1 unstable release
0.1.2 | Nov 8, 2024 |
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#147 in Images
21KB
326 lines
onnx-runner
Use ORT to run ONNX model.
Currently, only YOLO models are supported, and other ONNX models may be supported in the future
Install
Requirements
- If you want to use CPU to run onnx-runner, nothing to install
- If you want to use GPU to run onnx-runner, you need install CUDA 12.x and CUDNN 9.x
Windows
-
Download latest version: onnx-runner-0.1.1-windows.tar.gz
-
Or download from release page: Releases
-
Extract
onnx-runner-{version}-windows.tar.gz
to your path. The compressed package already includes the necessary dependencies for running ONNX and OpenCV. You don't need to download any other dependencies -
Run onnx-runner `` with CMD or PowerShell
onnx-runner.exe -m <your_onnx_model> -i <your_input> --show
Ubuntu
-
Download and install
# Download latest package wget https://github.com/xgpxg/onnx-runner/releases/download/v0.1.1/onnx-runner_0.1.1_amd64.deb # Install package sudo apt -f install ./onnx-runner_0.1.1_amd64.deb
Note:The OpenCV will be installed by default
-
Run onnx-runner
onnx-runner -m <your_onnx_model> -i <your_input> --show
Other Linux
-
Download latest version: onnx-runner-v0.1.1-linux.tar.gz
-
Extract
onnx-runner-{version}-linux.tar.gz
to your path. -
Copy
libonnxruntime.so
to /usr/lib -
Install
Opencv
-
Run onnx-runner
onnx-runner -m <your_onnx_model> -i <your_input> --show
MacOS
Not currently supported
usage
CLI
onnx-runner -m yolov8n.onnx -i image.jpg --show
For more information, see help:
onnx-runner -h
Usage: onnx-runner.exe [OPTIONS] --model <MODEL> --input <INPUT>
Options:
-m, --model <MODEL> YOLO onnx model file path, support version: v5, v7, v8, v10, and v11
-i, --input <INPUT> Input source, like image file, http image, camera, or rtsp
--yolo-version <YOLO_VERSION> The number of YOLO version, like 5, 7 ,8 ,10, or 11. Specifically, for YOLO 10, it needs to be set up [default: 8]
--show Should the detection results be displayed in the gui window, default is false
-h, --help Print help
-V, --version Print version
Supported input sources:
Input | Example |
---|---|
Local image file | D:/images/img.png |
Internet image file | https://cdn.pixabay.com/photo/2019/11/05/01/00/couple-4602505_1280.jpg |
Local video file | D:/images/video.mp4 |
Internet video file | https://cdn.pixabay.com/video/2024/06/04/215258_large.mp4 |
Local camera | camera://0 |
Ip camera(RTSP) | rtsp://192.168.1.5:554 |
Lib
You need to install rust
and cargo
, then add onnx-runner to your project.
cargo add onnx-runner
Example
fn main() {
//Use default config
let mut config = ModelRunConfig::default();
//Create a new runner
let runner = ModelRunner::new(args.model.as_str(), config).unwrap();
//Run with input. The input can be a local image, a network image, a camera, or a remote camera that supports RTSP
runner.run(args.input.as_str(), ModelRunner::no_pre, |res, mut mat| {
//Your code in here. You can send result to a http
println!("Result: {:?}", &res);
},
)?;
}
CPU/GPU supports
All CPU are supported.
Currently only supports Nvidia GPUs. You need install CUDA 12.x + and cudnn 9.x + on your device.
Troubleshooting
-
I have installed CUDA and CUDNN, but why is the CPU still used instead of the GPU?
First check whether the CUDA environment variables have been configured, and then check whether the CUDNN dependency libraries have been copied to the CUDA directory. Pay attention to the versions of CUDA and CUDNN. Currently only CUDA12.x and CUDNN9.x are supported.
Dependencies
~9–40MB
~603K SLoC