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use anyhow::Result;
use clap::Parser;
use usls::{
models::YOLO, Annotator, DataLoader, Device, Options, Viewer, Vision, YOLOScale, YOLOTask,
YOLOVersion, COCO_SKELETONS_16,
};
#[derive(Parser, Clone)]
#[command(author, version, about, long_about = None)]
pub struct Args {
/// Path to the ONNX model
#[arg(long)]
pub model: Option<String>,
/// Input source path
#[arg(long, default_value_t = String::from("../../ultralytics/assets/bus.jpg"))]
pub source: String,
/// YOLO Task
#[arg(long, value_enum, default_value_t = YOLOTask::Detect)]
pub task: YOLOTask,
/// YOLO Version
#[arg(long, value_enum, default_value_t = YOLOVersion::V8)]
pub ver: YOLOVersion,
/// YOLO Scale
#[arg(long, value_enum, default_value_t = YOLOScale::N)]
pub scale: YOLOScale,
/// Batch size
#[arg(long, default_value_t = 1)]
pub batch_size: usize,
/// Minimum input width
#[arg(long, default_value_t = 224)]
pub width_min: isize,
/// Input width
#[arg(long, default_value_t = 640)]
pub width: isize,
/// Maximum input width
#[arg(long, default_value_t = 1024)]
pub width_max: isize,
/// Minimum input height
#[arg(long, default_value_t = 224)]
pub height_min: isize,
/// Input height
#[arg(long, default_value_t = 640)]
pub height: isize,
/// Maximum input height
#[arg(long, default_value_t = 1024)]
pub height_max: isize,
/// Number of classes
#[arg(long, default_value_t = 80)]
pub nc: usize,
/// Class confidence
#[arg(long)]
pub confs: Vec<f32>,
/// Enable TensorRT support
#[arg(long)]
pub trt: bool,
/// Enable CUDA support
#[arg(long)]
pub cuda: bool,
/// Enable CoreML support
#[arg(long)]
pub coreml: bool,
/// Use TensorRT half precision
#[arg(long)]
pub half: bool,
/// Device ID to use
#[arg(long, default_value_t = 0)]
pub device_id: usize,
/// Enable performance profiling
#[arg(long)]
pub profile: bool,
/// Disable contour drawing, for saving time
#[arg(long)]
pub no_contours: bool,
/// Show result
#[arg(long)]
pub view: bool,
/// Do not save output
#[arg(long)]
pub nosave: bool,
}
fn main() -> Result<()> {
let args = Args::parse();
// logger
if args.profile {
tracing_subscriber::fmt()
.with_max_level(tracing::Level::INFO)
.init();
}
// model path
let path = match &args.model {
None => format!(
"yolo/{}-{}-{}.onnx",
args.ver.name(),
args.scale.name(),
args.task.name()
),
Some(x) => x.to_string(),
};
// saveout
let saveout = match &args.model {
None => format!(
"{}-{}-{}",
args.ver.name(),
args.scale.name(),
args.task.name()
),
Some(x) => {
let p = std::path::PathBuf::from(&x);
p.file_stem().unwrap().to_str().unwrap().to_string()
}
};
// device
let device = if args.cuda {
Device::Cuda(args.device_id)
} else if args.trt {
Device::Trt(args.device_id)
} else if args.coreml {
Device::CoreML(args.device_id)
} else {
Device::Cpu(args.device_id)
};
// build options
let options = Options::new()
.with_model(&path)?
.with_yolo_version(args.ver)
.with_yolo_task(args.task)
.with_device(device)
.with_trt_fp16(args.half)
.with_ixx(0, 0, (1, args.batch_size as _, 4).into())
.with_ixx(0, 2, (args.height_min, args.height, args.height_max).into())
.with_ixx(0, 3, (args.width_min, args.width, args.width_max).into())
.with_confs(if args.confs.is_empty() {
&[0.2, 0.15]
} else {
&args.confs
})
.with_nc(args.nc)
.with_find_contours(!args.no_contours) // find contours or not
// .with_names(&COCO_CLASS_NAMES_80) // detection class names
// .with_names2(&COCO_KEYPOINTS_17) // keypoints class names
// .exclude_classes(&[0])
// .retain_classes(&[0, 5])
.with_profile(args.profile);
// build model
let mut model = YOLO::new(options)?;
// build dataloader
let dl = DataLoader::new(&args.source)?
.with_batch(model.batch() as _)
.build()?;
// build annotator
let annotator = Annotator::default()
.with_skeletons(&COCO_SKELETONS_16)
.without_masks(true) // no masks plotting when doing segment task
.with_bboxes_thickness(3)
.with_keypoints_name(false) // enable keypoints names
.with_saveout_subs(&["YOLO"])
.with_saveout(&saveout);
// build viewer
let mut viewer = if args.view {
Some(Viewer::new().with_delay(5).with_scale(1.).resizable(true))
} else {
None
};
// run & annotate
for (xs, _paths) in dl {
let ys = model.forward(&xs, args.profile)?;
let images_plotted = annotator.plot(&xs, &ys, !args.nosave)?;
// show image
match &mut viewer {
Some(viewer) => viewer.imshow(&images_plotted)?,
None => continue,
}
// check out window and key event
match &mut viewer {
Some(viewer) => {
if !viewer.is_open() || viewer.is_key_pressed(usls::Key::Escape) {
break;
}
}
None => continue,
}
// write video
if !args.nosave {
match &mut viewer {
Some(viewer) => viewer.write_batch(&images_plotted)?,
None => continue,
}
}
}
// finish video write
if !args.nosave {
if let Some(viewer) = &mut viewer {
viewer.finish_write()?;
}
}
Ok(())
}
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