ModelsObject Detection
ByteTrack
Object Detection
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ByteTrack

ByteTrack is a multi-object tracking computer vision algorithm.
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Overview

ByteTrack is a multi-object tracking computer vision algorithm. Using ByteTrack, you can allocate IDs for unique objects in a video for use in tracking objects. For example, you can track players on a football field and monitor them throughout a scene.

Performance

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Label Data Automatically with ByteTrack

You can automatically label a dataset using ByteTrack with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use ByteTrack to train a computer vision model.
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Use ByteTrack to Build Computer Vision Pipelines and Applications
Images

Data

Augmentation GuideLabeling Guide
Flask

Training

Model OverviewTrain on ColabTrain on JupyterTrain on KaggleTrain on SageMaker
Screwdriver and Wrench

Utilities

Plot PredictionsFilter PredictionsBlur PredictionsCreate A Confusion MatrixUse SAHI for Small Object Detection
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Convert Annotation Format

YOLOv8 uses the uses the YOLOv8 PyTorch TXT annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.
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Architecture

Frameworks

Annotation Format

Popular ByteTrack Use Cases

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ByteTrack Integrations

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