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Merge pull request #374 from robertknight/yolo-v11
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Update YOLO example instructions to use YOLO v11
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robertknight authored Oct 1, 2024
2 parents a1b91af + 724bf23 commit 099268d
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2 changes: 1 addition & 1 deletion rten-examples/README.md
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Expand Up @@ -59,7 +59,7 @@ The examples have been chosen to cover common tasks and popular models.
- **rmbg** - Background removal using [BRIA Background Removal](https://huggingface.co/briaai/RMBG-1.4)
- **segment_anything** - Image segmentation using [Segment Anything](https://segment-anything.com)
- **trocr** - Recognize text using [TrOCR](https://arxiv.org/abs/2109.10282)
- **yolo** - Object detection using [YOLO v8](https://github.com/ultralytics/ultralytics)
- **yolo** - Object detection using [Ultralytics YOLO](https://github.com/ultralytics/ultralytics)
### Text
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21 changes: 12 additions & 9 deletions rten-examples/src/yolo.rs
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Expand Up @@ -44,7 +44,7 @@ Options:
Print only a summary of the objects found
",
bin_name = parser.bin_name().unwrap_or("detr")
bin_name = parser.bin_name().unwrap_or("yolo")
);
std::process::exit(0);
}
Expand Down Expand Up @@ -76,25 +76,28 @@ fn resource_path(path: &str) -> PathBuf {
abs_path
}

/// Detect objects in images using the YOLO v8 model.
/// Detect objects in images using Ultralytics YOLO models.
///
/// This example has been tested with YOLO v8 and YOLO v11. The steps are the
/// same for both versions.
///
/// See <https://docs.ultralytics.com/modes/export/> for current instructions on
/// how to get YOLO v8 models in ONNX format.
/// how to get YOLO v11 models in ONNX format.
///
/// Note that this model is AGPL-licensed. If you need an object detection model
/// for commercial purposes, you can either buy a license from Ultralytics, or
/// use an alternate model such as DETR.
/// Note that these models are AGPL-licensed. If you need an object detection
/// model for commercial purposes, you can either buy a license from
/// Ultralytics, or use an alternate model such as DETR.
///
/// ```
/// pip install ultralytics
/// yolo mode=export model=yolov8s.pt format=onnx
/// rten-convert yolov8s.onnx yolov8.rten
/// yolo mode=export model=yolov11s.pt format=onnx
/// rten-convert yolov11s.onnx yolov11.rten
/// ```
///
/// Run this program on an image:
///
/// ```
/// cargo run --release --bin yolo yolov8.rten image.jpg
/// cargo run --release --bin yolo yolov11.rten image.jpg
/// ```
fn main() -> Result<(), Box<dyn Error>> {
let args = parse_args()?;
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