Code Examples and Tutorials
Last updated September 4, 2024
The Ultralytics library provides a wealth of code examples and tutorials that guide developers through various aspects of object detection, segmentation, and classification using YOLOv8. This article highlights key resources that help you quickly grasp the library's functionality and implement YOLOv8 in your projects.
Core Functionality Examples
- Training a YOLOv8 Model: Explore examples that demonstrate how to train a YOLOv8 model for object detection, segmentation, or classification using custom datasets.
- Performing Inference: Learn how to load a trained YOLOv8 model and perform inference on input images or videos, extracting detection results and visualizing them.
- Dataset Management: Find examples showcasing dataset preparation, annotation, and loading using the `Datasets` class.
- Using Pre-trained Models: Discover examples that demonstrate loading and utilizing pre-trained YOLOv8 models from the Ultralytics Hub for immediate inference.
- Model Customization: Explore examples that show how to modify model architectures, training hyperparameters, and inference settings to fine-tune YOLOv8 for specific applications.
Practical Tutorials
- Object Detection: Follow tutorials that guide you through the complete process of training and deploying a YOLOv8 model for object detection, covering dataset preparation, model selection, training, evaluation, and inference.
- Image Segmentation: Discover tutorials that demonstrate how to use YOLOv8 for image segmentation, covering dataset annotation, model training, segmentation mask extraction, and visualization.
- Object Classification: Explore tutorials showcasing the use of YOLOv8 for object classification, from dataset preparation and model training to object classification and visualization.
- Web Applications: Find tutorials that guide you through integrating a trained YOLOv8 model into web applications using frameworks like Flask or Django, enabling real-time object detection in web interfaces.
- Mobile Applications: Discover tutorials on deploying YOLOv8 models on mobile devices using frameworks like TensorFlow Lite or CoreML, enabling object detection functionality in mobile apps.
Resources and Support
- Ultralytics Documentation: Consult the comprehensive documentation on the Ultralytics website, providing detailed explanations of the library's functions, classes, and methods.
- GitHub Repository: Explore the Ultralytics GitHub repository, containing the library's source code, example scripts, and community contributions.
- Ultralytics Forum: Engage with the Ultralytics community forum to ask questions, share experiences, and seek assistance from other users and developers.
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