Clik here to view.
PyTorch object detection with pre-trained networks
In this tutorial, you will learn how to perform object detection with pre-trained networks using PyTorch. Utilizing pre-trained object detection networks, you can detect and recognize 90 common...
View ArticleClik here to view.
What is Optical Character Recognition (OCR)?
Optical character recognition, or OCR for short, is used to describe algorithms and techniques (both electronic and mechanical) to convert images of text to machine-encoded text. We typically think of...
View ArticleClik here to view.
Installing Tesseract, PyTesseract, and Python OCR packages on your system
In this tutorial, we will configure our development environment for OCR. Once your machine is configured, we’ll start writing Python code to perform OCR, paving the way for you to develop your own OCR...
View ArticleClik here to view.
Your First OCR Project with Tesseract and Python
The first time I ever used the Tesseract optical character recognition (OCR) engine was in my college undergraduate years. I was taking my first course on computer vision. Our professor wanted us to...
View ArticleClik here to view.
Detecting and OCR’ing Digits with Tesseract and Python
In a previous tutorial, we implemented our very first OCR project. We saw that Tesseract worked well on some images but returned total nonsense for other examples. Part of being a successful OCR...
View ArticleClik here to view.
Whitelisting and Blacklisting Characters with Tesseract and Python
In our previous tutorial, you learned how to OCR only digits from an input image. But what if you wanted to obtain more fine-grained control on the character filtering process? For example, when...
View ArticleClik here to view.
Language Translation and OCR with Tesseract and Python
Given that we can detect the writing system of the text, it raises the question: Is it possible to translate text from one language to another using OCR and Tesseract? To learn how to translate...
View ArticleClik here to view.
An interview with Raul Garcia-Martin, PhD candidate and computer vision...
In this blog post, I sit down with Raul Garcia-Martin, a PhD candidate in Biometric Recognition at the University Carlos III of Madrid. Raul’s work focuses on identifying individual people by their...
View ArticleClik here to view.
PyTorch: Transfer Learning and Image Classification
In this tutorial, you will learn how to perform transfer learning for image classification using the PyTorch deep learning library. This tutorial is part 2 in our 3-part series on intermediate PyTorch...
View ArticleClik here to view.
An interview with David Bonn, computer vision and wildfire detection expert
Imagine this: You’ve built a brand new home out in the country, far from major cities. You need a break from all the hustle and bustle, and you want to bring yourself back to nature. The house you’ve...
View ArticleClik here to view.
Using Machine Learning to Denoise Images for Better OCR Accuracy
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...
View ArticleClik here to view.
Automatically OCR’ing Receipts and Scans
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:...
View ArticleClik here to view.
OCR’ing Business Cards
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...
View ArticleClik here to view.
Tesseract Page Segmentation Modes (PSMs) Explained: How to Improve Your OCR...
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...
View ArticleClik here to view.
Improving OCR Results with Basic Image Processing
In our previous tutorial, you learned how to improve the accuracy of Tesseract OCR by supplying the appropriate page segmentation mode (PSM). The PSM allows you to select a segmentation method...
View ArticleClik here to view.
An interview with Adithya Gaurav Singh: Finding love with computer vision and...
Not many people know this about me, but my wife and I met online when she was 18, and I was 20. It wasn’t a dating website/app like Match, eHarmony, Tinder, etc. … instead, it was Last.fm, a website...
View ArticleClik here to view.
Using spellchecking to improve Tesseract OCR accuracy
In a previous tutorial, you learned how to use the textblob library and Tesseract to automatically OCR text and then translate it to a different language. This tutorial will also use textblob, but...
View ArticleClik here to view.
OCR Passports with OpenCV and Tesseract
This lesson is part 4 of a 4-part series on OCR 120: Tesseract Page Segmentation Modes (PSMs) Explained: How to Improve Your OCR Accuracy (tutorial 2 weeks ago)Improving OCR Results with Basic Image...
View ArticleClik here to view.
Correcting Text Orientation with Tesseract and Python
An essential component of any OCR system is image preprocessing — the higher the quality input image you present to the OCR engine, the better your OCR output will be. To be successful in OCR, you...
View ArticleClik here to view.
Using Machine Learning to Denoise Images for Better OCR Accuracy
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...
View Article