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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 |
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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 |
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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 |
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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 [email protected] |