OpenCV 4 with Python Blueprints - Second Edition

Summary

In this chapter, we trained a multiclass classifier to recognize traffic signs from the GTSRB database. We discussed the basics of supervised learning, explored the intricacies of feature extraction, and sneaked a peek into DNNs.

Using the approach we took in this chapter, you should be able to formulate real-life problems as machine learning models, use your Python skills to download a sample labeled dataset from the internet, write your featurizing functions that convert images to feature vectors, and use OpenCV for training off-the-shelf machine learning models that help you solve your real-life problems.

Notably, we left out some details along the way, such as attempting to fine-tune the hyperparameters of the learning algorithm ...