OpenCV Tutorial | Computer Vision | Full OpenCV with Python Course
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Why watch?
• Project-based learning: Cartoonifier, Face Blur, Gesture Control & more
• Covers essential concepts: image filters, edge detect, contours, webcam/video I/O, object & face detection, color tracking
• Perfect for students, freshers, job seekers, and IT professionals
Course Syllabus:
00:04:31 – Phase 0: Getting Ready for OpenCV
Introduction to OpenCV, Importance of Computer Vision, Where OpenCV is Used, Key Features of OpenCV, Prerequisites & Tools Setup
00:31:25 – Phase 1: Getting Started with OpenCV
Installing OpenCV (cv2), Reading & displaying images, Saving images, Image dimensions & channels, Grayscale conversion
01:06:06 – Phase 2: Image Transformations & Manipulation
Resizing & scaling images, Cropping using slicing, Rotating and flipping images, Drawing shapes (lines, circles), Adding text on images
01:44:17 – Phase 3: Basic Image Drawing Techniques
Drawing lines, rectangles, circles, Adding custom text on images, Creating basic graphic overlays
02:14:42 – Phase 4: Working with Video & Webcam
Capturing video from webcam (cv2.VideoCapture), Frame-by-frame processing, Real-time filters, Saving video (cv2.VideoWriter)
02:51:28 – Phase 5: Image Filtering & Blurring
Gaussian blur, Median blur, Sharpening filters, Smoothing noisy images, Enhancing image clarity
03:23:18 – Phase 6: Edge Detection & Thresholding
Canny edge detection, Binary & adaptive thresholding, Bitwise operations (AND, OR, NOT), Extracting outlines from images
03:47:36 – Phase 7: Contours & Shape Detection
Finding contours, Drawing contours on images, Shape detection using approxPolyDP, Object recognition basics
04:22:52 – Phase 8: Face & Object Detection
Using Haar Cascades, Face detection, Eye & smile detection, Pre-trained classifiers, Drawing boxes on detected faces
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