This format contains one text file per image (containing the annotations and a numeric representation of the label) and a labelmap which maps the numeric IDs to human readable strings. The annotations are normalized to lie within the range [0, 1] which makes them easier to work with even after scaling or stretching images. It has become quite popular as it has followed the Darknet framework's implementations of the various YOLO models.
Roboflow can read and write YOLO Darknet files so you can easily convert them to or from any other object detection annotation format. Once you're ready, use your converted annotations with our training YOLO v4 with a custom dataset tutorial.
With Roboflow, you can deploy a computer vision model without having to build your own infrastructure.
Below, we show how to convert data to and from
YOLO Darknet TXT
. We also list popular models that use the
YOLO Darknet TXT
data format. Our conversion tools are free to use.
Free data conversion
SOC II Type 2 Compliant
Trusted by 250,000+ developers
Free data conversion
SOC II Type 1 Compliant
Trusted by 250,000+ developers
The
YOLOv3 PyTorch
,
YOLOv4 Darknet
,
YOLOv4 Tiny
,
models all use the
data format.
1 0.408 0.30266666666666664 0.104 0.15733333333333333
1 0.245 0.424 0.046 0.08
head
helmet
person