This repository contains the code supporting the Grounding DINO base model for use with Autodistill.
Grounding DINO is a zero-shot object detection model developed by IDEA Research. You can distill knowledge from Grounding DINO into a smaller model using Autodistill.
Read the Grounding DINO Autodistill documentation.
To use the Grounding DINO base model, you will need to install the following dependency:
pip3 install autodistill-grounding-dino
from autodistill_grounding_dino import GroundingDINO
from autodistill_yolov8 import YOLOv8
# define an ontology to map class names to our GroundingDINO 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 = GroundingDINO(ontology=CaptionOntology({"shipping container": "container"}))
# label all images in a folder called `context_images`
base_model.label("./context_images", extension=".jpeg")
The code in this repository is licensed under an Apache 2.0 license.
We love your input! Please see the core Autodistill contributing guide to get started. Thank you 🙏 to all our contributors!