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

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

examples/YOLOv8-ONNXRuntime-Rust/Cargo.toml

@@ -12,7 +12,7 @@ clap = { version = "4.2.4", features = ["derive"] }
 image = { version = "0.25.2"}
 imageproc = { version = "0.25.0"}
 ndarray = { version = "0.16" }
-ort = { version = "2.0.0-rc.5", features = ["cuda", "tensorrt"]}
+ort = { version = "2.0.0-rc.5", features = ["cuda", "tensorrt", "load-dynamic", "copy-dylibs", "half"]}
 rusttype = { version = "0.9.3" }
 anyhow = { version = "1.0.75" }
 regex = { version = "1.5.4" }

examples/YOLOv8-ONNXRuntime-Rust/README.md

@@ -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
 

examples/YOLOv8-ONNXRuntime-Rust/src/lib.rs

@@ -118,16 +118,15 @@ pub fn check_font(font: &str) -> rusttype::Font<'static> {
     rusttype::Font::try_from_vec(buffer).unwrap()
 }
 
-
 use ab_glyph::FontArc;
-pub fn load_font() -> FontArc{
+pub fn load_font() -> FontArc {
     use std::path::Path;
     let font_path = Path::new("./font/Arial.ttf");
     match font_path.try_exists() {
         Ok(true) => {
             let buffer = std::fs::read(font_path).unwrap();
             FontArc::try_from_vec(buffer).unwrap()
-        },
+        }
         Ok(false) => {
             std::fs::create_dir_all("./font").unwrap();
             println!("Downloading font...");
@@ -136,7 +135,7 @@ pub fn load_font() -> FontArc{
                 .timeout(std::time::Duration::from_secs(500))
                 .call()
                 .unwrap_or_else(|err| panic!("> Failed to download font: {source_url}: {err:?}"));
-    
+
             // read to buffer
             let mut buffer = vec![];
             let total_size = resp
@@ -153,9 +152,9 @@ pub fn load_font() -> FontArc{
             fd.write_all(&buffer).unwrap();
             println!("Font saved at: {:?}", font_path.display());
             FontArc::try_from_vec(buffer).unwrap()
-        },
+        }
         Err(e) => {
             panic!("Failed to load font {}", e);
-        },
+        }
     }
-}
+}

examples/YOLOv8-ONNXRuntime-Rust/src/model.rs

@@ -8,7 +8,7 @@ use rand::{thread_rng, Rng};
 use std::path::PathBuf;
 
 use crate::{
-    load_font, gen_time_string, non_max_suppression, Args, Batch, Bbox, Embedding, OrtBackend,
+    gen_time_string, load_font, non_max_suppression, Args, Batch, Bbox, Embedding, OrtBackend,
     OrtConfig, OrtEP, Point2, YOLOResult, YOLOTask, SKELETON,
 };
 
@@ -40,7 +40,7 @@ impl YOLOv8 {
             OrtEP::CUDA(config.device_id)
         } else {
             OrtEP::CPU
-        }; 
+        };
 
         // batch
         let batch = Batch {
@@ -463,7 +463,7 @@ impl YOLOv8 {
                         image::Rgb(self.color_palette[bbox.id()].into()),
                         bbox.xmin() as i32,
                         (bbox.ymin() - legend_size as f32) as i32,
-                        legend_size as  f32,
+                        legend_size as f32,
                         &font,
                         &legend,
                     );