ereli

import time 
from pathlib import Path
import pygame
import pygame.camera
from pygame.locals import *
import time
import fire

def show():
  pygame.camera.init()

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import mimetypes
import sys
from collections import OrderedDict

filename = sys.argv[1]

def file_type(filename):
    type = mimetypes.guess_type(filename)
    return type

ereli

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 

ereli

pbpaste |tr -d [0-9]|  sed -e 's/^[[:space:]]*//'

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aws dynamodb get-item --table-name='table_name' --key='{"id" : {"S":"12345"}}'|python3 -c 'import sys, json;from dynamodb_json import json_util as jt; data = json.load(sys.stdin); print(json.dumps(jt.loads(data)))'|jq .

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#!/usr/bin/env python3
from sys import stdout
from nltk.corpus import stopwords
import fileinput

#import nltk
#nltk.download('stopwords')

stopword = stopwords.words('english')

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# This is shorthened version of blog post 
#  http://ksopyla.com/2017/02/tensorflow-gpu-virtualenv-python3/

# Get cuda_8.0.61_375.26_linux.run and cudnn-8.0-linux-x64-v5.1.tgz  
#

## update packages
sudo apt-get -y update
sudo apt-get -y upgrade
sudo apt-get -y install gcc make

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CREATE SEQUENCE country_seq;

CREATE TABLE IF NOT EXISTS country (
  id int NOT NULL DEFAULT NEXTVAL ('country_seq'),
  iso char(2) NOT NULL,
  name varchar(80) NOT NULL,
  nicename varchar(80) NOT NULL,
  iso3 char(3) DEFAULT NULL,
  numcode smallint DEFAULT NULL,
  phonecode int NOT NULL,

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# In order for gpg to find gpg-agent, gpg-agent must be running, and there must be an env
# variable pointing GPG to the gpg-agent socket. This little script, which must be sourced
# in your shell's init script (ie, .bash_profile, .zshrc, whatever), will either start
# gpg-agent or set up the GPG_AGENT_INFO variable if it's already running.

# Add the following to your shell init to set up gpg-agent automatically for every shell
if [ -f ~/.gnupg/.gpg-agent-info ] && [ -n "$(pgrep gpg-agent)" ]; then
    source ~/.gnupg/.gpg-agent-info
    export GPG_AGENT_INFO
else

ereli

So you've cloned somebody's repo from github, but now you want to fork it and contribute back. Never fear!

Technically, when you fork "origin" should be your fork and "upstream" should be the project you forked; however, if you're willing to break this convention then it's easy.

* Off the top of my head *

1. Fork their repo on Github
2. In your local, add a new remote to your fork; then fetch it, and push your changes up to it

    git remote add my-fork git@github...my-fork.git