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<div align="center"> <p> <a align="center" href="" target="_blank"> <img width="850" src="https://media.roboflow.com/open-source/autodistill/autodistill-banner.png?3" > </a> </p> </div>Autodistill YOLO-NAS Module
This repository contains the code supporting the YOLO-NAS target model for use with Autodistill.
YOLO-NAS is an object detection model developed by Deci AI.
You can use autodistill to train a YOLO-NAS object detection model on a dataset of labelled images generated by the base models that autodistill supports.
Read the full Autodistill documentation.
Read the YOLO-NAS Autodistill documentation.
Installation
To use the YOLO-NAS target model, you will need to install the following dependency:
pip3 install autodistill-yolonas
Quickstart
from autodistill_yolonas import YOLONAS
target_model = YOLONAS()
# train a model
# specify the directory where your annotations (in YOLO format) are stored
target_model.train("./context_images_labeled", epochs=20)
# run inference on the new model
pred = target_model.predict("./context_images_labeled/train/images/dog-7.jpg", confidence=0.01)
License
The YOLO-NAS model is licensed under the YOLO-NAS License.
🏆 Contributing
We love your input! Please see the core Autodistill contributing guide to get started. Thank you 🙏 to all our contributors!