YOLO-NAS Object Detection Model: What is, How to Use

Try the Model

Use the widget below to experiment with YOLO-NAS. You can detect COCO classes such as people, vehicles, animals, household items.

Overview

YOLO-NAS is an object detection model developed by Deci that achieves SOTA performances compared to YOLOv5, v7, and v8. YOLO-NAS is pre-trained on multiple prominent datasets including COCO, Objects365, and Roboflow 100. This overachieving pre-training ensures its precision amongst numerous tasks. Try training YOLO-NAS on your own dataset.

YOLO-NAS performance (Source: Deci YOLO-NAS README).

Use Cases

video surveillance

medical diagnosis

wildlife monitoring

real-time object detection tasks

‍

YOLO-NAS License

YOLO-NAS

is licensed under a

Apache 2.0

license.

Performance

Model	mAP	Latency (ms)
YOLO-NAS S	47.5	3.21
YOLO-NAS M	51.55	5.85
YOLO-NAS L	52.22	7.87
YOLO-NAS S INT-8	47.03	2.36
YOLO-NAS M INT-8	51.0	3.78
YOLO-NAS L INT-8	52.1	4.78

mAP numbers in table reported for Coco 2017 Val dataset and latency benchmarked for 640x640 images on Nvidia T4 GPU.

Deploy a YOLO-NAS API

You can use Roboflow Inference to deploy a

YOLO-NAS

API on your hardware. You can deploy the model on CPU (i.e. Raspberry Pi, AI PCs) and GPU devices (i.e. NVIDIA Jetson, NVIDIA T4).

Below are instructions on how to deploy your own model API.

First, install Inference:‍


pip install inference

To try a demo with a model trained on the Microsoft COCO dataset, use:


import inference
model = inference.load_roboflow_model("yolo-nas-s-640")
results = model.infer(image="YOUR_IMAGE.jpg")

Above, replace:

YOUR_IMAGE.jpg with the path to your image.

You can also run fine-tuned models with Inference.

Retrieve your Roboflow API key and save it in an environment variable called ROBOFLOW_API_KEY:


export ROBOFLOW_API_KEY="your-api-key"

To use your model, run the following code:


import inference
model = inference.load_roboflow_model("model-name/version")
results = model.infer(image="YOUR_IMAGE.jpg")

Above, replace:

YOUR_IMAGE.jpg with the path to your image.
model_id/version with the YOLO-NAS model ID and version you want to use. Learn how to retrieve your model and version ID.

YOLO-NAS

Try the Model

Overview

Use Cases

YOLO-NAS License

Performance

Deploy a YOLO-NAS API

Label Data Automatically with YOLO-NAS