Is it free to convert RetinaNet Keras CSV to YOLOv5 PyTorch TXT?
Yes! It is free to convert RetinaNet Keras CSV data into the YOLOv5 PyTorch TXT format on the Roboflow platform.
Convert annotation formats
How To Convert RetinaNet Keras CSV to YOLOv5 PyTorch TXT
In this guide, we show you how to convert data between the RetinaNet Keras and YOLOv5 formats for free. You can use your converted data to train YOLO-NAS models and other models that support the YOLOv5 format.
RetinaNet Keras CSVtoYOLOv5 PyTorch TXT
Convert with an AI agent
Paste this prompt into your coding agent
Claude Code, Cursor, Codex or any agent with the Roboflow MCP uploads your RetinaNet Keras CSV dataset to Roboflow, generates a version and downloads it as YOLOv5 PyTorch TXT.
No Roboflow MCP yet? The prompt has your agent set it up first, or connect your agent before you paste it.
Rather convert it by hand? Follow the steps below
RetinaNet Keras CSV
A custom format used by the Keras implementation of RetinaNet.
YOLOv5 PyTorch TXT
A modified version of YOLO Darknet annotations that adds a YAML file for model config.
Below, learn the structure of YOLOv5 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 2: Upload your data into Roboflow
Once your account has been created, click Create New Project. (opens in a new tab)
Upload your data to Roboflow by dragging and dropping your RetinaNet Keras CSV 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 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 RetinaNet Keras CSV format to YOLOv5 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 RetinaNet Keras CSV 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.
Convert RetinaNet Keras CSV 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
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- YOLOv7 PyTorch TXT
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- YOLOv8 PyTorch TXT
- YOLOv9 PyTorch TXT
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