MS COCO is composed of several datasets created in different years-each one focuses on a different computer vision task, such as: Use it in any type of work, including commercial projects, crediting the original creators.Remix images with each other or external images.According to this license you are allowed to: It is provided under a Creative Commons Attribution 4.0 License. The MS COCO dataset is maintained by a team of contributors, and sponsored by Microsoft, Facebook, and other organizations. Dense pose -the dataset has more than 39,000 images containing over 56,000 humans, with every labeled person annotated with an instance id and a mapping between pixels representing that person’s body and a template 3D model.Panoptic -full scene segmentation, indicating objects in the image according to 80 categories of “things” (cat, pen, fridge, etc.) and 91 “stuff” categories (road, sky, water, etc.).“Stuff image” segmentation -pixel maps of 91 categories of “stuff”-amorphous background regions like walls, sky, or grass.Keypoints- the dataset has more than 200,000 images containing over 250,000 humans, labeled with keypoints such as right eye, nose, left hip.Captioning -natural language descriptions of each image.Object detection -coordinates of bounding boxes and full segmentation masks for 80 categories of objects.MC COCO provides the following types of annotations: The dataset contains annotations you can use to train machine learning models to recognize, label, and describe objects. MS COCO (Microsoft Common Objects in Context) is a large-scale image dataset containing 328,000 images of everyday objects and humans.
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