Neural network computer vision with OpenCV 5 : build computer vision solutions using Python and DNN module / Gopi Krishna Nuti

Includes index.

Intro -- Cover Page -- Title Page -- Copyright Page -- Dedication -- About the Author -- About the Reviewer -- Acknowledgement -- Preface -- Table of Contents -- 1. Introduction to Computer Vision -- Introduction -- Structure -- Objectives -- History of computer imaging -- Retrieving information from images -- Image processing -- Representation -- Manipulation -- Flexibility -- Reproducibility -- Digital image processing -- Conclusion -- Exercises -- 2. Basics of Imaging -- Introduction -- Structure -- Objectives -- Pixels and image representation -- Pixels -- Color spaces -- Primary colors

Additive colors -- Subtractive colors -- Grayscale -- Other color spaces -- Pixels and color spaces -- Examples -- Image filetypes -- Video files -- Images and videos -- Programming for image data -- A brief history of computer image programming -- OpenCV: History and overview -- Image processing code samples -- Opening, viewing and closing image files -- CPP code -- Python code -- Videos and frames -- Programming with color spaces -- Grayscale -- RGB image -- Conclusion -- Exercises -- 3. Challenges in Computer Vision -- Introduction -- Structure -- Objectives -- Topics in computer vision

Complexity in image processing -- Image classification -- Object localization -- Image segmentation -- Character recognition -- Conclusion -- Exercises -- Key terms -- 4. Classical Solutions -- Introduction -- Structure -- Objectives -- Solutions for challenges in computer vision -- Classical solutions -- Modern solutions -- Algorithm families -- Morphological operations -- Erosion and dilation of images -- Closing and opening images -- Thresholding -- Detecting edges and corners -- Image transformations -- Region growing -- Clustering -- Template matching -- Watershed algorithm

Foreground and background detection -- Superpixels -- Image pyramids -- Convolution -- Conclusion -- Exercises -- Key terms -- 5. Deep Learning and CNNs -- Introduction -- Structure -- Objectives -- History of deep learning -- Perceptron -- Shallow learning networks -- Deep learning networks -- Weights, biases, and activation functions -- Weight -- Bias -- Activation function -- Optimization function -- Convolutional neural networks -- CNNs versus fully connected networks -- Deep learning process -- Training -- Techniques in training -- Inference process -- Techniques/tricks in inference

Conclusion -- Key terms -- Exercises -- 6. OpenCV DNN Module -- Introduction -- Structure -- Objectives -- Deep learning frameworks -- TensorFlow -- PyTorch -- Keras -- Inference for computer vision -- Local inferencing -- Local CPUs -- Local GPUs -- Cloud -- Edge computing -- OpenCV DNN module -- History -- Features and limitations -- Capabilities -- Limitations -- Considerations -- Supported layers -- Unsupported layers and operations -- Important classes -- Conclusion -- Exercises -- 7. Modern Solutions for Image Classification -- Introduction -- Structure -- Objectives

Neural Network Computer Vision with OpenCV equips you with professional skills and knowledge to build intelligent vision systems using OpenCV. It creates a sequential pathway for understanding morphological operations, edge and corner detection, object localization, image classification, segmentation, and advanced applications like face detection and recognition, and optical character recognition.