In this guide, we show you how to convert data between the
VOCand
YOLOv5formats for free. You can use your converted data to train
models and other models that support the
YOLOv5 format.
Roboflow is a 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.
Once your account has been created, click Create New Project.
To learn how to manually label your images in VOC XML format, see our CVAT tutorial.
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:
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
YOLOv5 PyTorch TXT
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
Pascal VOC XML
format to
YOLOv5 PyTorch TXT
format!
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.
We take security seriously and have implemented comprehensive measures to keep your sensitive data safe
Ready to use your new
YOLOv5
dataset? Great!
Now you probably want to use your new annotations with our YOLO v5 tutorial to get a model working with your own dataset.
Here are some compatible models:
Yes! It is free to convert
Pascal VOC XML
data into the
YOLOv5 PyTorch TXT
format on the Roboflow platform.
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.
