This video explains the process of training a traditional machine learning algorithm (Random Forest) for image segmentation. The process includes feature generation using Gabor, canny, roberts, scharr, gaussian, median and other digital image filters.
Code associated with these tutorials can be downloaded from here: https://github.com/bnsreenu/python_for_image_processing_APEER
The dataset used in this video can be downloaded from the link below. This dataset can be used to train and test machine learning algorithms designed for multiclass semantic segmentation. Please read the Readme document for more information.
https://drive.google.com/file/d/1HWtBaSa-LTyAMgf2uaz1T9o1sTWDBajU/view?usp=sharing
