Formats
YOLO Darknet TXT
Object Detection
IMPORTEXPORT
FEATURED
Object Detection

YOLO Darknet TXT

The favored annotation format of the Darknet family of models.

Overview

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.

Format Description

Below, learn the structure of YOLO Darknet 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
img0001.txt
1 0.408 0.30266666666666664 0.104 0.15733333333333333
1 0.245 0.424 0.046 0.08
darknet.labels
head
helmet
person

Split and Merge Datasets

With Roboflow supervision, an open source Python package with utilities for completing computer vision tasks, you can merge and split detections in YOLO Darknet TXT. Read our dedicated guides to learn how to merge and split YOLO Darknet TXT detections.

Split detections in YOLO Darknet TXT

No items found.

Merge detections in YOLO Darknet TXT

No items found.

Supported Models

Below, see model architectures that require data in the YOLO Darknet TXT format when training a new model.

On each page below, you can find links to our guides that show how to plot predictions from the model, and complete other common tasks like detecting small objects with the model.

YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
Object Detection
Deploy with Roboflow
•
•
7.2k+
stars
•
GPL-3.0
license
•
Released
Apr 8, 2018

YOLOv4 Darknet

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in Darknet.
Object Detection
Deploy with Roboflow
•
•
stars
•
YOLO
license
•
Released

YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset
Object Detection
Deploy with Roboflow
•
•
stars
•
YOLO
license
•
Released
Nov 9, 2020

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Formats
YOLO Darknet TXT

What is YOLO Darknet TXT?

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.

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YOLO Darknet TXT

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.

CONVERT To
CONVERT From
EXAMPLE

Convert Data to YOLO Darknet TXT

Use Roboflow to convert
YOLO Darknet 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

YOLO Darknet TXT
 to 
YOLOv8 PyTorch TXT
YOLO Darknet TXT
 to 
YOLOv8 Oriented Bounding Boxes
YOLO Darknet TXT
 to 
PaliGemma JSONL
YOLO Darknet TXT
 to 
YOLOv10 PyTorch TXT
YOLO Darknet TXT
 to 
YOLOv9 PyTorch TXT
YOLO Darknet TXT
 to 
Florence-2
YOLO Darknet TXT
 to 
YOLOv11 PyTorch TXT
YOLO Darknet TXT
 to 
OpenAI GPT-4o Object Detection JSONL
YOLO Darknet TXT
 to 
COCO Run-Length Encoding (RLE)
YOLO Darknet TXT
 to 
Tensorflow TFRecord
YOLO Darknet TXT
 to 
COCO JSON
YOLO Darknet TXT
 to 
Pascal VOC XML
YOLO Darknet TXT
 to 
CreateML JSON
YOLO Darknet TXT
 to 
YOLOv7 PyTorch TXT
YOLO Darknet TXT
 to 
YOLOv5 PyTorch TXT
YOLO Darknet TXT
 to 
Google Cloud AutoML Vision CSV
YOLO Darknet TXT
 to 
Sagemaker GroundTruth Manifest
YOLO Darknet TXT
 to 
meituan/yolov6
YOLO Darknet TXT
 to 
Scaled-YOLOv4 TXT
YOLO Darknet TXT
 to 
YOLO Keras TXT
YOLO Darknet TXT
 to 
OpenAI CLIP Classification
YOLO Darknet TXT
 to 
RetinaNet Keras CSV
YOLO Darknet TXT
 to 
Tensorflow Object Detection CSV
YOLO Darknet TXT
 to 
Multiclass Classification CSV
YOLO Darknet TXT
 to 
YOLOv4 PyTorch TXT
YOLO Darknet TXT
 to 
YOLOv5 Oriented Bounding Boxes

Convert Data from YOLO Darknet TXT

Use Roboflow to convert the following formats to
YOLO Darknet 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

YOLOv8 PyTorch TXT
to
YOLO Darknet TXT
COCO JSON
to
YOLO Darknet TXT
Pascal VOC XML
to
YOLO Darknet TXT
CreateML JSON
to
YOLO Darknet TXT
Sagemaker GroundTruth Manifest
to
YOLO Darknet TXT
SuperAnnotate JSON
to
YOLO Darknet TXT
LabelMe JSON
to
YOLO Darknet TXT
Google Cloud AutoML Vision CSV
to
YOLO Darknet TXT
LabelBox JSON
to
YOLO Darknet TXT
Supervisely JSON
to
YOLO Darknet TXT
Scale AI JSON
to
YOLO Darknet TXT
VGG Image Annotator JSON
to
YOLO Darknet TXT
VGG Image Annotator CSV
to
YOLO Darknet TXT
VoTT CSV
to
YOLO Darknet TXT
VoTT JSON
to
YOLO Darknet TXT
LabelBox Video JSON
to
YOLO Darknet TXT
IBM Cloud Annotations JSON
to
YOLO Darknet TXT
Unity Perception JSON
to
YOLO Darknet TXT
OIDv4 TXT
to
YOLO Darknet TXT
YOLO Keras TXT
to
YOLO Darknet TXT
RetinaNet Keras CSV
to
YOLO Darknet TXT
OpenImages CSV
to
YOLO Darknet TXT
Tensorflow Object Detection CSV
to
YOLO Darknet TXT
Multiclass Classification CSV
to
YOLO Darknet TXT
Cogniac
to
YOLO Darknet TXT
Marmot XML
to
YOLO Darknet TXT
Udacity TXT
to
YOLO Darknet TXT
Kaggle Wheat CSV
to
YOLO Darknet TXT
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
YOLO Darknet TXT
data format
.

What computer vision models use YOLO Darknet TXT?

The

YOLOv3 PyTorch

,

YOLOv4 Darknet

,

YOLOv4 Tiny

,

models all use the

YOLO Darknet TXT

data format.

YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.

YOLOv4 Darknet

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in Darknet.

YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset

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:

class_id center_x center_y width height
img0001.txt
1 0.408 0.30266666666666664 0.104 0.15733333333333333
1 0.245 0.424 0.046 0.08
darknet.labels
head
helmet
person
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