Python for Computer Vision Online Course

Python for Computer Vision Online Course

The Mastering Computer Vision from the Absolute Beginning Using Python course provides a comprehensive, hands-on introduction to the field of Computer Vision (CV). You’ll explore core CV concepts, the digital imaging process, and real-world applications while learning through live coding, quizzes, and practical activities. Each section reinforces understanding with exercises and coding-based assignments. The course culminates in two real-time projects—Change Detection in CCTV Cameras and Smart DVRs—that sharpen your practical skills and enhance your portfolio. By the end, you’ll have a solid foundation in Computer Vision and be ready to apply your knowledge to real-world projects and career opportunities.

Who should take this Course?

The Python for Computer Vision Online Course is designed for data scientists, AI/ML enthusiasts, software developers, and researchers who want to gain hands-on skills in image processing and computer vision techniques using Python. It is also ideal for students, beginners in AI, and professionals from fields like robotics, healthcare, and automation who are looking to apply computer vision to real-world projects and innovations.

What you will learn

• Learn the concept of colored and black and white images with practice
• Know the theory and implementation of panoramic images
• Learn image filtering with implementation in Python
• Implement any project from scratch that requires Computer Vision knowledge
• Apply edge detection, shape detection, and corner detection
• Develop a project to make a very intelligent and efficient DVR using Python

Course Outline 

Introduction to Course and Instructor

• Introduction to the Course
• Introduction to Instructor
• About AI Sciences
• Course Outline (Optional)
• Computer Vision Applications
• Final Project

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

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

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

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

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

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

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

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

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)

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

Automatic Panorama SIFT

• Point Correspondence Introduction
• Point Drawing Implementation
• Scale and Orientation Alignment
• SIFT and HOG
• Points Matching

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

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

Motion

• Optical Flow
• BC Assumption
• Optical Flow Derivation

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

3D Reconstruction

• 3d Reconstruction Introduction
• 3d Motion Capture
• Camera
• Camera Matrix
• Triangulation
• Camera Matrix Estimation
• Mocap Revisited

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