Ultralytics is the company and Python package behind the YOLO (You Only Look Once) family of real-time object detection models, maintained by Ultralytics Inc. It ranks #19 in trending tech at roughly 1.2% usage share. It's trending because it's become the default toolkit for practical computer vision — a few lines of Python can load a pretrained YOLO model and detect, classify, segment, or track objects in images and video in real time.
The ultralytics package wraps model loading and inference into a single, consistent API.
from ultralytics import YOLO
# load a pretrained YOLO model (auto-downloads weights on first use)
model = YOLO("yolo11n.pt")
# run detection on an image
results = model("street.jpg")
for result in results:
for box in result.boxes:
cls_name = result.names[int(box.cls)]
confidence = float(box.conf)
print(f"{cls_name}: {confidence:.2f}")
result.save(filename="street_detected.jpg")Install the package with pip; a GPU with CUDA speeds up inference and training but isn't required to get started.
# install Ultralytics
pip install ultralytics
# quick CLI test — runs detection on a sample image
yolo predict model=yolo11n.pt source='https://ultralytics.com/images/bus.jpg'