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 LabelMe JSON to YOLOv9 PyTorch TXT

In this guide, we show you how to convert data between the




formats for free. You can use your converted data to train

models and other models that support the



Free data conversion

SOC II Type 1 Compliant

Trusted by 250,000+ developers

Step 1: Create a free Roboflow public workspace

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.

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
LabelMe JSON
images and annotations into the upload space.

To learn more about LabelMe, check out our LabelMe Tutorial which goes through the process of annotating an object detection dataset along with tips, tricks, and best practices.

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

YOLOv9 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

LabelMe JSON

format to

YOLOv9 PyTorch TXT



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.

Enterprise-grade security and compliance

We take security seriously and have implemented comprehensive measures to keep your sensitive data safe

Compliant with SOC2 Type 1 requirements
All data is encrypted in transit and at rest, with SSL transport receiving a grade A+ rating from Qualys
Strict row-level permissions to ensure users cannot access sensitive data outside of their organizations
Roboflow is hosted on the Google Cloud Platform and Amazon Web Services, best-in-class infrastructure as a service providers
Authentication, database and file storage mechanisms are ISO 27001, ISO 27017, ISO 27018, SOC 1, SOC 2 and SOC 3 compliant
PCI compliant with Self-Assessment Questionnaire A and Attestation of Compliance
All card numbers and bank accounts never touch our servers and are stored by Stripe, a PCI Service Provider Level 1, the highest available security certification in the payments industry
Access to production data is heavily restricted within Roboflow and only accessible via SSO login
All Roboflow employees sign nondisclosure agreements restricting them from sharing information learned while handling customer data

Next Steps

Ready to use your new


dataset? Great!

Next, use your converted dataset to train a custom YOLOv9 model.

Here are some compatible models:

Try an end-to-end computer vision tutorial, check out your dataset health check or experiment with some augmentations.

Frequently Asked Questions

Is it free to convert
LabelMe JSON
YOLOv9 PyTorch TXT

Yes! It is free to convert

LabelMe JSON

data into the

YOLOv9 PyTorch TXT

format on the Roboflow platform.

How long does it take to convert
LabelMe JSON
data to
YOLOv9 PyTorch TXT

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.

Convert LabelMe JSON to other formats

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Convert YOLOv9 PyTorch TXT to other formats

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