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YOLO11 support #468

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YOLO11 support #468

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3e32710
Add support for YOLO11
mgumowsk Jan 14, 2026
c58c44a
style fix
mgumowsk Jan 14, 2026
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3 changes: 2 additions & 1 deletion src/model_api/models/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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",
Expand Down Expand Up @@ -92,6 +92,7 @@
"TopDownKeypointDetectionPipeline",
"VisualPromptingResult",
"YOLO",
"YOLO11",
"YOLOF",
"YOLOv3ONNX",
"YOLOv4",
Expand Down
14 changes: 10 additions & 4 deletions src/model_api/models/yolo.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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(
Expand Down Expand Up @@ -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"
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