What is YOLO-World?¶
YOLO-World is a YOLO-based open vocabulary model for open vocabulary detection.
YOLO-World was developed by Tencent's AI Lab.
Installation¶
To use YOLO-World with autodistill, you need to install the following dependency:
pip3 install autodistill-yolo-world
Quickstart¶
from autodistill_yolo_world import YOLOWorldModel
from autodistill.detection import CaptionOntology
from autodistill.utils import plot
import cv2
# define an ontology to map class names to our GroundedSAM prompt
# the ontology dictionary has the format {caption: class}
# where caption is the prompt sent to the base model, and class is the label that will
# be saved for that caption in the generated annotations
# then, load the model
base_model = YOLOWorldModel(
ontology=CaptionOntology(
{
"person": "person",
"car": "car",
}
),
model_type = "yolov8s-world.pt"
)
# run inference on a single image
results = base_model.predict("assets/test.jpg")
plot(
image=cv2.imread("assets/test.jpg"),
classes=base_model.ontology.classes(),
detections=results
)
# label all images in a folder called `context_images`
base_model.label("./context_images", extension=".jpeg")