Let me introduce you Adrian Rosebrock and his http://www.pyimagesearch.com/ website. It’s about computer vision and image processing using Python and OpenCV. Looks like there are more than one person that like to share programming experience via blogging :) Here’s how Adrian position himself: This blog is dedicated to helping other programmers understand how image search engines work. While a lot of computer vision concepts are theoretical in nature, I’m a big fan of “learning by example”.
p | This was a request from a(href=“http://www.reddit.com/r/computervision/comments/2a1lvi/help_how_to_process_this_image_to_find_the_circles/") /r/computervision. | A reddit member was asking on how to count number of eggs on quite | noisy image like you may see below. | I’ve decided to write a simple algorithm that does the job and explain how it works. div.beforeafter img(src="source.jpg",alt="before") img(src="display.jpg",alt="after") span.more h2 Step 1 - Filter image p img(src=“source.jpg”,alt=“Source image”) | The original image has noticeable color noise and therefore it must be filtered before we pass it to further stages.
This is a second issue of monthly computer vision digest - a list things that you don’t wanna miss, a list of what happened in computer vision in June 2014. Previous issues: - Computer Vision Digest (May 2014) In this issue: - Signed Distance Field - converting raster masks to vector form - QVision: Computer Vision Library for Qt - Closer look on licence plate recognition - OpenCV 3.0
In this post I’ll show you how you can train cascade classifier with OpenCV very quickly even if you have low-end hardware using virtual machine in the cloud. Why Clouds? Well, training a descriptor takes a lot of time. Depending on template size, number of samples and stages, it can take from several ours to a couple of days to train such cascade! Be prepared that during training stage your PC will likely be unusuable due to high RAM usage and CPU load.
![AKAZE logo][akaze-logo] A new version of KAZE and AKAZE features is a good candidate to become a part of OpenCV. So i decided to update KAZE port i made a while ago with a new version of these features and finally make a pull request to make it a part of OpenCV. KAZE are now a part of OpenCV library The OpenCV has accepted my pull-request and merged KAZE port into master branch of the OpenCV library.
Perhaps, someone may find this post provocative or offensive. But in fact it’s not. Very often i receive offers from all kind of CXX (CEO, CTO, COO, C-bla-bla-bla) that can be formulated like “We want to build product X using OpenCV”. What’s wrong with you guys? OpenCV is not a panacea. In this post i’ll try to reveal this myth. Although OpenCV does a great help on getting proof-of-concept software that every start-up needs most of all at early stages, it can make a nightmare for developers in production stage.
img.img-thumbnail.pull-left(src=“travis-logo.png”) p | In this post i will show you how i implemented continuous integration and testing in my a(href=“http://cloudcv.io") CloudCV | project. Healthy unit tests and easy and continuous integration workflow is a must in any project goes beyound “Hello, world” application. | Today software is a mixture of technologies of all kind. Therefore it can break literally everywhere. Each integration point is a place of risk. | The CloudCV has a C++ backend that is using OpenCV library, it’s front-end is written in Node.
p | I welcome you at my new blog home! After using Wordpress for three years of bloging i decided that i’m unhappy with this blog engine. | Personally, i wanted something more “geeky”, if you know what i mean. Wordpress is like a “click to win” - it offers a lot, but keeps you | in strict sandbox called Wordpress API. But first of all - it’s too slow as a blogging platform for one people.
img.pull-left.img-thumbnail(src=“instant-opencv-cover.jpg”,alt=“Instant OpenCV for iOS”) p | A new book from authors of OpenCV targeted on iOS development using OpenCV. ul li Learn something new instantly. A short, fast, focused guide delivering immediate results li Build and run your OpenCV code on iOS li Become familiar with iOS fundamentals and make your application interact with the GUI, camera, and gallery li Build your library of computer vision effects, including photo and video filters