alexandre barilov ab2005

Run:

brew install libuvc
gcc uvccam.c -luvc -o exx
To get device info run: ./exx 1>/dev/null
To save YUV422 to file: ./exx 2>/dev/null 1>video.yuv

Some ffmpeg experiments:

Record raw YUV422 from camera:

The “classical stack” of Software 1.0 is what we’re all familiar with — it is written in languages such as Python, C++, etc. It consists of explicit instructions to the computer written by a programmer. By writing each line of code, the programmer is identifying a specific point in program space with some desirable behavior. In contrast, Software 2.0 is written in neural network weights. No human is involved in writing this code because there are a lot of weights (typical networks might have millions), and coding directly in weights is kind of hard (I tried). Instead, we specify some constraints on the behavior of a desirable program (e.g., a dataset of input output pairs of examples) and use the computational resources at our disposal to search the program space for a program that satisfies the constraints. In the case of neural networks, we restrict the search to a continuous subset of the program space where the search process can be made (somewhat surprisingly) efficient with backpropagation and stochasti

Information transfer rates

Channel	Rate
ADSL	24 Kb
Cell
GSM	14.4Kb
Edge	1.5Mb
HSPA	42Mb
LTE2	173Mb
LTE4	362Mb

USB 2.0 is rated at 480Mbps. That’s about 60 megabytes per second.
USB 3.0 is rated at 5 Gbps. That’s about 640 megabytes per second.
eSATA is rated at 3 Gbps and 6 Gbps. That’s about 373 and 750 megabytes per second.
Firewire is rated at 3 Gbps (400) and 6 Gbps (800). That’s about 373 and 750 megabytes per second.
Thunderbolt is rated at 10 Gbps per channel (x2). Thunderbolt 2 raises that value to 20 Gbps over a single channel. Thunderbolt 3 doubles the bandwidth again to 40 Gbps.
Ethernet is rated at 100 Mbps

bit rates

	<!DOCTYPE html>
	<html lang="en-US" >
	<head>
	<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />
	<title>Sensor Data Explorer</title>
	<link rel="stylesheet" media="all" href="style.css" />
	<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.7.2/jquery.min.js"></script>
	<script src="http://ajax.microsoft.com/ajax/jquery.templates/beta1/jquery.tmpl.min.js"></script>
	<!--[if lt IE 9]>
	<script src="http://html5shim.googlecode.com/svn/trunk/html5.js"></script>

	# -----------
	# User Instructions:
	#
	# Modify the the search function so that it returns
	# a shortest path as follows:
	#
	# [['>', 'v', ' ', ' ', ' ', ' '],
	# [' ', '>', '>', '>', '>', 'v'],
	# [' ', ' ', ' ', ' ', ' ', 'v'],
	# [' ', ' ', ' ', ' ', ' ', 'v'],

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset=utf-8>
	<title>Face Tracking Demo</title>
	<style>
	body { font-family:Verdana,Arial; }
	a { text-decoration:none; color:#666; }
	h1 { font-size:20px; padding:0; }
	header p { font-size:12px; }

	#!/bin/bash
	#####################################################
	# Name: Bash CheatSheet for Mac OSX
	#
	# A little overlook of the Bash basics
	#
	# Usage:
	#
	# Author: J. Le Coupanec
	# Date: 2014/11/04


	layer_depth = {
	'layer_1': 32,
	'layer_2': 64,
	'layer_3': 128,
	'fully_connected': 512
	}
	n_classes = 10 # MNIST total classes (0-9 digits)
	weights = {
	'layer_1': tf.Variable(tf.truncated_normal(

	package com.example.ab.myapplication;

	import android.Manifest;
	import android.app.Service;
	import android.content.Context;
	import android.content.Intent;
	import android.content.pm.PackageManager;
	import android.content.res.Configuration;
	import android.graphics.ImageFormat;
	import android.graphics.Point;