Chapter 1: Installation and Environment Setup
Chapter Goal: Making System Ready for Image Processing and Analysis
No of pages 20
Sub -Topics (Top 2)
1. Installing Jupyter Notebook
2. Installing OpenCV and other Image Analysis dependencies
3. Installing Neural Network Dependencies...
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Chapter 1: Installation and Environment Setup
Chapter Goal: Making System Ready for Image Processing and Analysis
No of pages 20
Sub -Topics (Top 2)
1. Installing Jupyter Notebook
2. Installing OpenCV and other Image Analysis dependencies
3. Installing Neural Network Dependencies
Chapter 2: Introduction to Image Processing
Chapter Goal: Introduction to different concepts of Image Processing
No of pages: 50
Sub - Topics (Top 2)
1. Terminologies related to Image Analysis
2. Flowchart of Image Processing
Chapter 3: Python Operations
Chapter Goal: Introduction to Python as a Programming Language
No of pages: 50
Sub - Topics (Top 2):
1. Essentials of Python
2. Advanced Python
Chapter 4: Image Processing and Analysis Algorithms
Chapter Goal: Understanding Algorithms and their applications in Python
No of pages: 100
Sub - Topics (Top 2):
1. Operations on Images
2. Image Segmentation
Chapter 5: OpenCV - An Introduction
Chapter Goal: Exploring the famous computer vision Library OpenCV, and understanding its essential elements
No of pages: 100
Sub - Topics (Top 2):
1. Exploring OpenCV Algorithms
2. Applications on Images using Python
Chapter 6: Machine Learning & Image Processing
Chapter Goal: Applying Machine Learning Models on Processed Images.
No of pages: 100
Sub - Topics (Top 2):
1. Applying Supervised and Unsupervised Learning approaches on Images using Python
2. Applying Advanced Artificial Neural Networks on Images
Chapter 7: Real Time Use Cases
Chapter Goal: Working on 5 projects using Python, applying all the concepts learned in this book
No of pages: 100
Sub - Topics (Top 2):
Facial Recognition and Detection
Self-Driving Cars Conceptualization
Hand Gesture Movement Recognition
Attendance Management
Retail Stacks Management
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