

Convert to

COCO JSON

VoTT JSON

The native format of Microsoft's Visual Object Tagging Tool (VoTT)





COCO JSON

COCO is a common JSON format used for machine learning because the dataset it was introduced with has become a common benchmark.

enterprise only

This conversion is only available on an Enterprise plan.

enterprise only

This conversion is only available on an Enterprise plan.

How To Convert VoTT JSON to COCO JSON

If your labeling tool exported annotations in the

VoTT

format, but you’re trying to use a

DETR

model that needs

COCO

annotations, we’ve got you covered. You can convert data between these formats for free in 3 clicks with Roboflow.

Step 1: Create a free Roboflow public workspace

Roboflow is the universal conversion tool for computer vision annotation formats. The Public plan is the best way for those exploring personal projects, class assignments, and other experiments to try Roboflow. To convert your dataset, start by creating a free workspace on the Public plan.

Create Roboflow Workspace

Step 2: Upload your data into Roboflow

Once your account has been created, click Create New Project.

Upload your data to Roboflow by dragging and dropping your

VoTT JSON

images and annotations into the upload space.

Step 3: Generate Dataset Version

Next, click "Generate New Version" to generate a new version of your dataset:

You can then apply any preprocessing or augmentation steps to your dataset:

Step 4: Export Dataset Version

After generating, you will be prompted to Export your dataset. You can choose to receive your dataset as a .zip file or a curl download link. Choose

COCO JSON

when asked in what format you want to export your data. You will see a dropdown with various options like this:

Congratulations, you have successfully converted your dataset from

VoTT JSON

format to

COCO JSON

format!

Summary

Want to dive deeper into converting annotation formats with Roboflow? In the tutorial below, we explore how to convert your data in the Roboflow dashboard. We also discuss rejecting annotations
and train-test-validation splits.
‍

Next Steps

Ready to use your new

COCO

dataset? Great!

To learn how to create COCO JSON yourself from scratch, see our CVAT (object detection annotation tool) tutorial.

Here are some compatible models:

DETR

Detection Transformer (DETR) is an end-to-end object detection model implemented using the Transformer architecture.

YOLOS

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.

Mask RCNN

Mask RCNN is a convolutional neural network for instance segmentation.

EfficientDet

EfficientDet achieves the best performance in the fewest training epochs among object detection model architectures, making it a highly scalable architecture especially when operating with limited compute.

Detectron2

Detectron2 is model zoo of it's own for computer vision models written in PyTorch.

Frequently Asked Questions

Is it free to convert

VoTT JSON

to

COCO JSON

?
‍

Yes! It is free to convert

VoTT JSON

data into the

COCO JSON

format on the Roboflow platform.
‍

How long does it take to convert

VoTT JSON

data to

COCO JSON

?
‍

If you have between a few and a few thousand images, converting data between these formats will be quick. But, the time it takes to convert between data formats increases with the more images you have.