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info@cocodataset.org. Home; People
- News
We have partnered with the team behind the open-source tool...
- Coco + LVIS | Eccv 2020
The COCO dataset includes 330K images of complex scenes...
- Coco + Mapillary 2018
The goal of the joint COCO and Mapillary Workshop is to...
- COCO 2017 Object Detection Task
A challenge to push the state of the art in object detection...
- News
- Coco/2014
- Coco/2017
- Coco/2017_Panoptic
- GeneratedCaptionsTabForHeroSec
Config description: This version contains images, bounding boxes andlabels for the 2014 version.Download size: 37.57 GiBDataset size: 37.35 GiBSplits:Config description: This version contains images, bounding boxes andlabels for the 2017 version.Download size: 25.20 GiBDataset size: 24.98 GiBSplits:Config description: This version contains images, bounding boxes andlabels for the 2017 version.Download size: 19.57 GiBDataset size: 19.63 GiBSplits:TensorFlow Datasets provides access to the COCO dataset, a large-scale object detection, segmentation, and captioning dataset. Choose from different versions and splits, and see examples and feature documentation.
COCO is a large-scale object detection, segmentation, and captioning dataset with 330K images and 1.5 million object instances. To download COCO, you need to install the dataset repo and use the datasets library or the convert_to_parquet script.
Nov 12, 2023 · Learn how to use the COCO dataset for object detection, segmentation, and captioning tasks with Ultralytics YOLO. Download the dataset, view the YAML configuration, and explore the pretrained models.
MS COCO is a large-scale dataset for object detection, segmentation, captioning, and other tasks. Download the dataset, browse the annotations, and compare the benchmarks and papers on Papers With Code.
TaskDataset VariantBest ModelCOCO minivalCo-DETRCOCO test-devCo-DETRCOCO minivalInternImage-HCOCO test-devEVAWe’re on a journey to advance and democratize artificial intelligence through open source and open science.
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You can explore COCO dataset by visiting SuperAnnotate’s respective dataset section. Modern-day AI-driven solutions are still not capable of producing absolute accuracy in results, which comes down to the fact that the COCO dataset is a major benchmark for CV to train , test, polish, and refine models for faster scaling of the annotation pipeline .