Download Coco Dataset For Object Detection Updated May 2026

If you only need a specific subset (e.g., only "cats" and "dogs") or want to avoid manual unzipping, tools like FiftyOne or GluonCV are highly efficient.

# Create directories mkdir -p coco/images && cd coco # Download Annotations wget -c http://cocodataset.org unzip annotations_trainval2017.zip # Download Images cd images wget -c http://images.cocodataset.org/zips/train2017.zip wget -c http://images.cocodataset.org/zips/val2017.zip unzip train2017.zip unzip val2017.zip Use code with caution. download coco dataset for object detection

The annotations are stored in a single large (e.g., instances_train2017.json ). For object detection, the most critical section is the annotations list: COCO Object Detection Format - Labelformat Docs If you only need a specific subset (e

To download the COCO (Common Objects in Context) dataset for object detection, you primarily need the images and their corresponding JSON annotations . COCO is a massive dataset with over 200,000 labeled images across 80 object categories, making it the industry standard for benchmarking computer vision models. Quick Download Links (Official Sources) For object detection, the most critical section is

For standard object detection tasks, you will need the following files from cocodataset.org: 2017 Train images (118K images, ~19GB) 2017 Val images (5K images, ~1GB) 2017 Test images (41K images, ~6GB) Annotations: 2017 Train/Val annotations (241MB) Methods to Download and Setup 1. Using Terminal (Fastest for Linux/Mac)