Add yolo-sam demo

benches/yolo.rs

@@ -31,9 +31,8 @@ fn yolo_stage_bench(
 
         let t = std::time::Instant::now();
         let _ys = black_box(model.postprocess(xs, x).unwrap());
-        let t1 = t.elapsed();
-        t_post += t1;
-        t_pipeline = t1;
+        t_post += t.elapsed();
+        t_pipeline += t0.elapsed();
     }
     match stage {
         Stage::Pre => t_pre,

examples/sam/main.rs

@@ -28,10 +28,10 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
 
     // build annotator
     let annotator = Annotator::default()
+        .with_bboxes_thickness(7)
         .without_bboxes_name(true)
         .without_bboxes_conf(true)
-        .without_mbrs_name(true)
-        .without_mbrs_conf(true)
+        .without_mbrs(true)
         .with_saveout("SAM");
 
     // run & annotate

examples/yolo-sam/main.rs

@@ -0,0 +1,62 @@
+use usls::{
+    models::{SamPrompt, YOLOTask, YOLOVersion, SAM, YOLO},
+    Annotator, DataLoader, Options, Vision,
+};
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    // build SAM
+    let options_encoder = Options::default()
+        .with_i00((1, 1, 1).into())
+        .with_model("mobile-sam-vit-t-encoder.onnx")?;
+    let options_decoder = Options::default()
+        .with_i11((1, 1, 1).into())
+        .with_i21((1, 1, 1).into())
+        .with_find_contours(true) // find contours or not
+        .with_model("mobile-sam-vit-t-decoder.onnx")?;
+    let mut sam = SAM::new(options_encoder, options_decoder)?;
+
+    // build YOLOv8-Det
+    let options_yolo = Options::default()
+        .with_yolo_version(YOLOVersion::V8)
+        .with_yolo_task(YOLOTask::Detect)
+        .with_model("yolov8m-dyn.onnx")?
+        .with_cuda(0)
+        .with_i00((1, 1, 4).into())
+        .with_i02((416, 640, 800).into())
+        .with_i03((416, 640, 800).into())
+        .with_find_contours(false)
+        .with_confs(&[0.45]);
+    let mut yolo = YOLO::new(options_yolo)?;
+
+    // load one image
+    let xs = vec![DataLoader::try_read("./assets/dog.jpg")?];
+
+    // build annotator
+    let annotator = Annotator::default()
+        .with_bboxes_thickness(7)
+        .without_bboxes_name(true)
+        .without_bboxes_conf(true)
+        .without_mbrs(true)
+        .with_saveout("YOLO+SAM");
+
+    // run & annotate
+    let ys_det = yolo.run(&xs)?;
+    for y_det in ys_det {
+        if let Some(bboxes) = y_det.bboxes() {
+            for bbox in bboxes {
+                let ys_sam = sam.run(
+                    &xs,
+                    &[SamPrompt::default().with_bbox(
+                        bbox.xmin(),
+                        bbox.ymin(),
+                        bbox.xmax(),
+                        bbox.ymax(),
+                    )],
+                )?;
+                annotator.annotate(&xs, &ys_sam);
+            }
+        }
+    }
+
+    Ok(())
+}

src/core/engine.rs

@@ -169,7 +169,7 @@ impl OrtEngine {
 
         // summary
         println!(
-            "{CHECK_MARK} ONNX | OpSet: {} | EP: {:?} | DType: {:?} | Params: {}",
+            "{CHECK_MARK} Backend: ONNXRuntime | OpSet: {} | EP: {:?} | DType: {:?} | Params: {}",
             model_proto.opset_import[0].version,
             device,
             inputs_attrs.dtypes,

src/models/sam.rs

@@ -149,7 +149,7 @@ impl SAM {
 
                 // contours
                 let mut rng = thread_rng();
-                let id = rng.gen_range(0..=255);
+                let id = rng.gen_range(0..20);
                 if self.find_contours {
                     let contours: Vec<imageproc::contours::Contour<i32>> =
                         imageproc::contours::find_contours_with_threshold(&luma, 0);