cardminder unable to perform recognition

#Cardminder unable to perform recognition how to#

If you need help configuring your development environment for OpenCV, I highly recommend that you read my pip install OpenCV guide - it will have you up and running in a matter of minutes. Luckily, OpenCV is pip-installable: $ pip install opencv-contrib-python

To follow this guide, you need to have the OpenCV library installed on your system. Let’s dive in! Configuring your development environment Finally, we’ll learn where you can brush up on your computer vision skills so that you can make effective image processing pipelines, like the one in this tutorial. We’ll then apply a bit of image processing and OpenCV to pre-process and clean up the input allowing Tesseract to successfully OCR the image. From there, we’ll look at an example image where Tesseract OCR, regardless of PSM, fails to correctly OCR the input image.

We’ll start this tutorial by reviewing our project directory structure. Find out where to learn to build an image processing pipeline for your particular application.Compare OCR accuracy before and after applying our image processing routine.

#Cardminder unable to perform recognition how to#

Discover how to apply thresholding, distance transforms, and morphological operations to clean up images.

Learn how basic image processing can dramatically improve the accuracy of Tesseract OCR.

You can then use this example as a starting point for cleaning up your images with basic image processing for OCR. This tutorial will provide you with such an example.

Looking for the source code to this post? Jump Right To The Downloads Section Improving OCR Results with Basic Image ProcessingĮxactly which image processing algorithms or techniques you utilize is heavily dependent on your exact situation, project requirements, and input images however, with that said, it’s still important to gain experience applying image processing to clean up images before OCR’ing them.