Modern Computer Vision with PyTorch, Second Edition

Modern Computer Vision with PyTorch, 2nd Edition

eBook Details:

  • Paperback: 746 pages
  • Publisher: WOW! eBook; 2nd edition (June 10, 2024)
  • Language: English
  • ISBN-10: 1803231335
  • ISBN-13: 978-1803231334

eBook Description:

Modern Computer Vision with PyTorch, Second Edition: A practical roadmap from deep learning fundamentals to advanced applications and Generative AI. The definitive computer vision book is back, featuring the latest neural network architectures and an exploration of foundation and diffusion models.

Whether you are a beginner or are looking to progress in your computer vision career, this Modern Computer Vision with PyTorch, 2nd Edition book guides you through the fundamentals of neural networks (NNs) and PyTorch and how to implement state-of-the-art architectures for real-world tasks.

The Modern Computer Vision with PyTorch, Second Edition is fully updated to explain and provide practical examples of the latest multimodal models, CLIP, and Stable Diffusion.

You’ll discover best practices for working with images, tweaking hyperparameters, and moving models into production. As you progress, you’ll implement various use cases for facial keypoint recognition, multi-object detection, segmentation, and human pose detection. This book provides a solid foundation in image generation as you explore different GAN architectures. You’ll leverage transformer-based architectures like ViT, TrOCR, BLIP2, and LayoutLM to perform various real-world tasks and build a diffusion model from scratch. Additionally, you’ll utilize foundation models’ capabilities to perform zero-shot object detection and image segmentation. Finally, you’ll learn best practices for deploying a model to production.

  • Get to grips with various transformer-based architectures for computer vision, CLIP, Segment-Anything, and Stable Diffusion, and test their applications, such as in-painting and pose transfer
  • Combine CV with NLP to perform OCR, key-value extraction from document images, visual question-answering, and generative AI tasks
  • Implement multi-object detection and segmentation
  • Leverage foundation models to perform object detection and segmentation without any training data points
  • Learn best practices for moving a model to production

By the end of this Modern Computer Vision with PyTorch, 2nd Edition deep learning book, you’ll confidently leverage modern NN architectures to solve real-world computer vision problems.

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