If your labeling tool exported annotations in the
YOLOv8format, but you’re trying to use a
model that needs
Tensorflow CSV annotations, we’ve got you covered. You can convert data between these formats for free in 3 clicks with Roboflow.
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.
Once your account has been created, click Create New Project.
Next, try our YOLO v8 tutorial to train and deploy a custom YOLOv8 model.
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
Tensorflow Object Detection CSV
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
YOLOv8 PyTorch TXT
format to
Tensorflow Object Detection CSV
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.
Ready to use your new
Tensorflow CSV
dataset? Great!
Here are some compatible models:
Try an end-to-end computer vision tutorial, check out your dataset health check or experiment with some augmentations.
Yes! It is free to convert
YOLOv8 PyTorch TXT
data into the
Tensorflow Object Detection CSV
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.
