<div align="center">
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<a align="center" href="" target="_blank">
<img
width="850"
src="https://media.roboflow.com/open-source/autodistill/autodistill-banner.png"
>
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# Autodistill YOLO-World Module
This repository contains the code supporting the YOLO-World base model for use with [Autodistill](https://github.com/autodistill/autodistill).
[YOLO-World](https://github.com/AILab-CVC/YOLO-World), developed by Tencent's AI Lab, is a zero-shot object detection model that can run in close-to-real-time on powerful GPUs. You can provide arbitrary text prompts to detect objects in images, and the model will return bounding boxes and class labels for the objects it finds.
You can use YOLO-World in Autodistill to detect objects.
Read the full [Autodistill documentation](https://autodistill.github.io/autodistill/).
Read the [YOLO-World Autodistill documentation](https://autodistill.github.io/autodistill/base_models/yolo_world/).
## Installation
To use YOLO-World with autodistill, you need to install the following dependency:
```bash
pip3 install autodistill-yolo-world
```
## Quickstart
```python
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 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 = YOLOWorldModel(ontology=CaptionOntology({"book": "book"}))
# predict on an image
result = base_model.predict("bookshelf.jpeg", confidence=0.1)
plot(
image=cv2.imread("./bookshelf.jpeg"),
classes=base_model.ontology.classes(),
detections=result
)
```
## License
The YOLO-World model is released under a [GPT-3.0 license](https://github.com/AILab-CVC/YOLO-World).
## 🏆 Contributing
We love your input! Please see the core Autodistill [contributing guide](https://github.com/autodistill/autodistill/blob/main/CONTRIBUTING.md) to get started. Thank you 🙏 to all our contributors!
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