How to Train Ultralytics YOLOv8 models on Your Custom Dataset in Google Colab | Episode 3

Ultralytics July 26, 2023
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Welcome to the official Ultralytics YouTube channel! 🚀 Dive into the cutting-edge world of computer vision and AI with Ultralytics, the creators of YOLO (You Only Look Once), the world's most popular object detection model. Our channel is your go-to resource for all things YOLO, from YOLOv5 to YOLO11 and beyond. 🔬 What you'll find here: - In-depth tutorials on YOLO implementation and optimization - Interviews with AI experts and industry leaders - Tips and tricks for machine learning and deep learning - Insights into emerging trends in computer vision and AI 🌟 Subscribe now to stay at the forefront of AI innovation. Don't miss our weekly uploads featuring the latest in object detection, image segmentation, and pose estimation technologies. Connect with us: 🏠 Website: https://ultralytics.com 💼 GitHub: https://github.com/ultralytics 🚀 Ultralytics HUB: https://ultralytics.com/hub 📚 Documentation: https://docs.ultralytics.com #Ultralytics #YOLO #ComputerVision #AI

Video Description

Learn how to train Ultralytics YOLOv8 models on your custom dataset using Google Colab in this comprehensive tutorial! 🚀 Join Nicolai as he walks you through every step needed to harness the power of YOLOv8 for real-time object detection. From setting up your environment and labeling your dataset to importing and training the model in Google Colab, this video covers it all. In this episode, you will: 1. Set Up Environment: Learn how to configure Google Colab for optimal performance by selecting a GPU and installing Ultralytics with `pip install ultralytics`. 2. Label Your Dataset: Use tools like Roboflow to label and export your dataset in the YOLOv8 format. 3. Import and Train: Import your dataset into Google Colab, set paths correctly, and start training your YOLOv8 model. Choose the model variant (e.g., YOLOv8m), set the number of epochs, and monitor training metrics like mean Average Precision (mAP). 4. Evaluate and Validate: Download the model weights, plot the confusion matrix, and validate the model on unseen images to ensure high performance. 🔗 Colab Notebook: https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb 🌟YOLO Vision 2024 (YV24), our annual hybrid Vision AI event is just days away! Happening on 27th September 2024 at Google for Startups Campus, Madrid.! Watch live on: 🔗 YouTube: https://youtu.be/XKAcQd4NfG8 🔗 Bilibili: https://live.bilibili.com/1921503038 For more details on training custom datasets with YOLOv8 in Google Colab, check out the blog: https://www.ultralytics.com/blog/training-custom-datasets-with-ultralytics-yolov8-in-google-colab Don't miss out on enhancing your AI skills with YOLOv8! Like, subscribe, and visit the following Ultralytics resources for more information: - 🏠 Ultralytics Home: https://www.ultralytics.com - 📚 Ultralytics YOLO: https://www.ultralytics.com/yolo - 🚀 Ultralytics HUB: https://www.ultralytics.com/hub #YOLOv8 #Ultralytics #ObjectDetection #ComputerVision #AI #MachineLearning Chapters: 0:00 📌 Introduction 1:20 🖥️ Setting Up Environment 3:45 🏷️ Labeling Dataset 7:10 📂 Importing Dataset 10:30 🚀 Training Model 15:00 📊 Evaluating Results

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