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clear all; clc; home;

%{
f = -[1 1.3 1.7 2];

A = [1 1 1 1;           % sum of all parameters
     1 1.3 1.7 2]       % weight of all parameters

 b = [1;                % sum of all parameters not larger than 1
     1.5];              % the target grade

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#Gitignore for files generated by Xilinx ISE

*.log
*.svf
*.scr
*.cmd
*.bak
*.lso
*.elf
*.ace

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#include "OrientationFusion.h"
#include "time/SystemTime.h"

using namespace Sensors;

#define matrix_set(matrix, row, column, value) \
    matrix->data[row][column] = value

#define matrix_set_symmetric(matrix, row, column, value) \
    matrix->data[row][column] = value; \

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$VersionEnvironmentVariable = "BUILD_NUMBER"
$DnxVersionEnvironmentVariable = "DNX_BUILD_VERSION"

if (Test-Path Env:$VersionEnvironmentVariable) {
    $BuildNumber = [Environment]::GetEnvironmentVariable($VersionEnvironmentVariable)

    if ($BuildNumber -match '^(?<Version>\d+\.\d+\.\d+)-(?<PrereleaseTag>\w+)\.(?<PrereleaseBuild>\d+)')
    {
        $Version = $Matches["Version"]
        $Tag = $Matches["PrereleaseTag"]

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name	caffemodel	caffemodel_url	license	sha1	caffe_commit
Vanilla CNN Model	vanillaCNN.caffemodel	https://github.com/ishay2b/VanillaCNN/blob/master/ZOO/vanillaCNN.caffemodel?raw=true	unrestricted	b5e34ce75d078025e07452cb47e65d198fe27912	9c9f94e18a8909580a6b94c44dbb1e46f0ee8eb8

Implementation of the Vanilla CNN described in the paper: Yue Wu and Tal Hassner, "Facial Landmark Detection with Tweaked Convolutional Neural Networks", arXiv preprint arXiv:1511.04031, 12 Nov. 2015. See project page for more information about this project.

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# Check if SSE instructions are available on the machine where 
# the project is compiled.

MACRO (FindSSE)

IF(CMAKE_SYSTEM_NAME MATCHES "Linux")
   EXEC_PROGRAM(cat ARGS "/proc/cpuinfo" OUTPUT_VARIABLE CPUINFO)

   STRING(REGEX REPLACE "^.*(sse2).*$" "¥¥1" SSE_THERE ${CPUINFO})
   STRING(COMPARE EQUAL "sse2" "${SSE_THERE}" SSE2_TRUE)

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import struct

import itertools
from pyglet.media.drivers.openal import lib_openal as al
from pyglet.media.drivers.openal import lib_alc as alc
import wave
import numpy as np
import ctypes

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# http://christopher5106.github.io/deep/learning/2016/06/07/recurrent-neural-net-with-Caffe.html
# https://github.com/BVLC/caffe/pull/3948

# https://github.com/junhyukoh/caffe-lstm/blob/master/examples/lstm_sequence/lstm_sequence.cpp
# https://github.com/BVLC/caffe/issues/4547

import caffe
import numpy as np
import matplotlib.pyplot as plt