This repository contains basic knowledge required to implement computer vision problems in Tensorflow 2. It covers many of the basic fundamental things one has to know while getting acquainted with CV problems using tensorflow. This repo will be beneficial for research purpose as it will help to teach the following:
- how to build neural networks as well as how to use pretrained models
- how to deal with datasets and their labels
- how to use different techniques to do the image preprocessing as required
- how to implement custom filters and edge detectors from scratch according to our need
- how to visualize the extracted features from the neural net to get a better understanding of the model so that optimization can be done