heisters

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
	<key>Ansi 0 Color</key>
	<dict>
		<key>Blue Component</key>
		<real>0.19370138645172119</real>
		<key>Green Component</key>
		<real>0.15575926005840302</real>

brandonb927

#!/bin/sh

###
# SOME COMMANDS WILL NOT WORK ON macOS (Sierra or newer)
# For Sierra or newer, see https://github.com/mathiasbynens/dotfiles/blob/master/.macos
###

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/5b3c8418ed42d93af2e647dc9d122f25cc034871/.osx

gist:5020503

tell application "Finder" to set desktopBounds to bounds of window of desktop
set screenWidth to item 3 of desktopBounds
set screenHeight to item 4 of desktopBounds

tell application "System Events"
  set apps to every process whose visible is true
	if ((count of apps) = 0) then return
end tell

repeat with i from 1 to (count of apps)

BinaryMuse

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

rfabbri

  502  git fetch
  503  gitk --all
  504  git branch
  505  git checkout bnl
  506  gitk 
  507  bg
  508  d
  509  cd brl/bbas/bnl
  510  ls
  511  g bnl_fresnel.h 

patriciogonzalezvivo

VisualSFM by Changchang Wu

Probably the most straight forward way to start generating Point Clouds from a set of pictures.

VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM). The reconstruction system integrates several of my previous projects: SIFT on GPU(SiftGPU), Multicore Bundle Adjustment, and Towards Linear-time Incremental Structure from Motion. VisualSFM runs fast by exploiting multicore parallelism for feature detection, feature matching, and bundle adjustment.

For dense reconstruction, this program supports Yasutaka Furukawa's PMVS/CMVS tool chain, and can prepare data for Michal Jancosek's CMP-MVS. In addition, the output of VisualSFM is natively supported by Mathias Rothermel and Konrad Wenzel's [SURE]

application2000

These commands are based on a askubuntu answer http://askubuntu.com/a/581497
To install gcc-6 (gcc-6.1.1), I had to do more stuff as shown below.
USE THOSE COMMANDS AT YOUR OWN RISK. I SHALL NOT BE RESPONSIBLE FOR ANYTHING.
ABSOLUTELY NO WARRANTY.

If you are still reading let's carry on with the code.

sudo apt-get update && \
sudo apt-get install build-essential software-properties-common -y && \
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y && \

nadavrot

High-Performance Matrix Multiplication

This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).

Intro

Matrix multiplication is a mathematical operation that defines the product of

wangg12

# from: http://blender.stackexchange.com/questions/40650/blender-camera-from-3x4-matrix?rq=1
# And: http://blender.stackexchange.com/questions/38009/3x4-camera-matrix-from-blender-camera


# Input: P 3x4 numpy matrix
# Output: K, R, T such that P = K*[R | T], det(R) positive and K has positive diagonal
#
# Reference implementations: 
#   - Oxford's visual geometry group matlab toolbox 
#   - Scilab Image Processing toolbox