cedricbonhomme

# Installation of a decent editor, emacs
$ sudo apt install emacs

# Prerequisites to build Python
$ sudo apt install make build-essential libssl-dev zlib1g-dev libbz2-dev \
libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev libncursesw5-dev \
xz-utils tk-dev libffi-dev liblzma-dev python-openssl

# Installation of pyenv
$ curl https://pyenv.run | bash

benmarwick

# in a terminal
# python -m pip install --user opencv-contrib-python numpy scipy matplotlib ipython jupyter pandas sympy nose


import cv2
import pandas as pd
import numpy as np
import imutils
from scipy.spatial import distance as dist
from imutils import perspective

yinguobing

"""
read() and grab() in OpenCV VideoCapture takes different time as there is no
decoding for grab() operation. Let's try to find out how much these two methods
differs.
"""
import cv2


def main():
    tm = cv2.TickMeter()

enzanki-ars

#!/bin/bash

#  #########################################################
#  
#  WW      WW   AAA   RRRRRR  NN   NN IIIII NN   NN   GGGG  
#  WW      WW  AAAAA  RR   RR NNN  NN  III  NNN  NN  GG  GG 
#  WW   W  WW AA   AA RRRRRR  NN N NN  III  NN N NN GG      
#   WW WWW WW AAAAAAA RR  RR  NN  NNN  III  NN  NNN GG   GG 
#    WW   WW  AA   AA RR   RR NN   NN IIIII NN   NN  GGGGGG 
#  

hrshovon

This is a note on how to cross compile opencv for pretty much any ARM device(HardFP supported in this case) and deploy. Native
compiling in ARM devices can be painfully slow and they seem to hang often during build(mine got stuck at 43%). So if you happen
to have a desktop/laptop/server running ubuntu or similar linux distro, u can build opencv in fractionth of the time taken for 
native compiling without any issues.
Building opencv3 with TBB and NEON and VFP support can boost opencv performance. Thanks to Adrian at pyimagesearch for pointing 
that out.
Both my PC and target machine aka orange pi zero are running ubuntu 16.04 with python2.7 and python 3.5.
Let us use the term "build machine" for your PC where you are building opencv and "target machine" for the ARM single board computer.

1.Run the following commands in both machines(I think installing these in target machine only would do) to install the necessary libraries etc.(mine worked with them,so they should be enough 

max-mapper

1. install WD Drive Utilities on Mac OS
2. convert to JBOD/EXFAT and turn off Drive Sleep
3. plug into linux

sudo parted /dev/sd<num>
print
rm 1 (and others)
mklabel gpt
unit TB

joseph-zhong

To build OpenCV3.0 for AWS Lambda Python

Summary

Because AWS Lambda runs in a Amazon Linux environment, to run external modules you must

Create the OpenCV build environment

sudo yum update -y

tsiege

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!






\

rwinscot

// Based on the 'roboface' example sketch for Adafruit I2C 8x8 LED 
// backpacks:
//
//  www.adafruit.com/products/870   www.adafruit.com/products/1049
//  www.adafruit.com/products/871   www.adafruit.com/products/1050
//  www.adafruit.com/products/872   www.adafruit.com/products/1051
//  www.adafruit.com/products/959   www.adafruit.com/products/1052
//
// Requires Adafruit_LEDBackpack and Adafruit_GFX libraries.
// For a simpler introduction, see the 'matrix8x8' example.

eskriett

#!/usr/bin/python
# GoogleMapDownloader.py 
# Created by Hayden Eskriett [http://eskriett.com]
#
# A script which when given a longitude, latitude and zoom level downloads a
# high resolution google map
# Find the associated blog post at: http://blog.eskriett.com/2013/07/19/downloading-google-maps/

import urllib
import Image