0.0.5 (#24)

* Using Rayon to accelarate YOLO post-processing

* Refactor YOLO with outputs format

* Optimize `conf * clss` for yolov5 v6 v7

* Add depth-anything-v2

* Update README.md

* Update CHANGELOG.md

examples/yolo/README.md

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+<h1 align='center'>YOLO-Series</h1>
+
+
+|      Detection     |    Instance Segmentation   |   Pose     | 
+| :---------------: | :------------------------: |:---------------: |
+| <img src='./demos/det.png'  width="300px">  | <img src='./demos/seg.png'  width="300px"> |<img src='./demos/pose.png'  width="300px">  | 
+
+|    Classification   |    Obb   |
+| :------------------------: |:------------------------: |
+|<img src='./demos/cls.png'  width="300px"> |<img src='./demos/obb-2.png'  width="628px">
+
+|    Head Detection   |    Fall Detection   | Trash Detection   |
+| :------------------------: |:------------------------: |:------------------------: |
+|<img src='./demos/head.png'  width="300px"> |<img src='./demos/falldown.png'  width="300px">|<img src='./demos/trash.png'  width="300px">
+
+|    YOLO-World   |    Face Parsing   | FastSAM   |
+| :------------------------: |:------------------------: |:------------------------: |
+|<img src='./demos/yolov8-world.png'  width="300px"> |<img src='./demos/face-parsing.png'  width="300px">|<img src='./demos/fastsam.png'  width="300px">
+
+
+
+
+
+## Quick Start
+```Shell
+
+# Classify
+cargo run -r --example yolo -- --task classify --version v5  # YOLOv5 
+cargo run -r --example yolo -- --task classify --version v8  # YOLOv8 
+
+# Detect
+cargo run -r --example yolo -- --task detect --version v5  # YOLOv5 
+cargo run -r --example yolo -- --task detect --version v6  # YOLOv6
+cargo run -r --example yolo -- --task detect --version v7  # YOLOv7
+cargo run -r --example yolo -- --task detect --version v8  # YOLOv8
+cargo run -r --example yolo -- --task detect --version v9  # YOLOv9
+cargo run -r --example yolo -- --task detect --version v10 # YOLOv10
+cargo run -r --example yolo -- --task detect --version rtdetr  # YOLOv8-RTDETR
+cargo run -r --example yolo -- --task detect --version v8 --model yolov8s-world-v2-shoes.onnx  # YOLOv8-world
+
+# Pose
+cargo run -r --example yolo -- --task pose --version v8  # YOLOv8-Pose
+
+# Segment
+cargo run -r --example yolo -- --task segment --version v5  # YOLOv5-Segment
+cargo run -r --example yolo -- --task segment --version v8  # YOLOv8-Segment
+cargo run -r --example yolo -- --task segment --version v8 --model FastSAM-s-dyn-f16.onnx  # FastSAM
+
+# Obb
+cargo run -r --example yolo -- --task obb --version v8  # YOLOv8-Obb
+```
+
+<details close>
+<summary>other options</summary>
+
+`--source` to specify the input images  
+`--model` to specify the ONNX model  
+`--width --height` to specify the input resolution  
+`--nc` to specify the number of model's classes  
+`--plot` to annotate with inference results  
+`--profile` to profile  
+`--cuda --trt --coreml --device_id` to select device  
+`--half` to use float16 when using TensorRT EP  
+
+</details>
+
+
+## YOLOs configs with `Options` 
+
+<details open>
+<summary>Use official YOLO Models</summary>
+
+```Rust
+let options = Options::default()
+    .with_yolo_version(YOLOVersion::V5)  // YOLOVersion: V5, V6, V7, V8, V9, V10, RTDETR
+    .with_yolo_task(YOLOTask::Classify)  // YOLOTask: Classify, Detect, Pose, Segment, Obb
+    .with_model("xxxx.onnx")?;
+
+```
+</details>
+
+<details open>
+<summary>Cutomized your own YOLO model</summary>
+
+```Rust
+// This config is for YOLOv8-Segment 
+use usls::{AnchorsPosition, BoxType, ClssType, YOLOPreds};
+
+let options = Options::default()
+    .with_yolo_preds(
+        YOLOPreds {
+            bbox: Some(BoxType::Cxcywh),
+            clss: ClssType::Clss,
+            coefs: Some(true),
+            anchors: Some(AnchorsPosition::After),
+            ..Default::default()
+        }
+    )
+    .with_model("xxxx.onnx")?;
+```
+</details>
+
+## Other YOLOv8 Solution Models
+
+|          Model          |    Weights   | Datasets|
+|:---------------------: | :--------------------------: | :-------------------------------: |
+| Face-Landmark Detection |   [yolov8-face-dyn-f16](https://github.com/jamjamjon/assets/releases/download/v0.0.1/yolov8-face-dyn-f16.onnx)         | |
+| Head Detection |   [yolov8-head-f16](https://github.com/jamjamjon/assets/releases/download/v0.0.1/yolov8-head-f16.onnx)         | |
+| Fall Detection |   [yolov8-falldown-f16](https://github.com/jamjamjon/assets/releases/download/v0.0.1/yolov8-falldown-f16.onnx)          | |
+| Trash Detection |   [yolov8-plastic-bag-f16](https://github.com/jamjamjon/assets/releases/download/v0.0.1/yolov8-plastic-bag-f16.onnx)         | |
+| FaceParsing |  [face-parsing-dyn](https://github.com/jamjamjon/assets/releases/download/v0.0.1/face-parsing-dyn.onnx)  | [CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ/tree/master/face_parsing)<br />[[Processed YOLO labels]](https://github.com/jamjamjon/assets/releases/download/v0.0.1/CelebAMask-HQ-YOLO-Labels.zip)[[Python Script]](https://github.com/jamjamjon/assets/releases/download/v0.0.1/CelebAMask-HQ-YOLO-Labels.zip) |
+
+
+
+
+## Export ONNX Models
+
+
+<details close>
+<summary>YOLOv5</summary>
+    
+[Here](https://docs.ultralytics.com/yolov5/tutorials/model_export/)
+
+</details>
+
+
+<details close>
+<summary>YOLOv6</summary>
+
+[Here](https://github.com/meituan/YOLOv6/tree/main/deploy/ONNX)
+
+</details>
+
+
+<details close>
+<summary>YOLOv7</summary>
+
+[Here](https://github.com/WongKinYiu/yolov7?tab=readme-ov-file#export)
+
+</details>
+
+<details close>
+<summary>YOLOv8</summary>
+    
+```Shell
+pip install -U ultralytics
+
+# export onnx model with dynamic shapes
+yolo export model=yolov8m.pt format=onnx simplify dynamic
+yolo export model=yolov8m-cls.pt format=onnx simplify dynamic
+yolo export model=yolov8m-pose.pt format=onnx simplify dynamic
+yolo export model=yolov8m-seg.pt format=onnx simplify dynamic
+yolo export model=yolov8m-obb.pt format=onnx simplify dynamic
+
+# export onnx model with fixed shapes
+yolo export model=yolov8m.pt format=onnx simplify
+yolo export model=yolov8m-cls.pt format=onnx simplify
+yolo export model=yolov8m-pose.pt format=onnx simplify
+yolo export model=yolov8m-seg.pt format=onnx simplify
+yolo export model=yolov8m-obb.pt format=onnx simplify
+```
+</details>
+
+
+<details close>
+<summary>YOLOv9</summary>
+
+[Here](https://github.com/WongKinYiu/yolov9/blob/main/export.py)
+
+</details>
+
+<details close>
+<summary>YOLOv10</summary>
+
+[Here](https://github.com/THU-MIG/yolov10#export)
+
+</details>
+
+
+
+

examples/yolo/main.rs

@@ -0,0 +1,180 @@
+use anyhow::Result;
+use clap::Parser;
+
+use usls::{coco, models::YOLO, Annotator, DataLoader, Options, Vision, YOLOTask, YOLOVersion};
+
+#[derive(Parser, Clone)]
+#[command(author, version, about, long_about = None)]
+pub struct Args {
+    #[arg(long)]
+    pub model: Option<String>,
+
+    #[arg(long, default_value_t = String::from("./assets/bus.jpg"))]
+    pub source: String,
+
+    #[arg(long, value_enum, default_value_t = YOLOTask::Detect)]
+    pub task: YOLOTask,
+
+    #[arg(long, value_enum, default_value_t = YOLOVersion::V8)]
+    pub version: YOLOVersion,
+
+    #[arg(long, default_value_t = 224)]
+    pub width_min: isize,
+
+    #[arg(long, default_value_t = 640)]
+    pub width: isize,
+
+    #[arg(long, default_value_t = 800)]
+    pub width_max: isize,
+
+    #[arg(long, default_value_t = 224)]
+    pub height_min: isize,
+
+    #[arg(long, default_value_t = 640)]
+    pub height: isize,
+
+    #[arg(long, default_value_t = 800)]
+    pub height_max: isize,
+
+    #[arg(long, default_value_t = 80)]
+    pub nc: usize,
+
+    #[arg(long)]
+    pub trt: bool,
+
+    #[arg(long)]
+    pub cuda: bool,
+
+    #[arg(long)]
+    pub half: bool,
+
+    #[arg(long)]
+    pub coreml: bool,
+
+    #[arg(long, default_value_t = 0)]
+    pub device_id: usize,
+
+    #[arg(long)]
+    pub profile: bool,
+
+    #[arg(long)]
+    pub no_plot: bool,
+}
+
+fn main() -> Result<()> {
+    let args = Args::parse();
+
+    // build options
+    let options = Options::default();
+
+    // version & task
+    let options =
+        match args.version {
+            YOLOVersion::V5 => {
+                match args.task {
+                    YOLOTask::Classify => options
+                        .with_model(&args.model.unwrap_or("yolov5n-cls-dyn.onnx".to_string()))?,
+                    YOLOTask::Detect => {
+                        options.with_model(&args.model.unwrap_or("yolov5n-dyn.onnx".to_string()))?
+                    }
+                    YOLOTask::Segment => options
+                        .with_model(&args.model.unwrap_or("yolov5n-seg-dyn.onnx".to_string()))?,
+                    t => anyhow::bail!("Task: {t:?} is unsupported for {:?}", args.version),
+                }
+            }
+            YOLOVersion::V6 => match args.task {
+                YOLOTask::Detect => options
+                    .with_model(&args.model.unwrap_or("yolov6n-dyn.onnx".to_string()))?
+                    .with_nc(args.nc),
+                t => anyhow::bail!("Task: {t:?} is unsupported for {:?}", args.version),
+            },
+            YOLOVersion::V7 => match args.task {
+                YOLOTask::Detect => options
+                    .with_model(&args.model.unwrap_or("yolov7-tiny-dyn.onnx".to_string()))?
+                    .with_nc(args.nc),
+                t => anyhow::bail!("Task: {t:?} is unsupported for {:?}", args.version),
+            },
+            YOLOVersion::V8 => {
+                match args.task {
+                    YOLOTask::Classify => options
+                        .with_model(&args.model.unwrap_or("yolov8m-cls-dyn.onnx".to_string()))?,
+                    YOLOTask::Detect => {
+                        options.with_model(&args.model.unwrap_or("yolov8m-dyn.onnx".to_string()))?
+                    }
+                    YOLOTask::Segment => options
+                        .with_model(&args.model.unwrap_or("yolov8m-seg-dyn.onnx".to_string()))?,
+                    YOLOTask::Pose => options
+                        .with_model(&args.model.unwrap_or("yolov8m-pose-dyn.onnx".to_string()))?,
+                    YOLOTask::Obb => options
+                        .with_model(&args.model.unwrap_or("yolov8m-obb-dyn.onnx".to_string()))?,
+                }
+            }
+            YOLOVersion::V9 => match args.task {
+                YOLOTask::Detect => options
+                    .with_model(&args.model.unwrap_or("yolov9-c-dyn-f16.onnx".to_string()))?,
+                t => anyhow::bail!("Task: {t:?} is unsupported for {:?}", args.version),
+            },
+            YOLOVersion::V10 => match args.task {
+                YOLOTask::Detect => {
+                    options.with_model(&args.model.unwrap_or("yolov10n-dyn.onnx".to_string()))?
+                }
+                t => anyhow::bail!("Task: {t:?} is unsupported for {:?}", args.version),
+            },
+            YOLOVersion::RTDETR => match args.task {
+                YOLOTask::Detect => {
+                    options.with_model(&args.model.unwrap_or("rtdetr-l-f16.onnx".to_string()))?
+                }
+                t => anyhow::bail!("Task: {t:?} is unsupported for {:?}", args.version),
+            },
+        }
+        .with_yolo_version(args.version)
+        .with_yolo_task(args.task);
+
+    // device
+    let options = if args.cuda {
+        options.with_cuda(args.device_id)
+    } else if args.trt {
+        let options = options.with_trt(args.device_id);
+        if args.half {
+            options.with_fp16(true)
+        } else {
+            options
+        }
+    } else if args.coreml {
+        options.with_coreml(args.device_id)
+    } else {
+        options.with_cpu()
+    };
+    let options = options
+        .with_i00((1, 1, 4).into())
+        .with_i02((args.height_min, args.height, args.height_max).into())
+        .with_i03((args.width_min, args.width, args.width_max).into())
+        .with_confs(&[0.2, 0.15]) // class_0: 0.4, others: 0.15
+        // .with_names(&coco::NAMES_80)
+        .with_names2(&coco::KEYPOINTS_NAMES_17)
+        .with_profile(args.profile);
+    let mut model = YOLO::new(options)?;
+
+    // build dataloader
+    let dl = DataLoader::default()
+        .with_batch(model.batch() as _)
+        .load(args.source)?;
+
+    // build annotator
+    let annotator = Annotator::default()
+        .with_skeletons(&coco::SKELETONS_16)
+        .with_bboxes_thickness(7)
+        .without_masks(true) // No masks plotting.
+        .with_saveout("YOLO-Series");
+
+    // run & annotate
+    for (xs, _paths) in dl {
+        // let ys = model.run(&xs)?;  // way one
+        let ys = model.forward(&xs, args.profile)?; // way two
+        if !args.no_plot {
+            annotator.annotate(&xs, &ys);
+        }
+    }
+
+    Ok(())
+}