Computer Vision with OpenCV
artificial-intelligence-ai.
🎓 Course Modules:
📦 Module 1: Introduction to Computer Vision
What is Computer Vision?
Applications in real life (self-driving, AR, surveillance)
Role of OpenCV and why it matters
🖼️ Module 2: Image Basics & Operations
Reading, displaying, and saving images
Image resizing, cropping, and channels
Color spaces: RGB, HSV, Grayscale
🔧 Module 3: Image Processing Fundamentals
Thresholding and masking
Filtering and blurring
Edge detection (Sobel, Canny)
📐 Module 4: Geometric Transformations
Image rotation, translation, and scaling
Affine and perspective transformations
Warping and stitching basics
📊 Module 5: Drawing & Annotation Tools
Drawing lines, shapes, and text on images
Creating custom annotation tools
Overlaying graphics on video streams
🧠 Module 6: Contours and Shape Detection
Finding contours
Shape approximation and matching
Bounding boxes and convex hulls
🧍 Module 7: Object Detection Basics
Template matching
Background subtraction
Motion detection in video feeds
😊 Module 8: Facial & Feature Detection
Haar cascades and face detection
Eye, smile, and body part detection
Live webcam tracking
🎥 Module 9: Working with Video
Reading and writing video files
Real-time video capture and processing
Frame-by-frame analysis
🤖 Module 10: Integrating OpenCV with AI Models
Using pretrained deep learning models
Object detection with YOLO/SSD using OpenCV DNN
Face recognition with embeddings
✅ Module 11: Capstone Project
Choose from object tracking, facial attendance system, or motion alert system
Full pipeline development and submission
Evaluation and feedback
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