Explore the world of Computer Vision and learn to master it using Python, OpenCV, TensorFlow, and others
About This Video
In Detail
The high-quality content of the …
Explore the world of Computer Vision and learn to master it using Python, OpenCV, TensorFlow, and others
About This Video
In Detail
The high-quality content of the Mastering Computer Vision from the Absolute Beginning Using Python course presents you with a great opportunity to learn and become an expert. You will learn the core concepts of the CV field. This course will also help you understand the digital imaging process and identify the key application areas of CV. The course is easy to understand, descriptive, comprehensive, practical with live coding, and rich with state-of-the-art and updated knowledge of this field.
Although this course is a compilation of all the basic concepts of CV, you are encouraged to step up and experience more than what you learn. Your understanding of every concept is tested at the end of each section. The homework assignments/tasks/activities/quizzes along with solutions will assess your learning. Several of these activities are focused on coding so that you are ready to run with implementations.
The two hands-on projects in the last section—Change Detection in CCTV Cameras (Real-Time) and Smart DVRs (Real-Time)—make up the most important learning element of this course. They will help you sharpen your practical skills. Successful completion of these two projects will help you enrich your portfolio and kick-start your career in the CV field.
By the end of the course, you will have a strong understanding of Computer Vision concepts and will be ready to apply them in your future projects.
Who this book is for
This course is useful for data scientists, machine learning experts, and learners who are absolute beginners and know nothing about Computer Vision, and for people who want to learn Computer Vision with real data along with its implementation in realistic projects.
Chapter 1 : Introduction to Course and Instructor
Introduction to the Course
Introduction to Instructor
About AI Sciences
Course Outline (Optional)
Computer Vision Applications
Final Project
Chapter 2 : Introduction to Images
Grayscale Image
Quiz (Grayscale Image)
Solution (Grayscale Image)
Grayscale Spectrum
Reading, Manipulating, and Saving Grayscale Image using Matplotlib Python
Quiz (Reading, Manipulating, and Saving Grayscale Image using Matplotlib Python)
Solution (Reading, Manipulating, and Saving Grayscale Image using Matplotlib Python)
Reading, Manipulating, and Saving Grayscale Image using OpenCV Python
Introduction to RGB Images
Quiz (Introduction to RGB Images)
Solution (Introduction to RGB Images)
RGB Color Images Matplotlib and OpenCV
Quiz (RGB Color Images Matplotlib and OpenCV)
Solution (RGB Color Images Matplotlib and OpenCV)
RGB to HSV theory and Algorithm
RGB to HSV Algorithm Implementation using Python
Quiz (RGB to HSV Algorithm Implementation using Python)
Solution (RGB to HSV Algorithm Implementation using Python)
Red Rose Extraction or Segmentation using HSV Python
Quiz (Red Rose Extraction or Segmentation using HSV Python)
Solution (Red Rose Extraction or Segmentation using HSV Python)
Hyper Spectral Images
Chapter 3 : 2D Scaling Transformations
Introduction to Geometric Transformations
Scaling Example in OpenCV
Quiz (Scaling Example in OpenCV)
Solution (Scaling Example in OpenCV)
Scaling in Real Space
Quiz (Scaling in Real Space)
Solution (Scaling in Real Space)
Linear Transformation Explained
Scaling is a Linear Transformation
Scaling as a Matrix Multiplication Example Python
Quiz (Scaling as a Matrix Multiplication Example Python)
Solution (Scaling as a Matrix Multiplication Example Python)
Image Coordinate System
Image Copy and Flipping Vertically
Quiz 01 (Image Copy and Flipping Vertically)
Solution 01 (Image Copy and Flipping Vertically)
Quiz 02 (Image Copy and Flipping Vertically)
Solution 02 (Image Copy and Flipping Vertically)
Continuous Coordinates
Saturations and Holes
Image Doubling and Holes using Python
Inverse Scaling and Quiz
Solution and Nearest Neighbor Interpolation
Inverse Scaling Python
Quiz 01 (Inverse Scaling Python)
Solution 01 (Inverse Scaling Python)
Quiz 02 (Inverse Scaling Python)
Solution 02 (Inverse Scaling Python)
Nearest Neighbor Interpolation
Weighted Average Versus Simple Average
Bilinear Interpolation
Bilinear Interpolation Implementation in Python
Scaling Transformation with Bilinear Interpolation Implementation
Scaling Transformation Algorithm(Recap)
Exam
Exam Solution 01
Exam Solution 02
Chapter 4 : 2D Geometric Transformations
Rotation Introduction
Optional Rotation is Linear Transform Proof
Rotation can Result Negative Coordinates (Problem)
Rotation Computing Width and Hight of Resultant Image(Solution)
Rotation Index Shifting
Quiz (Rotation Index Shifting)
Solution (Rotation Index Shifting)
Rotation Implementation Complete
Quiz (Rotation Implementation Complete)
Solution (Rotation Implementation Complete)
Rotation Implementation (Good Coding Practice)
Quiz: Rotation Implementation (Good Coding Practice)
Solution: Rotation Implementation (Good Coding Practice)
Reflection Introduction
Quiz (Reflection Introduction)
Solution (Reflection Introduction)
Reflection Implementation
Quiz 01 (Reflection Implementation)
Solution 01 (Reflection Implementation)
Quiz 02 (Reflection Implementation)
Solution 02 (Reflection Implementation)
Shear Introduction
Shear Implementation and Quiz
Translation and its Nonlinearity (Problem)
Homogeneous Coordinates
Translation as a Matrix (Solution)
Homogeneous Representations of All Transformations
Affine Transformation Implementation
Quiz (Affine Transformation Implementation)
Rotation about Any Point Theory
Rotation about Any Point Implementation
Reflection about a Line Quiz
Solution (Reflection about a Line)
Transformation Matrix Properties
Transformation Matrix Properties Implementation
Affine Transformation Hierarchy
Optional Affine Transformation SVD
Projective Transformation Homography
Projective Transformation Implementation
Projective Warping Algorithm
Chapter 5 : Geometric Transformation Estimation (Panorama)
Goal
Affine Transformation Estimation Introduction
Quiz (Affine Transformation Estimation Introduction)
Solution (Affine Transformation Estimation Introduction)
Affine Transformation Estimation Points Correspondences
Estimation Points Marking using Python and Quiz
Affine Transformation Min Number of Points Needed
Affine Transformation Estimation using Python
Affine Transformation Estimation Verification using Python
Affine Transformation Estimation with More Than Three Points
Quiz (Affine Transformation Estimation with More Than Three Points)
Solution (Affine Transformation Estimation with More Than Three Points)
Affine Transformation Estimation with More Than Three Points Implementation
Quiz (Affine Transformation Estimation with More Than Three Points Implementation)
Solution (Affine Transformation Estimation with More Than Three Points Implementation)
Optional Affine Transformation Estimation with LeastSquared
Projective Transformation Estimation Introduction
Projective Transformation Estimation First Implementation having Bug
Projective Transformation Estimation Reason of the Bug
Projective Transformation Estimation Removing Scale Factor
Projective Transformation Estimation DLT
Projective Transformation Estimation DLT Nullspace and Why Four Points
Projective Transformation Estimation DLT Nullspace Implementation
DLT Implementation
Quiz (DLT Implementation)
Panorama Stitching
Panorama Stitching Implementation in OpenCV
How Projective Transformation Helps in Panorama
Chapter 6 : Binary Morphology
Binary Images Theory
Binary Images Python
Structuring Element Kernel and Sliding Window Theory
Structuring Element Python
Erosion Theory
Quiz 01 (Erosion Theory)
Solution 01 (Erosion Theory)
Quiz 02 (Erosion Theory)
Solution 02 (Erosion Theory)
Erosion Python
Dilation Theory
Quiz 01 (Dilation Theory)
Solution 01 (Dilation Theory)
Quiz 02 (Dilation Theory)
Solution 02 (Dilation Theory)
Dilation Python
Opening Theory
Opening Python
Closing Theory
Closing Python
Gradient Morphology
Gradient Morphology Python
Top Hat and Black Hat
Chapter 7 : Image Filtering
Image Blurring 01
Image Blurring 02
General Image Filtering
Convolution
Naive Edge Detection
Image Sharpening
Quiz (Image Sharpening)
Solution (Image Sharpening)
Implementation of Image Blurring, Edge Detection, and Image Sharpening in Python
Low Pass, High Pass, and Band Pass Filters
Chapter 8 : Canny Edge Detector
Canny Edge Detector Algorithm Introduction
Canny Edge Detector OpenCV
Quiz (Canny Edge Detector OpenCV)
Solution (Canny Edge Detector OpenCV)
Gaussian Filter Introduction
Gaussian Filter to Mask Computation
Gaussian Filter Window Size
Gaussian Filter Implementation
Quiz (Gaussian Filter Implementation)
Solution (Gaussian Filter Implementation)
Gaussian Filter Smoothing Implementation
Quiz (Gaussian Filter Smoothing Implementation)
Solution (Gaussian Filter Smoothing Implementation)
Image Gradients Theory
Image Gradients Implementation
Image Gradients Implementation Datatype Bug
Derivative of Gaussian
Derivative of Gaussian Expression
Derivative of Gaussian Implementation
Applying DOG Filters
Gradient Vector
Gradient Magnitude and Gradient Direction
Non-Maxima Suppression
Gradient Direction Quantization
Quiz (Gradient Direction Quantization)
Solution (Gradient Direction Quantization)
Gradient Direction Quantization Implementation
Gradient Direction Quantization Implementation Better Way
NMS Implementation
Quiz 01 (NMS Implementation)
Solution 01 (NMS Implementation)
Quiz 02 (NMS Implementation)
Solution 02 (NMS Implementation)
Last Step Thresholding
Hysteresis Thresholding
Hysteresis Thresholding Implementation
Chapter 9 : Shape Detection
Shape Detection Introduction
Why Edge Detection is not Enough
RANSAC Introduction
RANSAC For Lines Coordinate Arrays
RANSAC for Lines Sampling Points Randomly Implementation
Quiz (RANSAC for Lines Sampling Points Randomly Implementation)
Solution (RANSAC for Lines Sampling Points Randomly Implementation)
RANSAC for Lines - Fitting Line with Two Points
RANSAC for Lines - Fitting Line with Two Points Implementation
Quiz (RANSAC for Lines Fitting Line with Two Points Implementation)
Solution (RANSAC for Lines Fitting Line with Two Points Implementation)
RANSAC for Lines Computing Consistency Score
RANSAC For Lines Computing Consistency Score Implementation
RANSAC for Lines Implementation
RANSAC for Lines Implementation Test on Real Image
Drawback
RANSAC for Lines Implementation Test on Real Image Drawing and Quiz
RANSAC for Circles
RANSAC for Circles Consistency Score
RANSAC for Circles Implementation
RANSAC for Circles Implementation Real Image
Drawback
RANSAC for Circles Implementation Real Image Drawing
RANSAC General
RANSAC Quiz
RANSAC Quiz Solution
Chapter 10 : Shape Detection Hough Transform
Hough Transform Introduction
Hough Transform as Voting
Hough Transform as Voting Loop
Hough Transform Polar Representation
Hough Transform Polar Representation Benefits
Hough Transform Polar Representation Implementation
Hough Transform Lines Implementation Real Image
Hough Transform Lines Parameters Conversion
Hough Transform Lines Drawing
Solution (Hough Transform Lines Drawing)
Hough Transform Fast Version
Hough Transform Circles
Hough Transform Circles Implementation
Hough Transform Circles Implementation Drawing
Solution (Hough Transform Circles Implementation Drawing)
Chapter 11 : Corner Detection
Corner Definition
Why Corner
Corner Measure
SSD
Why SSD to be Muted Somewhere
Corner Detection Implementation 01
Corner Detection Implementation 02
Corner Detection Implementation 03
Moravec Corner Detector
Scale Space
Infinite Directions Towards Harris Corner Detector
Harris Corner Detector 01
Harris Corner Detector 02
Harris Corner Detector 03
Harris Corner Detector 04 Structure Tensor
Harris Corner Detector 05 Final Expression
Harris Corner Detector Implementation Speedup Convolution
Harris Corner Detector Implementation 01
Harris Corner Detector Implementation 02
Harris Corner Detector as Edge Detector
Chapter 12 : Automatic Panorama SIFT
Point Correspondence Introduction
Point Drawing Implementation
Scale and Orientation Alignment
SIFT and HOG
Points Matching
Chapter 13 : Object Detection
Introduction to Object Detection
Classification Pipeline
Sliding Window Implementation
Shift Scale Rotation Invariance
Person Detection
HOG Features
Hand Engineering Versus CNNs
Implementation
Activity
Chapter 14 : YOLO Object Detector
CNNS Introduction
Face Detection Implementation
YOLO Implementation
YOLO Image Classification Revisited
YOLO Sliding Window Object Localization
YOLO Sliding Window Efficient Implementation
YOLO Introduction
YOLO Training Data Generation
YOLO Anchor Boxes
YOLO Algorithm
YOLO Non-Maxima Suppression
YOLO RCNN
Chapter 15 : Motion
Optical Flow
BC Assumption
Optical Flow Derivation
Chapter 16 : Object Tracking
Tracking by Detection
Tracking by Detection Motion Model Assumption
Tracking KLT TLD
Single Object Tracking
Multiple Object Tracking
WebCam and Saving Annotations of Multiple Object Tracking
Chapter 17 : 3D Reconstruction
3d Reconstruction Introduction
3d Motion Capture
Camera
Camera Matrix
Triangulation
Camera Matrix Estimation
Mocap Revisited
Chapter 18 : Smart CCTV Project
Introduction to the Project
Introduction to Data
Reading a Video File
Change Detection Frame Differencing
Change Detection Frame Differencing Implementation
Change Detection Background Subtraction
Change Detection Background Subtraction MOG
Denoising using Morphology
Connected Components
Connected Components Filtering
Tracking Change
Saving Segments
Saving and Viewing Segments
Saving and Viewing Segments with Object Detection
Applications