The dataset includes 80 distinct object categories. Whether you are using YOLO, Mask R-CNN, or TensorFlow, you need an accurate list of these names to map your model’s numerical predictions back to human-readable labels. Direct Access to COCO Class Names

The 80 classes are grouped into several super-categories, making it easier to filter your data: Car, truck, bus, boat, etc. Animals: Cat, dog, sheep, elephant, etc. Indoor/Household: Chair, bed, dining table, toaster. Outdoor/Street: Traffic light, fire hydrant, stop sign. Food: Apple, sandwich, pizza, cake.

I can provide the or a ready-to-use script based on those details.

If you'd like to move forward with your project, let me know: