Tools-CLI

Note

This is the latest version of tools CLI. If you are looking for the tools web application, please refer to the web-app branch.

This application is used for exporting Yolo V5, V6, V7, V8 (OBB, instance segmentation, pose estimation, cls) and Gold YOLO object detection models to .ONNX.

Running

You can either export a model stored on cloud (e.g. S3) or locally. To export a local model, please put it inside a shared-component folder.

The output files are going to be in shared-component/output folder.

Prerequisites

# Cloning the tools repository and all submodules
git clone --recursive https://github.com/luxonis/tools.git
# Change folder
cd tools

Using Docker

# Building Docker image
docker build -t tools_cli .
# Running the image
docker run -v "${PWD}/shared_with_container:/app/shared_with_container" tools_cli shared_with_container/models/yolov8n-seg.pt --imgsz "416"

Using Docker compose

# Building Docker image
docker compose build
# Running the image
docker compose run tools_cli shared_with_container/models/yolov6nr4.pt

Using Python package

# Building the package
pip install .
# Running the package
tools shared_with_container/models/yolov6nr4.pt --imgsz "416"

Arguments

• model: str = Path to the model.
• imgsz: str = Image input shape in the format width height or width. Default value "416 416".
• version: Optional[str] =
• use_rvc2: bool = Whether to export for RVC2 or RVC3 devices. Default value True.
• class_names: Optional[str] = Optional list of classes separated by a comma, e.g. "person, dog, cat"
• output_remote_url: Optional[str] = Remote output url for the output .onnx model.
• config_path: Optional[str] = Optional path to an optional config.
• put_file_plugin: Optional[str] = Which plugin to use. Optional.

Credits

This application uses source code of the following repositories: YOLOv5, YOLOv6, GoldYOLO YOLOv7, and Ultralytics YOLOv8 (see each of them for more information).

License

This application is available under AGPL-3.0 License license (see LICENSE file for details).