Add Small and Nano sizes of YOLO models version 8 and above

Models/yolo11n.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0690c675a942f4dc4f463b3e4e89520117aeea3fd767784df2934705c91ed11b
+size 5384988

Models/yolo11s.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:58744f876fbfe4c5beb52c2421b29028da824f8eb93932440cdd2ccbba2bdac2
+size 19040166

Models/yolo12n.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e317f39e7bc492e3ebd1217120c394f338b3504d2867c157eaf7ba0cdaf241be
+size 5389057

Models/yolo12s.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c574540176cf1310a171fd3b0af3c844acc9e4f64f45a59482e5238bb47e76fc
+size 18731306

Models/yolov8s.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:77e21642dcbb60907a2ef5c54fba53114bc4110be8dc0aadc5f638dd5c274935
+size 22445269

Models/yolov9s.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b88918c915573583869c664f4bc5510e61ffe3c9abfc46fff373af3db826c745
+size 14638367

Models/yolov9t.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f204063b506f17c33c6806932618de0b228e90e0c4ae3152e6e480da8a25692d
+size 4429860

README.md

@@ -2,16 +2,17 @@
 library_name: unity-sentis
 pipeline_tag: object-detection
 ---
-# YOLOv8n validated for Unity Sentis (Version 2.1.2)
+# YOLOv8, YOLOv9, YOLO11, YOLO12 validated for Sentis 2.1.2 in Unity 6
 
-[YOLOv8n](https://docs.ultralytics.com/models/yolov8/) is a real-time multi-object recognition model confirmed to run in Unity 6000.
+[YOLO](https://docs.ultralytics.com/models/) is a real-time multi-object recognition model.
+Small and Nano model sizes are included for YOLO version 8 and above (except version 10 which uses NMS-free approach).
 
 ## How to Use
 
-* Create a new scene in Unity 6000;
+* Create a new scene in Unity 6;
 * Install `com.unity.sentis` version `2.1.2` from the package manager;
-* Add the `RunYOLO8n.cs` script to the Main Camera;
-* Drag the `Models/yolov8n.onnx` file into the `Model Asset` field;
+* Add the `RunYOLO.cs` script to the Main Camera;
+* Drag an appropriate `.onnx` file from the `Models` folder into the `Model Asset` field;
 * Drag the `classes.txt` file into the `Classes Asset` field;
 * Create a `GameObject > UI > Raw Image` object in the scene, set its width and height to 640, and link it as the `Display Image` field;
 * Drag the `Border Texture.png` file into the `Border Texture` field;

RunYOLO8n.cs → RunYOLO.cs

@@ -7,14 +7,14 @@ using System.IO;
 using FF = Unity.Sentis.Functional;
 
 /*
- *  YOLOv8n Inference Script
+ *  YOLO Inference Script
  *  ========================
  * 
  * Place this script on the Main Camera and set the script parameters according to the tooltips.
  * 
  */
 
-public class RunYOLO8n : MonoBehaviour
+public class RunYOLO : MonoBehaviour
 {
     [Tooltip("Drag a YOLO model .onnx file here")]
     public ModelAsset modelAsset;
@@ -46,14 +46,14 @@ public class RunYOLO8n : MonoBehaviour
     private const int imageWidth = 640;
     private const int imageHeight = 640;
 
-    //The number of classes in the model
-    private const int numClasses = 80;
-
     private VideoPlayer video;
 
     List<GameObject> boxPool = new();
 
+    [Tooltip("Intersection over union threshold used for non-maximum suppression")]
     [SerializeField, Range(0, 1)] float iouThreshold = 0.5f;
+
+    [Tooltip("Confidence score threshold used for non-maximum suppression")]
     [SerializeField, Range(0, 1)] float scoreThreshold = 0.5f;
 
     Tensor<float> centersToCorners;

info.json

@@ -1,9 +1,16 @@
 {
     "code": [
-        "RunYOLO8n.cs"
+        "RunYOLO.cs"
     ],
     "models": [
-        "yolov8n.onnx"
+        "yolov8n.onnx",
+        "yolov8s.onnx",
+        "yolov9t.onnx",
+        "yolov9s.onnx",
+        "yolo11n.onnx",
+        "yolo11s.onnx",
+        "yolo12n.onnx",
+        "yolo12s.onnx"
     ],
     "data": [
         "classes.txt"