cargo run --release -- assets/football.jpg
# or
cargo run --release -- assets/football.jpg --task pose

This is a port of Ultralytics YOLOv8. The implementation is based on the tinygrad version and on the model architecture described in this issue. The supported tasks are object detection and pose estimation.

You can try this model online on the Candle YOLOv8 Space. The model then fully runs in your browser using WebAssembly - if you use a custom image it will never leave your phone/computer!

cargo run --example yolo-v8 --release -- candle-examples/examples/yolo-v8/assets/bike.jpg

This prints details about the detected objects and generates a bike.pp.jpg file.

Image source: wikimedia.

cargo run --example yolo-v8 --release -- \
  candle-examples/examples/yolo-v8/assets/bike.jpg --task pose

• --which: select the model variant to be used, n, s , m, l, or x by increasing size and quality.
• --task: detect for object detection and pose for pose estimation.
• --legend-size: the size of the characters to print.
• --model: use a local model file rather than downloading it from the hub.