Microsoft COCO 2017 Panoptic Segmentation is the COCO 2017 subset annotated for panoptic segmentation, a task that unifies instance segmentation for "thing" classes and semantic segmentation for "stuff" classes into a single per-pixel labeling. The 2017 release contains the standard COCO image splits (train2017 with ~118,000 images and val2017 with 5,000 images, ~123k images total) and panoptic annotations (JSON panoptic annotation files plus per-image panoptic PNG segment maps). Panoptic annotations provide both instance ids and semantic class ids so models can be evaluated on a single panoptic quality metric that accounts for both things and stuff. The dataset is derived from the Microsoft COCO collection introduced in Lin et al., "Microsoft COCO: Common Objects in Context" (arXiv:1405.0312 / ECCV 2014). Common distribution points and tools include the official COCO website (cocodataset.org), the cocodataset panoptic API (cocodataset/panopticapi on GitHub), and multiple Hugging Face dataset mirrors that expose the train/val splits and panoptic annotations (e.g., AISNP/COCO2017-panoptic).
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