YOLOv8 is the latest version 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.

YOLOv6 and YOLOv7 started doing segmentation and classification tasks along with the object detection task. YOLOv8 follows the same trend.The model itself is created in PyTorch and runs on both the CPU and GPU.

GIthub: https://github.com/deepakat002/yolov8
YOLOv8 github: https://github.com/ultralytics/ultral...
YOLOv8 Docs: https://docs.ultralytics.com/
Dataset: https://kaggle.com/datasets/outliersl...


This tutorial contains:
1. How to download data
2. How to prepare a trainval split dataset
3. How to run training with different configurations
4. How to save trained model weight on google colab
5. How to do prediction on images
6. How to do predictions on videos
7. How to save images and videos on google drive

Special Thanks to:
Video sources:
Anastasia Shuraeva : https://www.pexels.com/video/womanpl...
Tima Miroshnichenko : https://pexels.com/video/peopleplayi...
Tom Fisk: https://pexels.com/video/asoccergam...


Recommended books:
1. HANDS ON MACHINE LEARNING WITH SCIKIT LEARN, KERAS & TENSORFLOW: https://amzn.to/3wkAqeG
2. Deep Learning with PyTorch: Build, train, and tune neural networks using Python tools: https://amzn.to/3QX5ivo

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#yolov8 #objectdetection #coderzero