Guided Filter

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Testing Guided Filter (actually testing Jupyter notebook)

https://github.com/subokita/guided_filter/tree/master

Depends on numpy, scipy, matplotlib, and jupyter

The good part is that now I can somehow annotate my code with the original equations (well, when I don’t butcher it). Still, probably the best IDE is when you write math equation using latex, or so, and it will automatically generate backend python / c++ code  for it.

Screen Shot 2017-08-14 at 19.02.50

 

Depth Map mesh generation

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SceneKitTest.gif

Depth map (or height map?) mesh generation using SceneKit. This is my first time using SceneKit and it’s way less hassle than writing every single OpenGL operations line by line.

Basically what it does is to generate terrain / height map using given depth map. The calculation of the normal is still messed up though.

You can get the source code here:

https://github.com/subokita/SceneKit-Testhttps://github.com/subokita/SceneKit-Test

Edit:
Updated with:

  1. Testing handwriting custom fragment shader (well, just trying out how to set SceneKit to use my own fragment shader)
  2. Metal compute shader, kernel function is taken from InvasiveCode which is pretty straightforward. The only thing that I wanted to know is the initialisation steps.

Screen Shot 2017-08-07 at 08.58.04.png

Added CMake / installation scripts to Three.cpp

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Hurray, I just added Cmake and some bash scripts to install Three.cpp, it only works on Mac OS X though, since I don’t own a Windows PC.

Just run the build/install.sh, and it should try to install Homebrew if it’s needed, then it will install necessary libraries (e.g. glm, glfw3, etc), before running CMake, and makefile.

When the installation is done successfully, it should run a test demo that shows something like this:

2014-08-18 14_19_12

 

And thanks to github, I’ve created a GitHub page at: http://subokita.github.io/Three.cpp-Rev-2/, check it out and thanks!

PS: I’m still looking for collaborators / contributors for this port though, it has kind of deviated from the original three.cs, and there’s so many interesting thing that I wanted to add, but my 3D programming skill is not the greatest.

Ongoing port of Three.cpp

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This is an ongoing process of porting Three.js to C++ / OpenGL. The main idea is not to create the fastest 3D engine out there, but to create a 3D engine that’s simple enough to instantiate, so that other field of computing could use it rapidly for prototyping. Thus reducing the unnecessary hoops for OpenGL newcomers when it comes to thing such as context creation, loading shaders, etc. Continue reading

Robust Text Detection with Edge Enhanced MSER

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Sorry for the shilling, but here’s my upcoming project:

https://plusplusone.herokuapp.com

Please register your email address if you’re interested in it.


 

This is implementation of Chen, Huizhong, et al. “Robust Text Detection in Natural Images with Edge-Enhanced Maximally Stable Extremal Regions.” [1]. Partly based on the sample available on Matlab [2]. Continue reading

Visualizing Hough Transform

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I won’t go into Hough Transform, since you can find better explanations elsewhere, and it seems like most people at least get the basic idea behind it. But here’s something I whipped out for fun (well, I was reading Fast Symmetry Detection using Hough Transform, and I’d never written Hough from scratch before), visualizing the Hough lines, along with the accumulation matrix, which represents the (r, theta) space.

Continue reading

SLIC Superpixels on OpenCV

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Sorry for the shilling, but here’s my upcoming project:

https://plusplusone.herokuapp.com

Please register your email address if you’re interested in it.


 

Here’s a sample implementation of SLIC (Simple Linear Iterative Clustering) Superpixel algorithm using OpenCV, C++, and Intel TBB. It’s an adaptation of Pascal Mettes’ version which you can find over here: https://github.com/PSMM/SLIC-Superpixels

Continue reading

Non Rigid Face Tracking

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I rewrote the Non Rigid Face Tracking code by Jason Saragih (http://jsaragih.org/), which is published in the book “Mastering OpenCV with Practical Computer Vision Projects”. Copyright Packt Publishing 2012. (http://www.packtpub.com/cool-projects-with-opencv/book)

Mainly because I want to understand how it works, and partly because I wanted to clean up the code (which is arguably kind of messy). Continue reading