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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).
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123272 open source object images plus a pre-trained COCO Dataset model and API. Created by Microsoft
Download COCO/2017. Download and preprocess COCO/2017 to the following format (required by od networks): dataset = { 'images' : A tensor of float32 and shape [1, height, widht, 3],...
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MS 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.
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.
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.
FiftyOne is an open-source tool facilitating visualization and access to COCO data resources and serves as an evaluation tool for model analysis on COCO. What is COCO? COCO is a large-scale object detection, segmentation, and captioning dataset.
