YOLO-NAS module for use with Autodistill
Project description
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 YOLOv5 target model, you will need to install the following dependency:
pip3 install autodistill-yolo-nas
Quickstart
from autodistill_yolo_nas import YOLONAS
target_model = YOLONAS("YOLOv5n.pt")
# 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!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for autodistill-yolonas-0.1.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0dafe33d83e2ea42016deb0e7add7bb0d6882a820dfce21209ccf0510448a41f |
|
MD5 | 5c50bfdb5147f8220669768a3d9ad5cf |
|
BLAKE2b-256 | 049176aa202475b36e3c142fa743d7ff9fc2a944a003bdac09d86485f9564076 |
Hashes for autodistill_yolonas-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 22535f03df17a065ef5069029c28d4ef7330ad8dc68d6513da99dc6f01f82ebb |
|
MD5 | 7a2776195c5fd138261fbe77444719fc |
|
BLAKE2b-256 | 24a27806099022dca3e833ba11ebd8f3c5050813b759b21d17e147290a07ea6f |