 
								? 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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