| # 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 |
| 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 | |
| # 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) |
| name | caffemodel | caffemodel_url | license | sha1 | caffe_commit |
|---|---|---|---|---|---|
Vanilla CNN Model |
vanillaCNN.caffemodel |
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.
| $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"] |
| #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; \ |
| #Gitignore for files generated by Xilinx ISE | |
| *.log | |
| *.svf | |
| *.scr | |
| *.cmd | |
| *.bak | |
| *.lso | |
| *.elf | |
| *.ace |
| 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 |
