iandees

I've been interested in computer vision for a long time, but I haven't had any free time to make any progress until this holiday season. Over Christmas and the New Years I experimented with various methodologies in OpenCV to detect road signs and other objects of interest to OpenStreetMap. After some failed experiments with thresholding and feature detection, the excellent /r/computervision suggested using the dlib C++ module because it has more consistently-good documentation and the pre-built tools are faster.

After a day or two figuring out how to compile the examples, I finally made some progress:

Compiling dlib C++ on a Mac with Homebrew

1. Clone dlib from Github to your local machine:

chipx86

#!/usr/bin/env python
#
# Building a tar file chunk-by-chunk.
#
# This is a quick bit of sample code for streaming data to a tar file,
# building it piece-by-piece. The tarfile is built on-the-fly and streamed
# back out. This is useful for web applications that need to dynamically
# build a tar file without swamping the server.
import os
import sys

hi2p-perim

/*
	Check SSE/AVX support.
	This application can detect the instruction support of
	SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, SSE4a, SSE5, and AVX.
*/

#include <iostream>
#ifdef _MSC_VER
#include <intrin.h>
#endif

plentz

# to generate your dhparam.pem file, run in the terminal
openssl dhparam -out /etc/nginx/ssl/dhparam.pem 2048