(adapted from: http://www.rumbud.com/d/how-to-install-gnumeric-and-other-linux-apps-on-mac-osx/)
Install homebrew
brew install gnumeric
Open the "Script editor" application and paste the following code:
{ | |
"encoding": "utf-8", | |
"latexdiff_args": "", | |
"git_force_unix_pathsep": true, | |
"ref_single_word": true, | |
"bib": { | |
"max_authors": 2, | |
"sep_authors_first": ", ", | |
"author_serialcomma": true, | |
"sep_authors_last": " and ", |
# cd "$(brew --repository)" && git fetch && git reset --hard origin/master | |
# install homebrew: | |
# /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" | |
# unistall homebrew: | |
# /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/uninstall)" | |
# GRASS: |
(adapted from: http://www.rumbud.com/d/how-to-install-gnumeric-and-other-linux-apps-on-mac-osx/)
Install homebrew
brew install gnumeric
Open the "Script editor" application and paste the following code:
Probably the most straight forward way to start generating Point Clouds from a set of pictures.
VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM). The reconstruction system integrates several of my previous projects: SIFT on GPU(SiftGPU), Multicore Bundle Adjustment, and Towards Linear-time Incremental Structure from Motion. VisualSFM runs fast by exploiting multicore parallelism for feature detection, feature matching, and bundle adjustment.
For dense reconstruction, this program supports Yasutaka Furukawa's PMVS/CMVS tool chain, and can prepare data for Michal Jancosek's CMP-MVS. In addition, the output of VisualSFM is natively supported by Mathias Rothermel and Konrad Wenzel's [SURE]
#bash_profile for my macs | |
#prompt | |
export PS1="\u:\W$ " | |
export LC_ALL=en_US.UTF-8 | |
export LANG=en_US.UTF-8 | |
# PATH | |
export PATH=/usr/local/sbin:/usr/local/bin:/Users/guano/Library/Python/2.7/bin:/usr/local/opt/gdal2/bin:/usr/local/opt/liblas-gdal2/bin:$PATH |