COCO Segmentation Dataset

coco segmentation computer vision dataset

Common Objects in Context (COCO) is one of the most common large-scale image datasets for the evaluation of state-of-the-art computer vision models. COCO dataset contains image annotations in 80 categories, with over 1.5 million object instances.

COCO’s 5 annotation types aid in the following operations:

  1. Object detection
  2. Keypoint detection
  3. Semantic segmentation
  4. Panapotic segmentation
  5. Image captioning

You can create a separate JSON file for training, testing, and validation purposes.

Annotation Type: instance segmentation, object detection

Created By: COCO Consortium

Publish Date: September 01, 2017

License: CC BY 4.0

Dataset Size: 287,135 images

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