Formats

YOLOv5 Oriented Bounding Boxes

CONVERT To
CONVERT From
MODELS
EXAMPLE
Use Roboflow to convert
YOLOv5 Oriented Bounding Boxes
to the following formats.

Roboflow is a trusted solution for converting and managing your data. Today, over 100,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.
Use Roboflow to convert the following formats to
YOLOv5 Oriented Bounding Boxes
format.

Roboflow is a trusted solution for converting and managing your data. Today, over 100,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.
Roboflow is a trusted solution for converting and managing your data. Today, over 100,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

Once your data is in Roboflow, just add the link from your dataset and you're ready to go. We even include the code to export to common inference formats like TFLite, ONNX, and CoreML.

Below are pre-configured models that use the
YOLOv5 Oriented Bounding Boxes
data format
.

What computer vision models use YOLOv5 Oriented Bounding Boxes?

The

YOLOv5 Oriented Bounding Boxes

,

models all use the

YOLOv5 Oriented Bounding Boxes

data format.

To see our entire list of computer vision models, check out the Roboflow Model Library.

Each image has one txt file with a single line for each bounding box. The format of each row is

x1 y1 x2 y2 x3 y3 x4 y4 label

where fields are space delimited, and the coordinates are measured in pixels.

001.txt
236 267 271 267 271 306 236 306 helmet 0
188 230 216 230 216 257 188 257 helmet 0
169 146 200 146 200 174 169 174 helmet 0
201 114 230 114 230 140 201 140 helmet 0
247 245 272 245 272 268 247 268 helmet 0
261 231 285 231 285 257 261 257 helmet 0
146 150 172 150 172 179 146 179 head 0

The `data.yaml` file contains configuration values used by the model to locate images and map class names to class_id's.

data.yaml
path: ../datasets/roboflow

train: train/images
val: valid/images
test: test/images

nc: 3
names: ['head', 'helmet', 'person']
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