YOLO-NAS vs YOLOV8 for Real-time Object Detection - Pros and Cons

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In this video 📝 We’ll be taking a look at the new YOLO-NAS model from Deci AI and compare it with the YOLOv8 Model. This is a new state-of-the-art model for object detection. We are going to take a look at the model, go over how you can set it up and use a pretrained model to make predictions. We will the talk about the pros and cons for both models.

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Timestamps:
0:00 Introduction
1:10 YOLOv8
2:53 YOLO-NAS
4:25 YOLO-NAS Results
6:05 YOLOv8 Results
7:30 Pros and Cons

Tags:
#yolonas #yolov8 #objectdetection #ai #computervision #yolo

[NicolaiAI]

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[sabrimas]

i tried yolov8 for sometime, and when i want to try tuning hyperparameters using raytune, it shows an error, even though i followed the steps provided by Ultralytics, can you make a video about tuning yolov8 hyperparameters using raytune?

[sumanpahari]

Thank you so much for very good contain.Can we use any other pretrained model instead of coco for YOLO NAS.

[ashberten]

Thank you for your awesome tutorial. Do these models (YOLOv8 & YOLO-NAS) also work on Android? Please share your experience if you have tried it to deploy on Android.

[helloansuman]

How to train this on 8 GPUs on DGX A100?

[FatemehZaremehrjardi]

Thank you for the video! looking forward to watch your video about how to improve YoloNAS inference speed!

[rakeshkumarrout]

Hey Nic. This video is amazing.i have a question for you. Can you help me giving the approach, how to build a helmet detection model for motorbikes and a seat belt detector for cars and other vehicles as a single project? Kindly take the pain to share the right approach and models to use for that.

[polymir]

The reason for the slow performance with Yolo-nas is because your running inference using their .predict function. Their prediction functions are slow and not meant to be ran in a production system. You have to export the model into into something like onnx format to get the actual speeds. Once you do that, it should be much faster.

[NeuralNetwork-gozn]

hello, really nice tutorial!
I created a custom yolo detection with yolov8m as a base, but when I run it, as soon as the speed of the objects increases, the algorithm loses track of me and starts to "jerk" the video output. Does anyone have an idea how to fix this?
(yolov8m algorithm trained on 300 custom images)
Thanks so much to anyone who can help me!!

[ZeynepC]

Thanks for the video, I have a question. Which one is faster, yolov8 or yolo-NAS? Have you had a chance to test this?

[caiyu]

I did a comparison between yolo and detr in a limited datasets and found yolo is a little better even though both of them results are far from satisfaction. Our training datasets are only around 200.

[greendsnow]

Personally, I would detect you in an instant if I saw you outside :D
1ms, piew!
[That Yolo Guy]

[Polygone]

Love your content but I'm surprised that you didn't use more advanced comparators in the pros and cons like licenses, label format to train on custom data, ... it could have been more informative IMHO

[nhatpham]

Hi, what graphics card are you using?