OpenCV with Python in 4 Hours

Notes and code used in my Python and OpenCV course

Course Outline (with timestamps)

1. Installing the necessary packages

Besides installing OpenCV, we cover the installation of the following packages:

caer is a powerful utilities package with tons of useful helper functions for most Computer Vision tasks

$ pip install caer

canaro is a Python package solely for Deep Learning models built in Keras

$ pip install canaro

2. Basic Concepts:

• Reading Images and Video (0:04:12)
• Resizing and Rescaling Images and Video Frames (0:12:57)
• Drawing Shapes and Placing text on images (0:15:52)
• 5 Essential Methods in OpenCV (0:27:27)
• Image Transformations (0:39:45)
• Contour Detection (0:52:38)

3. Advanced Concepts:

• Switching between Colour Spaces (RGB, BGR, Grayscale, HSV and Lab) (1:08:25)
• Splitting and Merging Colour Channels (1:18:41)
• Blurring (1:26:35)
• BITWISE operations (1:40:00)
• Masking (1:48:38)
• Histogram Computation (1:57:14)
• Thresholding/Binarizing Images (2:10:54)
• Advanced Edge Detection (2:21:59)

4. Face Detection and Recognition

• Face Detection using Haar Cascades (2:30:57)
• Face Recognition using OpenCV's LBPHFaceRecognizer algorithm (2:44:37)

5. Capstone: Deep Computer Vision

• Building a Deep Computer Vision model to classify between the characters in the popular TV series The Simpsons (3:07:28)

Credits

The images in the Photos and Videos folders were downloaded from Unsplash and Pixabay, unless otherwise mentioned. The images in the Faces folder were procurred from a repo on Kaggle.