YOLOv11: SOTA Computer Vision Model

What is YOLO11?

YOLO11 is a computer vision model architecture developed by Ultralytics, the creators of YOLOv5. You can deploy YOLO11 models on a wide range of devices, including NVIDIA Jetson, NVIDIA GPUs, and macOS systems with Roboflow Inference, an open source Python package for running vision models.

What is YOLOv11?

YOLO11 (also known as YOLOv11) is a computer vision model architecture developed by Ultralytics, the creators of the popular YOLOv5 and YOLOv8 models. You can train YOLO11 models for object detection, segmentation, classification, keypoint detection, and Oriented Bounding Box detection.

You can run YOLO11 models on a NVIDIA Jetson, NVIDIA GPUs, and macOS systems with Roboflow Inference, an open source Python package for running vision models.

Deploy a YOLO11 Model

To deploy a YOLO11 model, first install Inference with pip install inference. Then, use the following code:

from inference import get_model
import supervision as sv
from inference.core.utils.image_utils import load_image_bgr

image = load_image_bgr("https://media.roboflow.com/inference/vehicles.png")
model = get_model(model_id="yolo11x-640")
results = model.infer(image)[0]
results = sv.Detections.from_inference(results)
annotator = sv.BoxAnnotator(thickness=4)
annotated_image = annotator.annotate(image, results)
annotator = sv.LabelAnnotator(text_scale=2, text_thickness=2)
annotated_image = annotator.annotate(annotated_image, results)
sv.plot_image(annotated_image)

from inference import InferencePipeline
from inference.core.interfaces.stream.sinks import render_boxes

pipeline = InferencePipeline.init(
    model_id="yolov11n-640",
    video_reference=0,
    on_prediction=render_boxes
)
pipeline.start()
pipeline.join()

Find YOLO11 Datasets

Using Roboflow Universe, you can find datasets for use in training YOLO11 models, and pre-trained models you can use out of the box.

Selected YOLO11 Models and Datasets

Plane Detection

Count airplanes photographed using aerial imagery techniques.

Warehouse Item Detection

Detect forklifts, pallets, and small load carriers, among other items you would find in a warehouse environment.

License Plate Detection

Identify license plates in an image.

Search for Datases

Search for YOLO11 Models on Roboflow Universe, the world's largest collection of open source computer vision datasets and APIs

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Train a YOLO11 Model

Notebooks

YOLO11 Object Detection

You can train a YOLO11 model using the Ultralytics command line interface.

To train a model, install Ultralytics:

pip install ultralytics

Then, use the following command to train your model:

yolo task=detect
mode=train
model=yolo11s.pt
data=dataset/data.yaml
epochs=100
imgsz=640

Replace data with the name of your YOLO11-formatted dataset. Learn more about the YOLO11 format.

You can then test your model on images in your test dataset with the following command:

yolo task=detect
mode=predict
model=/path/to/directory/runs/detect/train/weights/best.pt
conf=0.25
source=dataset/test/images

Once you have a model, you can deploy it with Roboflow.

Deploy Your YOLO11 Model

YOLO11 Model Sizes

There are five sizes of YOLO11 models available for each task type. The model sizes are nano, small, medium, large, and extra-large.

When benchmarked on the COCO dataset for object detection, here is how YOLO11 performs.

Model

Size (px)

mAP^{50-95 val}

YOLO11n

640

39.5

YOLO11s

640

47.0

YOLO11m

640

51.5

YOLO11l

640

53.4

YOLO11x

640

54.7

Frequently Asked Questions

What is the license for YOLO11?

The code for YOLO11 is licensed under an AGPL-3.0 license.

Who created YOLO11?

YOLO11 was built by Ultralytics.

What are the main features in YOLO11?

YOLO11 has a new Cross Stage Partial with Kernel Size 2 block that helps to improve processing speed. The model also has a new Convolutional block with Parallel Spatial Attention, which improves upon the convolutions used in previous model versions.

In addition, YOLO11 has a developer-first command-line interface and Python package through which you can work with YOLO11, just like YOLO11.

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Explore Ultralytics YOLOv11