YOLO11 support (#468)

* Add support for YOLO11

* style fix

Author: mgumowsk

src/model_api/models/__init__.py

@@ -34,7 +34,7 @@
     get_contours,
 )
 from .visual_prompting import Prompt, SAMLearnableVisualPrompter, SAMVisualPrompter
-from .yolo import YOLO, YOLOF, YOLOX, YoloV3ONNX, YoloV4, YOLOv5, YOLOv8
+from .yolo import YOLO, YOLO11, YOLOF, YOLOX, YoloV3ONNX, YoloV4, YOLOv5, YOLOv8
 
 classification_models = [
     "resnet-18-pytorch",
@@ -92,6 +92,7 @@
     "TopDownKeypointDetectionPipeline",
     "VisualPromptingResult",
     "YOLO",
+    "YOLO11",
     "YOLOF",
     "YOLOv3ONNX",
     "YOLOv4",

src/model_api/models/yolo.py

@@ -746,7 +746,7 @@ def __init__(self, inference_adapter, configuration, preload=False):
         out_shape = output.shape
         if len(out_shape) != 3:
             self.raise_error("the output must be of rank 3")
-        if self.labels and len(self.labels) + 4 != out_shape[1]:
+        if self.params.labels and len(self.params.labels) + 4 != out_shape[1]:
             self.raise_error("number of labels must be smaller than out_shape[1] by 4")
 
     @classmethod
@@ -799,20 +799,20 @@ def postprocess(self, outputs, meta) -> DetectionResult:
         )
         keep_top_k = 30000
         iou_threshold = self.params.iou_threshold
-        if self.agnostic_nms:  # type: ignore[attr-defined]
+        if self.params.agnostic_nms:
             boxes = boxes[
                 nms(
                     boxes[:, 2],
                     boxes[:, 3],
                     boxes[:, 4],
                     boxes[:, 5],
                     boxes[:, 1],
-                    iou_threshold,  # type: ignore[attr-defined]
+                    iou_threshold,
                     keep_top_k=keep_top_k,
                 )
             ]
         else:
-            boxes, _ = multiclass_nms(boxes, iou_threshold, keep_top_k)  # type: ignore[attr-defined]
+            boxes, _ = multiclass_nms(boxes, iou_threshold, keep_top_k)
         inputImgWidth = meta["original_shape"][1]
         inputImgHeight = meta["original_shape"][0]
         resize_meta = ResizeMetadata.compute(
@@ -853,3 +853,9 @@ class YOLOv8(YOLOv5):
     """YOLOv5 and YOLOv8 are identical in terms of inference"""
 
     __model__ = "YOLOv8"
+
+
+class YOLO11(YOLOv5):
+    """YOLO11 uses the same inference approach as YOLOv5 and YOLOv8"""
+
+    __model__ = "YOLO11"