Is it free to convert OIDv4 TXT to YOLOv11 PyTorch TXT?
Yes! It is free to convert OIDv4 TXT data into the YOLOv11 PyTorch TXT format on the Roboflow platform.
Convert annotation formats
How to Convert OIDv4 TXT to YOLOv11 PyTorch TXT
In this guide, we show you how to convert data between the OIDv4 and YOLOv11 PyTorch TXT formats for free. You can use your converted data to train models and other models that support the YOLOv11 PyTorch TXT format.
OIDv4 TXTtoYOLOv11 PyTorch TXT
OIDv4 TXT
The format returned by the OpenImages Dataset v4 ToolKit.
Below, learn the structure of OIDv4 TXT.
img0001.txt
helmet 0.0 73.041386 355.2 463.235188
person 2.56 95.46632500000001 86.4 213.357589
helmet 123.52 26.9102 826.24 594.5815520000001YOLOv11 PyTorch TXT
Below, learn the structure of YOLOv11 PyTorch 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 height
where fields are space delimited, and the coordinates are normalized from zero to one.
Note: To convert to normalized xywh from pixel values, divide x (and width) by the image's width and divide y (and height) by the image's height.
001.txt
1 0.617 0.3594420600858369 0.114 0.17381974248927037
1 0.094 0.38626609442060084 0.156 0.23605150214592274
1 0.295 0.3959227467811159 0.13 0.19527896995708155
1 0.785 0.398068669527897 0.07 0.14377682403433475
1 0.886 0.40879828326180256 0.124 0.18240343347639484
1 0.723 0.398068669527897 0.102 0.1609442060085837
1 0.541 0.35085836909871243 0.094 0.16952789699570817
1 0.428 0.4334763948497854 0.068 0.1072961373390558
1 0.375 0.40236051502145925 0.054 0.1351931330472103
1 0.976 0.3927038626609442 0.044 0.17167381974248927The `data.yaml` file contains configuration values used by the model to locate images and map class names to class_id's.
data.yaml
train: ../train/images
val: ../valid/images
nc: 3
names: ['head', 'helmet', 'person']
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 OIDv4 TXT 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 YOLOv11 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 OIDv4 TXT format to YOLOv11 PyTorch 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 OIDv4 TXT data into the YOLOv11 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.
Convert OIDv4 TXT 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 Darknet TXT
- YOLO Keras TXT
- YOLOv10 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
Convert other formats to YOLOv11 PyTorch TXT
- How to Convert Cloud Annotations JSON to YOLOv11 PyTorch TXT
- How to Convert Cloud AutoML Vision CSV to YOLOv11 PyTorch TXT
- How to Convert COCO JSON to YOLOv11 PyTorch TXT
- How to Convert Cogniac to YOLOv11 PyTorch TXT
- How to Convert CreateML JSON to YOLOv11 PyTorch TXT
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- How to Convert LabelBox JSON to YOLOv11 PyTorch TXT
- How to Convert LabelBox Video JSON to YOLOv11 PyTorch TXT
- How to Convert LabelMe JSON to YOLOv11 PyTorch TXT
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- How to Convert PaliGemma JSONL to YOLOv11 PyTorch TXT
- How to Convert Pascal VOC XML to YOLOv11 PyTorch TXT
- How to Convert RetinaNet Keras CSV to YOLOv11 PyTorch TXT
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- How to Convert YOLO Darknet TXT to YOLOv11 PyTorch TXT
- How to Convert YOLO Keras TXT to YOLOv11 PyTorch TXT
- How to Convert YOLOv10 PyTorch TXT to YOLOv11 PyTorch TXT
- How to Convert YOLOv8 PyTorch TXT to YOLOv11 PyTorch TXT