Neural Network Computer Vision with OpenCV 5 Build computer vision solutions using Python and DNN module

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Free Download Neural Network Computer Vision with OpenCV 5: Build computer vision solutions using Python and DNN module (English Edition) by Gopi Krishna Nuti
English | December 30, 2023 | ISBN: 9355516967 | 266 pages | MOBI | 12 Mb
Unlocking computer vision with Python and OpenCV

Key Features
● Practical solutions to image processing challenges.
● Detect and classify objects in images.
● Recognize faces and text from images using character detection and recognition models.
Description
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.
This book offers a practical roadmap to explore the nuances of image processing with detailed discussions on each topic, supported by hands-on Python code examples. The readers will learn the basics of neural networks, deep learning and CNNs by using deep learning frameworks like Keras, Tensorflow, PyTorch, Caffe etc. They will be able to utilize OpenCV DNN module to classify images by using models like Inception V3, Resnet 101, Mobilenet V2. Moreover, the book will help to successfully Implement object detection using YOLOv3, SSD and R-CNN models. The character detection and recognition models are also covered in depth with code examples.
You will gain a deeper understanding of how these techniques impact real-world scenarios and learn to harness the potential of Python and OpenCV to solve complex problems. Whether you are building intelligent systems, automating processes, or working on image-related projects, this book equips you with the skills to revolutionize your approach to visual data.
What you will learn
● Acquire expertise in image manipulation techniques.
● Apply knowledge to practical scenarios in computer vision.
● Implement robust systems for face detection and recognition.
● Enhance projects with accurate object localization capabilities.
● Extract text information from images effectively.
Who this book is for
This book is designed for those with basic Python skills, from beginners to intermediate-level readers. Whether you are building intelligent robots that perceive their surroundings or crafting advanced vision systems for object detection and image analysis, this book will equip you with the tools and skills to push the boundaries of AI perception.
Table of Contents
1. Introduction to Computer Vision
2. Basics of Imaging
3. Challenges in Computer Vision
4. Classical Solutions
5. Deep Learning and CNNs
6. OpenCV DNN Module
7. Modern Solutions for Image Classification
8. Modern Solutions for Object Detection
9. Faces and Text
10. Running the Code
11. End-to-end Demo

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Computer Vision with OpenCV and Python
Duration: 3h 2m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 1.33 GB
Genre: eLearning | Language: English​

Learn via hands-on projects the basics of computer vision and image processing

What you'll learn:
The basic concepts of computer vision and image processing
The basic functions of OpenCV such as loading, resizing, thresholding, blurring, and many more
Build a document scanner project
Build a bubble sheet multiple choice test project
Build a barcode and QR code scanner project
Build a face detection and blurring project
Build an object detection project

Requirements:
To take this course, you need basic familiarity with Python. No prior knowledge of OpenCV is required.

Description:
Computer Vision with OpenCV and Python is an overarching tutorial for beginners and intermediate Python programmers that teaches the basics of computer vision using Python and OpenCV.
You will learn the basic concepts of computer vision and image processing by following a hands-on approach. You will then use these concepts to build real-world projects such as face detection, object detection, barcode and QR scanner, and more.
If you are interested in computer vision and image processing but don't know where to start, this course is for you.
By the end of this course, you'll be comfortable with the OpenCV library and will be able to successfully apply image processing techniques to your projects.
We will be using the Python programming language since it is one of the most widely used and easiest languages to learn.
What you'll get:
When you buy the course you'll receive:
3+ hours of HD video tutorials
Text version of the course divided into 16 parts (coming soon)
Source code, example images, and videos used in the course
Lifetime access to the course
Priority support
What is covered in this course:
Just so that you have some idea of what you will learn in these tutorials, these are the topics that we will cover:
Read and write images and videos
Crop and resize images
Translate and rotate images
Image annotation, including drawing lines, circles, rectangles, text, etc
Bitwise operations and image masking
Barcode and QR code scanner in images and videos
Image filtering and blurring
Image thresholding
Morphological operations: Erosion/Dilation and Opening/Closing
Edge and contour detection
Document scanner
Bubble sheet multiple-choice test
Face detection (using Haar cascade) and blurring in images and videos
Object detection with deep learning in Images and videos

Who this course is for:
Python programmers who want a hands-on introduction to computer vision with OpenCV
Anyone familiar with OpenCV who needs a refresher course to fill in the gaps
Python developers who want to get started with computer vision and OpenCV
Students who want to better understand OpenCV

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