YOLOv8: How to Train for Object Detection on a Custom Dataset

YOLOv8 is the latest installment of the highly influential YOLO (You Only Look Once) architecture. YOLOv8 was developed by Ultralytics, a team known for its work on YOLOv3 and YOLOv5.

Following the trend set by  YOLOv6 and YOLOv7, we have at our disposal object detection, but also instance segmentation, and image classification. The model itself is created in PyTorch and runs on both the CPU and GPU. As with YOLOv5, we also have a number of various exports such as TF.js or CoreML.

In this video, I'll take you through a step-by-step tutorial on Google Colab, and show you how to train your own YOLOv8 object detection model.

Chapters:

0:00 Introduction
0:51 Overview
3:09 Setting up the Python environment
5:36 New API: CLI vs. Python SDK
8:51 Prepare the YOLOv8 object detection dataset
12:29 Train YOLOv8 model on custom dataset
13:54 YOLOv8 model evaluation
16:47 YOLOv8 model inference on images and videos
18:44 YOLOv8 model deployment and inference via hosted API
19:58 Conclusion

Resources:

[ayanpaul]

Thank you Roboflow!! Always keeps us updated🤝🤝

[goodtechdoor]

Epic, waiting on the next parts. Cheering for Roboflow & Ultralytics teams !

[matheusmartins]

Good diction, i'm currently learning English, and I find your pronunciation much easier to understand compared to most people, not sure why. Great video!

[AndroidDjRealEDM]

Finally is really simple to use for industrial projects!

[kevinwoodrobotics]

Great video! Definitely useful to train your own dataset since yolov8 was originally trained on COCO so it may not work for special applications!

[sujinyang]

This video has made my DL work so much easier! Thx for the great tutorial on YoloV8 and connecting it to Roboflow workflow😊😊

[giridharidash]

00:05 Yellow V8 is the latest object detection model that fine tunes much faster than its predecessors
02:29 Yellow V3 and Yellow V5 repositories have almost 45, 000 stars on GitHub and will solve previous issues in the Yellow V8 project.
04:58 Importing Yolo from ultralytics and running inference
07:36 Creating a dataset for training the YOLO model using Roboflow
10:16 Use Cinema to label images and create a dataset for training
13:00 The training has been completed and the results are satisfactory.
15:41 Training the models could take longer and yield better results.
18:04 Yellow V8 model can be trained and deployed for inference using a single line of code.
20:16 Comparing yellow V8 to previous object detection models
Crafted by Merlin AI.

[dinesh]

good job Roboflow and Ultralytics team... I want similar videos in docker... Thank you

[anujjain]

Thank you Brother, The Roboflow is just Amazing and super easy to use.

[hggaming]

Very simple and useful… Thank you so much

[shivamgoel]

Great video! very helpful to get started with Yolov8

[afrahthahir]

Is this working good in real time rtsp stream fetched from CCTV cameras??

[FatemehZaremehrjardi]

Thanks!
I tested the model on some images I can see the results in text but the bounding boxes on the pictures won't save.

[serverxeon]

Is there something wrong with your code, or did recent ultralytics version change break the code?

[anren]

at 13:45 you can utilize gpu by typing "device=0" so it can train faster

[jojis]

Hi, thank you for the lovely video.
Although I am getting this error when I initiate training: FileNotFoundError:
Dataset not found ⚠, missing paths

[Willow.]

what is the best.pt file? ı just downloaded it and closed everything else. did ı save my model? can ı use it?

[fatrat]

Hi, how if i don't want to use yolov8n, and i want to change yolov8m, where should i change it? Someone pls help me thx

[evanshlom]

Can this work with raspberry pi? (Pi4b with thermal camera.

[entertainmentvideos]

hello sir after detection there is no predict directory where my video and test images are stored... detection on video perform and completed successfully but predict directory is not