Ayke

OpenCV version: 4.3.0 Python version: 3.6

Prerequisite

Required libraries

sudo apt-get update
sudo apt-get install curl libssl-dev
sudo apt-get install ffmpeg

dzil123

package frc.robot.util;

public class Deadband {
    private double minValue;
    private double m;
    private double deadband;

    public Deadband(double minValue, double deadband) {
        this.minValue = minValue;
        m = calcM(minValue, deadband);

mathiasvr

# Generate lookup table for converting between perceived LED brightness and PWM

# Adapted from: https://jared.geek.nz/2013/feb/linear-led-pwm
# See also: https://ledshield.wordpress.com/2012/11/13/led-brightness-to-your-eye-gamma-correction-no/

from sys import stdout

TABLE_SIZE = 256 # Number of steps (brightness)
RESOLUTION = 2**10 # PWM resolution (10-bit = 1024)

arastu

#!/usr/bin/env bash
docker ps -a -q | xargs docker rm -f
docker images -a -q | xargs docker rmi -f
docker volume ls -q | xargs docker volume rm -f
docker network ls | xargs docker network rm
docker system prune -f

nohamelin

// -sp-context: browser
/* This Source Code Form is subject to the terms of the Mozilla Public
 * License, v. 2.0. If a copy of the MPL was not distributed with this
 * file, You can obtain one at http://mozilla.org/MPL/2.0/.
 *
 *
 * xseei.import.js
 * ===============
 * code-revision 2
 *   https://gist.github.com/nohamelin/8e2e1b50dc7d97044992ae981487c6ec

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 

grenade

#!/bin/bash

# generate new personal ed25519 ssh key
ssh-keygen -o -a 100 -t ed25519 -f ~/.ssh/id_ed25519 -C "rob thijssen <rthijssen@gmail.com>"

# generate new host cert authority (host_ca) ed25519 ssh key
# used for signing host keys and creating host certs
ssh-keygen -t ed25519 -f manta_host_ca -C manta.network

eval "$(ssh-agent -s)"