YOLO-Series

| Detection | Instance Segmentation | Pose | | :---------------: | :------------------------: |:---------------: | |

| | Classification | Obb | | :------------------------: |:------------------------: | |

| Head Detection | Fall Detection | Trash Detection | | :------------------------: |:------------------------: |:------------------------: | |

| YOLO-World | Face Parsing | FastSAM | | :------------------------: |:------------------------: |:------------------------: | |

## Quick Start ```Shell # Classify cargo run -r --example yolo -- --task classify --ver v5 # YOLOv5 cargo run -r --example yolo -- --task classify --ver v8 # YOLOv8 # Detect cargo run -r --example yolo -- --task detect --ver v5 # YOLOv5 cargo run -r --example yolo -- --task detect --ver v6 # YOLOv6 cargo run -r --example yolo -- --task detect --ver v7 # YOLOv7 cargo run -r --example yolo -- --task detect --ver v8 # YOLOv8 cargo run -r --example yolo -- --task detect --ver v9 # YOLOv9 cargo run -r --example yolo -- --task detect --ver v10 # YOLOv10 cargo run -r --example yolo -- --task detect --ver rtdetr # YOLOv8-RTDETR cargo run -r --example yolo -- --task detect --ver v8 --model yolov8s-world-v2-shoes.onnx # YOLOv8-world # Pose cargo run -r --example yolo -- --task pose --ver v8 # YOLOv8-Pose # Segment cargo run -r --example yolo -- --task segment --ver v5 # YOLOv5-Segment cargo run -r --example yolo -- --task segment --ver v8 # YOLOv8-Segment cargo run -r --example yolo -- --task segment --ver v8 --model FastSAM-s-dyn-f16.onnx # FastSAM # Obb cargo run -r --example yolo -- --task obb --ver v8 # YOLOv8-Obb ```

other options

`--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

## YOLOs configs with `Options`

Use official YOLO Models

```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")?; ```

Cutomized your own YOLO model

```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")?; ```

## 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)
[[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

YOLOv5

[Here](https://docs.ultralytics.com/yolov5/tutorials/model_export/)

YOLOv6

[Here](https://github.com/meituan/YOLOv6/tree/main/deploy/ONNX)

YOLOv7

[Here](https://github.com/WongKinYiu/yolov7?tab=readme-ov-file#export)

YOLOv8

```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 ```

YOLOv9

[Here](https://github.com/WongKinYiu/yolov9/blob/main/export.py)

YOLOv10

[Here](https://github.com/THU-MIG/yolov10#export)