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The MS COCO ( Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.
Jun 1, 2024 · COCO is a large-scale object detection, segmentation, and captioning dataset. Note: * Some images from the train and validation sets don't have annotations. * Coco 2014 and 2017 uses the same images, but different train/val/test splits * The test split don't have any annotations (only images).
Nov 12, 2023 · The COCO (Common Objects in Context) dataset is a large-scale object detection, segmentation, and captioning dataset. It is designed to encourage research on a wide variety of object categories and is commonly used for benchmarking computer vision models.
Feb 11, 2023 · Learn the step-by-step process to load and visualize the COCO dataset with custom code. Discover how to prepare the COCO object detection dataset to improve
Oct 12, 2021 · The Common Object in Context (COCO) is one of the most popular large-scale labeled image datasets available for public use. It represents a handful of objects we encounter on a daily basis and contains image annotations in 80 categories, with over 1.5 million object instances.
What is COCO? COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features: Object segmentation; Recognition in context; Superpixel stuff segmentation; 330K images (>200K labeled) 1.5 million object instances; 80 object categories; 91 stuff categories; 5 captions per image; 250,000 people with keypoints
What is COCO? COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features: Object segmentation; Recognition in context; Superpixel stuff segmentation; 330K images (>200K labeled) 1.5 million object instances; 80 object categories; 91 stuff categories; 5 captions per image; 250,000 people with keypoints
Jul 30, 2020 · COCO ( official website) dataset, meaning “Common Objects In Context”, is a set of challenging, high quality datasets for computer vision, mostly state-of-the-art neural networks. This name is also used to name a format used by those datasets.
