Mastering YOLO NAS: Object Detection

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In this tutorial, you'll learn how to create a custom object detection model using YOLO-NAS. And that's not all – we'll also look at the different cases you might face when creating or collecting a dataset.

Get ready to build, train, and share your own object detection solution with the world!

In this tutorial, you'll learn how to create a custom object detection model using YOLOv8 and Ultralytics Plus. And that's not all – we'll also deploying it on Hugging Face Space. Get ready to build, train, and share your own object detection solution with the world!

00:00 - Intro
0:22 - Steps
1:33 - Knowledge requirement
1:58 - What is Yolo Nas
2:30 - Who Created it ?
4:37 - Installation
7:22 - Environment Setup
11:19 - Dataset
13:38 - Collecting Dataset
16:11 - Annotate Images
19:17 - Folder Structure For Dataset
21:10 - Download Dataset
23:37 - Start Coding
26:38 - Data Parameters
29:55 - Training Parameters
32:12 - Start Training
34:44 - Image Prediction
35:30 - Video Prediction
36:10 - Evaluation
37:01 - Outro

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#yolo #objectdetection #python #yolonas #roboflow #computervision
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you're on the right path in sha Allah, keep going brother.

UnitedKonvict
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thank you buddy ! i learned a lot .. now i am training my custom images on yolo nas with 100 epoch ... despite that i have a powerful GPU (24 GB) the process is slow (i checked cuda and everything is running fine) .... its taking 23 sec for training and during these 23 sec i see my GPU usage as almosy 90% but validation is not using GPU, validation is taking 10 sec. which is too much ... for yolo V8 it took me like 5 min for 100 epoch ... my dataset has 100 images... any idea why ?

sanahnahk
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please make this types of project with streamlit.

mdriad
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i still have problems with super-gradient installation
Using cached onnx-1.15.0.tar.gz (12.3 MB)
Installing build dependencies ... done
Getting requirements to build wheel ... error
error: subprocess-exited-with-error

× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> [18 lines of output]
what should i do ?

malikakarmach