YOLO-Series
| Detection | Instance Segmentation | Pose |
| :---------------: | :------------------------: |:---------------: |
| 
| 
|
|
| Classification | Obb |
| :------------------------: |:------------------------: |
|
|
| Head Detection | Fall Detection | Trash Detection |
| :------------------------: |:------------------------: |:------------------------: |
|
|
|
| YOLO-World | Face Parsing | FastSAM |
| :------------------------: |:------------------------: |:------------------------: |
|
|
|
## Quick Start
```Shell
# customized
cargo run -r --example yolo -- --task detect --ver v8 --nc 6 --model xxx.onnx # YOLOv8
# Classify
cargo run -r --example yolo -- --task classify --ver v5 --scale s --width 224 --height 224 --nc 1000 # YOLOv5
cargo run -r --example yolo -- --task classify --ver v8 --scale n --width 224 --height 224 --nc 1000 # YOLOv8
cargo run -r --example yolo -- --task classify --ver v11 --scale n --width 224 --height 224 --nc 1000 # YOLOv11
# Detect
cargo run -r --example yolo -- --task detect --ver v5 --scale n # YOLOv5
cargo run -r --example yolo -- --task detect --ver v6 --scale n # YOLOv6
cargo run -r --example yolo -- --task detect --ver v7 --scale t # YOLOv7
cargo run -r --example yolo -- --task detect --ver v8 --scale n # YOLOv8
cargo run -r --example yolo -- --task detect --ver v9 --scale t # YOLOv9
cargo run -r --example yolo -- --task detect --ver v10 --scale n # YOLOv10
cargo run -r --example yolo -- --task detect --ver v11 --scale n # YOLOv11
cargo run -r --example yolo -- --task detect --ver rtdetr --scale l # RTDETR
cargo run -r --example yolo -- --task detect --ver v8 --model yolo/v8-s-world-v2-shoes.onnx # YOLOv8-world
# Pose
cargo run -r --example yolo -- --task pose --ver v8 --scale n # YOLOv8-Pose
cargo run -r --example yolo -- --task pose --ver v11 --scale n # YOLOv11-Pose
# Segment
cargo run -r --example yolo -- --task segment --ver v5 --scale n # YOLOv5-Segment
cargo run -r --example yolo -- --task segment --ver v8 --scale n # YOLOv8-Segment
cargo run -r --example yolo -- --task segment --ver v11 --scale n # YOLOv8-Segment
cargo run -r --example yolo -- --task segment --ver v8 --model yolo/FastSAM-s-dyn-f16.onnx # FastSAM
# Obb
cargo run -r --example yolo -- --ver v8 --task obb --scale n --width 1024 --height 1024 --source images/dota.png # YOLOv8-Obb
cargo run -r --example yolo -- --ver v11 --task obb --scale n --width 1024 --height 1024 --source images/dota.png # YOLOv11-Obb
```
**`cargo run -r --example yolo -- --help` for more options**
## 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_nc(80)
// .with_names(&COCO_CLASS_NAMES_80)
.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/yolo/v8-n-face-dyn-f16.onnx) | |
| Head Detection | [yolov8-head-f16](https://github.com/jamjamjon/assets/releases/download/yolo/v8-head-f16.onnx) | |
| Fall Detection | [yolov8-falldown-f16](https://github.com/jamjamjon/assets/releases/download/yolo/v8-falldown-f16.onnx) | |
| Trash Detection | [yolov8-plastic-bag-f16](https://github.com/jamjamjon/assets/releases/download/yolo/v8-plastic-bag-f16.onnx) | |
| FaceParsing | [yolov8-face-parsing-dyn](https://github.com/jamjamjon/assets/releases/download/yolo/v8-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/yolo/CelebAMask-HQ-YOLO-Labels.zip)[[Python Script]](../../scripts/CelebAMask-HQ-To-YOLO-Labels.py) |
## 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, YOLOv11
```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)