Coco object detection annotation format. It’s supported by many annotation t...
Coco object detection annotation format. It’s supported by many annotation tools and model training frameworks, making it a safe default choice for typical object detection projects. These refinements aim to improve training and evaluation performance in object detection tasks. metric: Name of a metric Streams a HF dataset and checks for common annotation issues, mirroring The MJ-COCO-2025 dataset features the improvements, including fixes for group annotations, addition of missing annotations, removal of redundant or overlapping labels, etc. COCO (Common Objects in Context) is a large-scale object detection dataset format developed by Microsoft. For more information about the supported formats, see: Annotation Oct 10, 2024 · DPAKS: DETR Guided by Prior Auxiliary Knowledge for Small Object Detection - XUhaozhi88/DPAKS. The format has become one of the most widely adopted standards for object detection tasks. pred_folder: Folder containing ID images for predictions. Semantic diff between two object detection datasets on Hugging Face Hub. Jan 20, 2026 · The dataset comprises 80 object categories, including common objects like cars, bicycles, and animals, as well as more specific categories such as umbrellas, handbags, and sports equipment. This repository contains the VeHIDE annotations formatted for object detection tasks using the popular COCO annotation style.