Boxmot

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BoxMOT is an open-source AI Agents & Automation tool that provides pluggable, state-of-the-art multi-object tracking modules. It offers a unified CLI and Python API for various tracking workflows, supporting both axis-aligned and oriented bounding boxes.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is boxmot?

BoxMOT is an open-source tool designed for multi-object tracking workflows, offering a unified command-line interface (CLI) and Python API. It provides pluggable, state-of-the-art tracking modules with support for both axis-aligned and oriented bounding boxes. The tool streamlines direct tracking, cached benchmark evaluation, tuning, research loops, and ReID export, eliminating the need to rebuild detector and tracker stacks for each experiment. It supports Python versions 3.9 through 3.12 and includes swappable trackers with shared detector and ReID plumbing. BoxMOT is particularly useful for benchmark-oriented workflows, allowing for reusable detections and embeddings, and offers a public Python API for integration into applications and notebooks.

Best used for

Ideal for developers and data scientists who need to implement and evaluate state-of-the-art multi-object tracking solutions. Especially valuable for researchers and engineers working on computer vision projects requiring flexible and benchmark-oriented tracking workflows with support for various bounding box types.

Common actions

track objects

evaluate tracking models

integrate object tracking

research computer vision

"AI Agents"face swappinggithub copilotopen-sourcecollaborationlow-code/no-codedeepfakeautomated workflowworkflows

Capabilities

Key features

Unified CLI and Python API
Pluggable tracking modules
Axis-aligned bounding box support
Oriented bounding box support
Benchmark evaluation
Swappable trackers
ReID export

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of bounding boxes does BoxMOT support?

BoxMOT supports both axis-aligned bounding boxes (AABB) and oriented bounding boxes (OBB). This flexibility allows users to work with different types of object detection outputs, catering to a wider range of computer vision applications and research needs.

Can BoxMOT be used for benchmark evaluation?

Yes, BoxMOT is designed with benchmark-oriented workflows in mind. It allows for cached benchmark evaluation using reusable detections and embeddings, making it efficient for comparing and assessing the performance of different multi-object tracking modules.

What programming languages and versions does BoxMOT support?

BoxMOT primarily supports Python, specifically versions 3.9 through 3.12. It provides a public Python API for seamless integration into applications and notebooks, alongside a command-line interface for direct execution of tracking workflows.

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