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[Example] YOLO-Series(v5-11) ONNXRuntime Rust (#17311)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Jamjamjon 2024-11-02 20:06:07 +08:00 • committed by GitHub
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examples/YOLOv8-ONNXRuntime-Rust/README.md
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@ -7,7 +7,7 @@ This repository provides a Rust demo for performing YOLOv8 tasks like `Classific
- Add YOLOv8-OBB demo
- Update ONNXRuntime to 1.19.x
Newly updated YOLOv8 example code is located in this repository (https://github.com/jamjamjon/usls/tree/main/examples/yolo)
Newly updated YOLOv8 example code is located in [this repository](https://github.com/jamjamjon/usls/tree/main/examples/yolo)
## Features
@ -22,25 +22,16 @@ Newly updated YOLOv8 example code is located in this repository (https://github.
Please follow the Rust official installation. (https://www.rust-lang.org/tools/install)
### 2. Install ONNXRuntime
### 2. ONNXRuntime Linking
This repository use `ort` crate, which is ONNXRuntime wrapper for Rust. (https://docs.rs/ort/latest/ort/)
- #### For detailed setup instructions, refer to the [ORT documentation](https://ort.pyke.io/setup/linking).
You can follow the instruction with `ort` doc or simply do this:
- step1: Download ONNXRuntime(https://github.com/microsoft/onnxruntime/releases)
- setp2: Set environment variable `PATH` for linking.
On ubuntu, You can do like this:
```bash
vim ~/.bashrc
# Add the path of ONNXRUntime lib
export LD_LIBRARY_PATH=/home/qweasd/Documents/onnxruntime-linux-x64-gpu-1.16.3/lib${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
source ~/.bashrc
```
- #### For Linux or macOS Users:
- Download the ONNX Runtime package from the [Releases page](https://github.com/microsoft/onnxruntime/releases).
- Set up the library path by exporting the `ORT_DYLIB_PATH` environment variable:
```shell
export ORT_DYLIB_PATH=/path/to/onnxruntime/lib/libonnxruntime.so.1.19.0
```
### 3. \[Optional\] Install CUDA & CuDNN & TensorRT