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70 lines
1.9 KiB
Rust
70 lines
1.9 KiB
Rust
use anyhow::Result;
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use usls::{
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models::{SamPrompt, SAM, YOLO},
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Annotator, DataLoader, Options, Scale,
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};
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#[derive(argh::FromArgs)]
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/// Example
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struct Args {
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/// device
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#[argh(option, default = "String::from(\"cpu:0\")")]
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device: String,
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}
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fn main() -> Result<()> {
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tracing_subscriber::fmt()
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.with_env_filter(tracing_subscriber::EnvFilter::from_default_env())
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.with_timer(tracing_subscriber::fmt::time::ChronoLocal::rfc_3339())
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.init();
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let args: Args = argh::from_env();
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// build SAM
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let (options_encoder, options_decoder) = (
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Options::mobile_sam_tiny_encoder().commit()?,
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Options::mobile_sam_tiny_decoder().commit()?,
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);
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let mut sam = SAM::new(options_encoder, options_decoder)?;
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// build YOLOv8
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let options_yolo = Options::yolo_detect()
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.with_model_scale(Scale::N)
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.with_model_version(8.0.into())
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.with_model_device(args.device.as_str().try_into()?)
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.commit()?;
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let mut yolo = YOLO::new(options_yolo)?;
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// load one image
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let xs = DataLoader::try_read_batch(&["images/dog.jpg"])?;
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// build annotator
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let annotator = Annotator::default()
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.with_bboxes_thickness(7)
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.without_bboxes_name(true)
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.without_bboxes_conf(true)
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.without_mbrs(true)
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.with_saveout("YOLO-SAM");
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// run & annotate
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let ys_det = yolo.forward(&xs)?;
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for y_det in ys_det.iter() {
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if let Some(bboxes) = y_det.bboxes() {
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for bbox in bboxes {
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let ys_sam = sam.forward(
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&xs,
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&[SamPrompt::default().with_bbox(
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bbox.xmin(),
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bbox.ymin(),
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bbox.xmax(),
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bbox.ymax(),
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)],
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)?;
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annotator.annotate(&xs, &ys_sam);
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}
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}
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}
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Ok(())
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}
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