metrics","deep-learning","deep-neural-networks","iou"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"A python library for Object Detection metrics. Why OD-Metrics? - User-friendly : Designed for simplicity, allowing users to calculate metrics with minimal setup. - Highly Customizable : Offers flexibility by allowing users to set custom values for every parameter in metrics definitions. - COCOAPI Compatibility : Metrics are rigorously tested to ensure compatibility with COCOAPI, ensuring reliability and consistency. Supported Metrics Supported metrics include: - mAP (Mean Average Precision) - mAR (Mean Average Recall) - IoU (Intersection over Union). For more information see Metrics documentation. Documentation For help, usage, API reference, and an overview of metrics formulas, please refer to Documentation. Try live Demo Try OD-Metrics samples Installation Install from PyPI Install from Github Simple Example Aknowledgment - TorchMetrics - COCO API - Object-Detection-Metrics License This work is made available under the Apache License 2.0 Support Found this helpful? ⭐ it on GitHub","default_branch":null,"files":null,"tree":[],"storefront":"/r/EMalagoli92","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/EMalagoli92/OD-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."}