Installation

Requirements

BoxMOT supports Python 3.10 through 3.13.

Basic install

pip install boxmot
boxmot --help

This installs the core package. It is enough for simple tracking and Python API usage when your detector and ReID backends are already available in the environment.

Mode-specific extras

BoxMOT keeps heavier workflow dependencies optional. Install the extras that match the modes and export targets you plan to use.

Workflow	PyPI install	Source checkout with uv	Notes
track, generate, eval with common YOLO backends	pip install "boxmot[yolo]"	uv sync --extra yolo	Preinstalls Ultralytics and YOLOX. If you skip this, BoxMOT can install some detector packages on first use.
train and eval-reid	pip install boxmot	uv sync	Uses the built-in ReID training and evaluation stack. You still need to place the chosen ReID dataset under your --data-dir.
tune	pip install "boxmot[evolve]"	uv sync --extra evolve	Installs Ray Tune, Optuna, Plotly, and related tuning dependencies.
research	pip install "boxmot[research]"	uv sync --extra research	Installs GEPA for the code-evolution loop.
export --include onnx	pip install "boxmot[onnx]"	uv sync --extra onnx	The default export path uses ONNX.
export --include openvino	pip install "boxmot[openvino]"	uv sync --extra openvino	Usually paired with --include onnx.
export --include tflite	pip install "boxmot[tflite]"	uv sync --extra tflite	Python 3.12 on Linux or Windows only.

You can combine extras when needed:

uv sync --extra yolo --extra evolve --extra research
pip install "boxmot[yolo,evolve,research]"

boxmot export --include engine requires NVIDIA TensorRT to be available in the environment. It is not provided as a BoxMOT extra.

Native C++ backends

Native C++ tracker backends are built lazily the first time you select --tracker-backend cpp. They are currently available for botsort, bytetrack, ocsort, occluboost, and sfsort.

Install the native build tools before using them:

• C++17 compiler
• CMake 3.16+
• OpenCV 4.x
• Eigen3 3.3+

Example:

boxmot track --detector yolov8n --tracker bytetrack --tracker-backend cpp --source video.mp4
boxmot eval --benchmark mot17 --split ablation --tracker bytetrack --tracker-backend cpp

The generated build files are kept under build/native/<tracker>/.

Verify the install

!!! example "Verify"

=== "CLI"

    Check the CLI:

    ```bash
    boxmot --help
    boxmot track --help
    ```

=== "Python"

    Smoke-test the Python API:

    ```python
    from boxmot import Boxmot

    boxmot = Boxmot(detector="yolov8n", reid="osnet_x0_25_msmt17", tracker="bytetrack")
    print(boxmot)
    ```

Next steps

• Use Quickstart for a minimal path.
• Use Modes Overview to decide between track, generate, eval, tune, research, train, eval-reid, and export.
• Use the workflow table above to add the extras your workflow needs.