Formats
Scaled-YOLOv4 TXT

Scaled-YOLOv4 TXT

Scaled-YOLOv4 uses a variant on the Darknet TXT format with an additional data.yaml configuration file.
Formats

Scaled-YOLOv4 TXT

Below, we show how to convert data to and from

Scaled-YOLOv4 TXT

. We also list popular models that use the

Scaled-YOLOv4 TXT

data format. Our conversion tools are free to use.

CONVERT To
CONVERT From
EXAMPLE

Convert Data to Scaled-YOLOv4 TXT

Use Roboflow to convert
Scaled-YOLOv4 TXT
to the following formats.

Roboflow is a trusted solution for converting and managing your data. Today, over 250,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

With Roboflow, you get a solution with:

Free data conversion

SOC II Type 2 Compliant

Trusted by 250,000+ developers

Convert Data from Scaled-YOLOv4 TXT

Use Roboflow to convert the following formats to
Scaled-YOLOv4 TXT
format.

Roboflow is a trusted solution for converting and managing your data. Today, over 250,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

With Roboflow, you get:

Free data conversion

SOC II Type 1 Compliant

Trusted by 250,000+ developers

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
Scaled-YOLOv4 TXT
data format
.

What computer vision models use Scaled-YOLOv4 TXT?

The

Scaled YOLOv4

,

models all use the

Scaled-YOLOv4 TXT

data format.

To see our entire list of computer vision models, check out the Roboflow Model Library.
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 0.17167381974248927
data.yaml
train: ../train/images
val: ../valid/images

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