arjun-kava

function map() {
	emit(1, {
		sum: this.value, // the field you want stats for
		min: this.value,
		max: this.value,
		count: 1,
		diff: 0
	});
}

arjun-kava

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

arjun-kava

#remove if already installed
sudo apt-get purge cuda
sudo apt-get purge libcudnn6
sudo apt-get purge libcudnn6-dev

#install cuda and cudnn
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.0.176-1_amd64.deb
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libcudnn7_7.0.5.15-1+cuda9.0_amd64.deb
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libcudnn7-dev_7.0.5.15-1+cuda9.0_amd64.deb
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libnccl2_2.1.4-1+cuda9.0_amd64.deb

arjun-kava

#!/usr/bin/env python
"""
Form a subset of the Flickr Style data, download images to dirname, and write
Caffe ImagesDataLayer training file.
"""
import os
import urllib.request
import hashlib
import argparse
import numpy as np

arjun-kava

# script used to publish package to npm and push new tag
# step 1 - change version from package json
# step 2 - run ./scripts/publish-npm.sh $version  i.e ./scripts/publish-npm.sh 0.0.3
set -e

if [ $# -eq 0 ]
  then
    echo "Please specify version."
    exit
fi

arjun-kava

####### First Solution ########
# create train and test list
find `pwd`/train -name \*.jpg > train.list
find `pwd`/test -name \*.jpg > test.list

######## Second Solution
# append path to already available files
REPLACE_TRAIN="\/path\/to\/train\/"
REPLACE_TEST="\/path\/to\/test\/"
sed -e "s/^/${REPLACE_TRAIN}/" > train.list

arjun-kava

#  edit .bashrc
nano /home/username/.bashrc


# append following lines into end of file
PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}$ 
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}


#load source again

arjun-kava

# start ubuntu in init 3 mode
init3

# stop lightdm
'sudo service lightdm stop' or 'sudo lightdm stop'

# set permission to executable
chmod +x ./your-nvidia-file.run

# install driver

arjun-kava

export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}

export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

arjun-kava

# calculate ancors based on height and width
./darknet detector calc_anchors data/voc.data -num_of_clusters 9 -width 416 -height 416


# check current IOU by relcall
./darknet detector recall cfg/suit.data cfg/suit-tiny.cfg backup/suit-tiny_100.weights