Is it free to convert Supervisely JSON to YOLO Darknet TXT?
Yes! It is free to convert Supervisely JSON data into the YOLO Darknet TXT format on the Roboflow platform.
Convert annotation formats
How To Convert Supervisely JSON to YOLO Darknet TXT
In this guide, we show you how to convert data between the Supervise.ly and YOLO Darknet formats for free. You can use your converted data to train YOLOv3 PyTorch models and other models that support the YOLO Darknet format.
Supervisely JSONtoYOLO Darknet TXT
Supervisely JSON
Supervise.ly offers a computer vision platform and uses a proprietary JSON-based annotation format.
Below, learn the structure of Supervisely JSON.
img0001.jsonJSON
{
"description": "",
"tags": [
{
"id": 12345,
"name": "train",
"value": null,
"labelerLogin": "roboflow",
"createdAt": "2000-01-01T00:00:00.000Z",
"updatedAt": "2000-01-01T00:00:00.000Z"
}
],
"size": {
"height": 191,
"width": 264
},
"objects": [
{
"id": 12345,
"classId": 67890,
"description": "",
"geometryType": "polygon",
"labelerLogin": "roboflow",
"createdAt": "2000-01-01T00:00:00.000Z",
"updatedAt": "2000-01-01T00:00:00.000Z",
"tags": [],
"classTitle": "helmet",
"points": {
"exterior": [
[
184,
30
],
[
259,
30
],
[
260,
134
],
[
185,
131
]
],
"interior": []
}
},
{
"id": 12346,
"classId": 67891,
"description": "",
"geometryType": "rectangle",
"labelerLogin": "roboflow",
"createdAt": "2000-01-01T00:00:00.000Z",
"updatedAt": "2000-01-01T00:00:00.000Z",
"tags": [],
"classTitle": "person",
"points": {
"exterior": [
[
63,
49
],
[
124,
62
]
],
"interior": []
}
}
]
}YOLO Darknet TXT
The favored annotation format of the Darknet family of models.
Below, learn the structure of YOLO Darknet TXT.
Each image has one txt file with a single line for each bounding box. The format of each row is:
class_id center_x center_y width heightimg0001.txt
1 0.408 0.30266666666666664 0.104 0.15733333333333333
1 0.245 0.424 0.046 0.08darknet.labels
head
helmet
personStep 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 Supervisely 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 YOLO Darknet 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 Supervisely JSON format to YOLO Darknet TXT format!
Video Tutorial
Convert Computer Vision Annotation Formats Tutorial
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.
Frequently Asked Questions
Yes! It is free to convert Supervisely JSON data into the YOLO Darknet 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.
Convert Supervisely JSON to other formats
- COCO JSON
- COCO Run-Length Encoding (RLE)
- CreateML JSON
- Florence-2
- Google Cloud AutoML Vision CSV
- meituan/yolov6
- Multiclass Classification CSV
- OpenAI CLIP Classification
- OpenAI GPT-4o Object Detection JSONL
- PaliGemma JSONL
- Pascal VOC XML
- RetinaNet Keras CSV
- Sagemaker GroundTruth Manifest
- Scaled-YOLOv4 TXT
- Tensorflow Object Detection CSV
- Tensorflow TFRecord
- YOLO Keras TXT
- YOLOv10 PyTorch TXT
- YOLOv11 PyTorch TXT
- YOLOv4 PyTorch TXT
- YOLOv5 Oriented Bounding Boxes
- YOLOv5 PyTorch TXT
- YOLOv7 PyTorch TXT
- YOLOv8 Oriented Bounding Boxes
- YOLOv8 PyTorch TXT
- YOLOv9 PyTorch TXT
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