Prepare COCO datasets

COCO is a large-scale object detection, segmentation, and captioning datasetself. This tutorial will walk through the steps of preparing this dataset for object tracking in GluonCV.

Hint

You need 42.7 GB disk space to download and extract this dataset. SSD is preferred over HDD because of its better performance.

The total time to prepare the dataset depends on your Internet speed and disk performance. For example, it often takes 20 min on AWS EC2 with EBS.

Prepare the dataset

We need the following four files from COCO:

Filename	Size	SHA-1
train2017.zip	18 GB	10ad623668ab00c62c096f0ed636d6aff41faca5
val2017.zip	778 MB	4950dc9d00dbe1c933ee0170f5797584351d2a41
annotations_trainval2017.zip	241 MB	8551ee4bb5860311e79dace7e79cb91e432e78b3
stuff_annotations_trainval2017.zip	401 MB	e7aa0f7515c07e23873a9f71d9095b06bcea3e12

The easiest way to download and unpack these files is to download helper script and we suggest run the command because it included download dataset and data processing mscoco_tracking.py and run the following command:

The easiest way is to run this script:

Download script: coco_tracking.py

python mscoco_tracking.py