iKrishneel

#!/usr/bin/env roseus

(ros::load-ros-manifest "roseus")
(require "package://pr2eus/pr2-interface.l")

(if (not
     (boundp '*pr2*))
    (pr2-init))
(if (not
     (boundp '*irtviewer*))

iKrishneel

#!/usr/bin/env bash

sudo apt-get update
sudo apt-get install libopencv-dev
sudo apt-get install build-essential 
sudo apt-get install checkinstall 
sudo apt-get install cmake 
sudo apt-get install pkg-config 
sudo apt-get install yasm
sudo apt-get install libtiff4-dev

iKrishneel

#!/usr/bin/env bash

sudo apt-get update
sudo apt-get install libopencv-dev build-essential checkinstall cmake pkg-config yasm libtiff4-dev libjpeg-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev python-dev python-numpy libtbb-dev  libqt4-dev libgtk2.0-dev libfaac-dev libmp3lame-dev  libopencore-amrnb-dev libopencore-amrwb-dev  libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils doxygen git

sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install ffmpeg

git clone https://github.com/Itseez/opencv

iKrishneel

#!/usr/bin/env bash

sudo apt-get update
sudo apt-get install libopencv-dev build-essential checkinstall cmake pkg-config yasm libtiff4-dev libjpeg-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev python-dev python-numpy libtbb-dev  libqt4-dev libgtk2.0-dev libfaac-dev libmp3lame-dev  libopencore-amrnb-dev libopencore-amrwb-dev  libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils doxygen git

sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install ffmpeg

sudo apt-get install git

iKrishneel

#!/usr/bin/env bash

sudo apt-get update
sudo apt-get install libopencv-dev build-essential checkinstall cmake pkg-config yasm libtiff4-dev libjpeg-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev python-dev python-numpy libtbb-dev  libqt4-dev libgtk2.0-dev libfaac-dev libmp3lame-dev  libopencore-amrnb-dev libopencore-amrwb-dev  libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils doxygen git

sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install ffmpeg

sudo apt-get install git

iKrishneel

#!/usr/bin/env bash

sudo apt-get update
sudo apt-get install libopencv-dev build-essential checkinstall cmake pkg-config yasm libtiff4-dev libjpeg-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev python-dev python-numpy libtbb-dev  libqt4-dev libgtk2.0-dev libfaac-dev libmp3lame-dev  libopencore-amrnb-dev libopencore-amrwb-dev  libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils doxygen git

sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install ffmpeg

sudo apt-get install git

iKrishneel

#!/usr/bin/env bash

# Copyright (C) 2016 by Krishneel Chaudhary @ JSK Lab, The University
# of Tokyo, Japan

function install-glog {
    /bin/echo -e "\e[1;32m[LOG] Installing GLOG \e[0m"
    
    ipwd=$PWD
    cd /tmp/

iKrishneel

name: "CaffeNet"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
}
layer {
  name: "conv1"
  type: "Convolution"

iKrishneel

How to create a custom Caffe layer in Python?

This tutorial will guide through the steps to create a simple custom layer for Caffe using python. By the end of it, there are some examples of custom layers.

###- Why would I want to do that? Usually you would create a custom layer to implement a funcionality that isn't available in Caffe, tuning it for your requirements.

###- What will I need? Probably just Python and Caffe instaled.

###- Is there any downside?

iKrishneel

# Tiny example of 3-layer nerual network with dropout in 2nd hidden layer
# Output layer is linear with L2 cost (regression model)
# Hidden layer activation is tanh

import numpy as np

n_epochs = 100
n_samples = 100
n_in = 10
n_hidden = 5