<div align="center">
<p>
<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 OWLv2 Module
This repository contains the code supporting the OWLv2 base model for use with [Autodistill](https://github.com/autodistill/autodistill).
OWLv2 is a zero-shot object detection model that follows from on the OWL-ViT architecture. OWLv2 has an open vocabulary, which means you can provide arbitrary text prompts for the model. You can use OWLv2 with autodistill for object detection.
Read the full [Autodistill documentation](https://autodistill.github.io/autodistill/).
Read the [OWLv2 Autodistill documentation](https://autodistill.github.io/autodistill/base_models/owlv2/).
## Installation
To use OWLv2 with autodistill, you need to install the following dependency:
```bash
pip3 install autodistill-owlv2
```
## Quickstart
```python
from autodistill_owlv2 import OWLv2
from autodistill.detection import CaptionOntology
# define an ontology to map class names to our OWLv2 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 = OWLv2(
ontology=CaptionOntology(
{
"person": "person",
"a forklift": "forklift"
}
)
)
# run inference on a single image
results = base_model.predict("./context_images/image.png")
base_model.label("./context_images", extension=".jpeg")
```
## License
This model is licensed under an [Apache 2.0](LICENSE) ([see original model implementation license](https://huggingface.co/docs/transformers/main/en/model_doc/owlv2), and the corresponding [HuggingFace Transformers documentation](https://huggingface.co/docs/transformers/main/en/model_doc/owlv2)).
## 🏆 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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