Table Of Contents
Table Of Contents

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.

http://cocodataset.org/images/coco-logo.png

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

Total running time of the script: ( 0 minutes 0.000 seconds)

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