arundasan91

cd ~
mkdir .packages
cd .packages

# Install CUDA
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo add-apt-repository "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
sudo apt-get update

arundasan91

## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!

# cuDNN acceleration switch (uncomment to build with cuDNN).
USE_CUDNN := 1

# CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := 1

# uncomment to disable IO dependencies and corresponding data layers

arundasan91

#!/bin/bash
sudo apt update
sudo apt install libhdf5-dev
sudo apt-get install -y opencl-headers build-essential protobuf-compiler libprotoc-dev libboost-all-dev libleveldb-dev hdf5-tools libhdf5-serial-dev libopencv-core-dev  libopencv-highgui-dev libsnappy-dev libatlas-base-dev cmake libstdc++6-4.8-dbg libgoogle-glog0v5 libgoogle-glog-dev libgflags-dev liblmdb-dev git python-pip gfortran
sudo sh -c "sudo echo '/usr/local/cuda/lib64' > /etc/ld.so.conf.d/cuda_hack.conf"
sudo ldconfig /usr/local/cuda/lib64
pip install --upgrade --user pip
pip install scikit-image --user
cd /home/$USER/packages/
git clone https://github.com/BVLC/caffe.git

arundasan91

#!/bin/bash
echo '1'
export PATH=$PATH:/home/student/.local/bin/
echo '2'
su - student -c "bash -c '/home/student/.local/bin/jupyter notebook'"
echo 'Launched Jupyter Notebook'
#touch /home/student/testrclocal
sed -i "s|PasswordAuthentication no|PasswordAuthentication yes|g" /etc/ssh/sshd_config
echo '3'
export HOSTIP=`hostname -I`

arundasan91

#!/usr/bin/env bash
# OpenRC extraction
function extract_json_key {
    RESULT=$(echo "$2" | sed "s/.*$1\": \"//g" | sed 's/".*//g')
    echo "$RESULT"
}

JSON_VENDOR_DATA=$(curl -s http://169.254.169.254/openstack/latest/vendor_data.json)
SITE=$(extract_json_key "site" "$JSON_VENDOR_DATA")

arundasan91

#!/bin/bash

ls -1 *.tiff | parallel convert '{}' '{.}.jpg'
find . -name "*.tiff" -print0 | xargs -0 -I {} rm {}

arundasan91

heat_template_version: 2015-10-15

description: Implementation of Apache MXNET Distributed Deep Learning Appliance for OpenStack.

parameters:
  key_name:
    type: string
    label: Key name
    description: Name of a key pair to enable SSH access to the instance
    default: default

arundasan91

def download_video(url, output_dir, filename, ext='mp4'):
    """Function to download video's from YouTube to a specific location.
    
    Args:
        url: YouTube URL.
        output_dir: Output directory to save the video.
        filename: Filename of the video.
        ext: File type to save the video to. Default to mp4.
    """
    import os

arundasan91

def video_to_frames(input_loc, output_loc):
    """Function to extract frames from input video file and save them as separate frames in an output directory.
    
    Args:
        input_loc: Input video file.
        output_loc: Output directory to save the frames.
        
    Returns:
        None
    """

arundasan91

def showanyVideo(baseDir=None,fname=None):
    """Function to display any video in Ipython or Jupyter Notebook given a directory in which the video exist and the video file name.
    Args:
        baseDir: Directory containing the video
        fname: Filename of video.
    """
    from IPython.display import HTML
    import os
    location = baseDir + fname
    if os.path.isfile(location):