Tutorials

Most introductions to Tesseract tutorials will provide you with instructions to install and configure Tesseract on your machine, provide one or two examples of how to use the tesseract binary, and then perhaps how to integrate Tesseract with Python using…

In this tutorial, we are implementing a Deep Convolutional GAN (DCGAN) with TensorFlow 2 / Keras, based on the paper, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (Radford et al., 2016). This was one of the earliest GAN…

Table of Contents Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 1 World Coordinate Frame Camera Coordinate Frame Coordinate Transformation Projective Transformation Dataset Summary Citation Information A few days back, while going through my photo gallery,…

In today’s tutorial, we will be looking at image segmentation and building our own segmentation model from scratch, based on the popular U-Net architecture. This lesson is the last of a 3-part series on Advanced PyTorch Techniques: Training a DCGAN…

In a previous tutorial, we learned how to automatically OCR and scan receipts by: Detecting the receipt in the input image Applying a perspective transform to obtain a top-down view of the receipt Utilizing Tesseract to OCR the text on…

In this tutorial, you will learn how to train a custom object detector from scratch using PyTorch. This lesson is part 2 of a 3-part series on advanced PyTorch techniques: Training a DCGAN in PyTorch (last week’s tutorial) Training an…

In this tutorial, you will learn how to use Tesseract and OpenCV to build an automatic receipt scanner. We’ll use OpenCV to build the actual image processing component of the system, including: Detecting the receipt in the image Finding the…

In this tutorial, we will learn how to train our first DCGAN Model using PyTorch to generate images. This lesson is part 1 of a 3-part series on Advanced PyTorch Techniques: Training a DCGAN in PyTorch (today’s tutorial) Training an…

One of the most challenging aspects of applying optical character recognition (OCR) isn’t the OCR itself. Instead, it’s the process of pre-processing, denoising, and cleaning up images such that they can be OCR’d. To learn how to denoise your images…