Computer Vision with Python: Build Practical Image Recognition, Object Detection, and Video Analysis Systems for Real-World AI Applications

Computer Vision with Python: Build Practical Image Recognition, Object Detection, and Video Analysis Systems for Real-World AI Applications book cover

Computer Vision with Python: Build Practical Image Recognition, Object Detection, and Video Analysis Systems for Real-World AI Applications

Author(s): Henry V. Primeaux (Author)

  • Publisher: Independently published
  • Publication Date: 21 May 2026
  • Language: English
  • Print length: 193 pages
  • ISBN-10: B0H2L9RRNP
  • ISBN-13: 9798198011748

Book Description

Computer Vision with Python: Build Practical Image Recognition, Object Detection, and Video Analysis Systems for Real-World AI Applications

Build computer vision systems that move beyond tutorials and start solving real AI problems.

Are you tired of computer vision guides that explain theory but leave you unsure how to build working image recognition, object detection, and video analysis pipelines? Do you want practical Python skills you can apply to real-world AI projects, automation workflows, industrial inspection, edge deployment, and intelligent visual systems?

Computer Vision with Python gives you a clear, hands-on path to building practical vision applications from the ground up. You’ll learn how to process images with OpenCV, build custom PyTorch classification models, train object detection systems with YOLO, analyze video streams, track objects, evaluate model performance, and optimize models for deployment.

This book stands out by focusing on practical engineering workflows instead of abstract explanations. Each chapter guides you through real implementation patterns, including image ingestion, feature extraction, transfer learning, Vision Transformers, foundation vision models, real-time tracking, action recognition, ONNX export, quantization, and edge-ready optimization.

Inside, you’ll gain confidence with:

  • Image recognition and classification with Python and PyTorch
  • Object detection using YOLO and bounding-box pipelines
  • Real-time video analysis, tracking, and event recognition
  • OpenCV image processing for practical automation tasks
  • Model evaluation with confusion matrices, IoU, mAP, and validation metrics
  • Deployment-focused optimization, export, pruning, and quantization

This book is for Python developers, AI engineers, machine learning learners, software engineers, and technical professionals who want to build useful computer vision systems for real-world applications.

If you’re ready to turn Python, OpenCV, PyTorch, and modern AI models into practical visual intelligence systems, get your copy today and start building with confidence.

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