- 0-Introduction to Machine Vision. Based on the Lecture 1 from CS231n: Convolutional Neural Networks for Visual Recognition, we briefly introduce machine vision as it developed from several researches in animal vision to mechanical vision to neuroscience.
- 1-Introduction to Python Programming [notebook]. A brief introduction to Python programming.
- 2-Introduction to NumPy [notebook]. A brief introduction to NumPy based on Justin Johnson's notes in CS231n.
- 3-Introduction to OpenCV. A brief introduction to OpenCV-Python.
- 4-Image Loading and Saving [notebook]. A tutorial on loading, displaying, and saving an image.
- 5-Core Operations [notebook]. A tutorial on core operations in OpenCV, which includes accessing and modifying pixels, image channels, and image arithmetic.
- 6-Machine Learning for Image Classification [notebook] . A brief introduction on machine learning using kNN and Linear SVM for image classification.
- 7-Preprocessing using Mean Normalization and PCA [notebook]. A tutorial on mean normalization and principal component analysis as preprocessing techniques for machine learning.
- 8-Real-time Image Classification using TensorFlow and OpenCV [notebook]. Using MobileNet architecture written in TensorFlow for OpenCV as real-time classifier.
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