kuasha

#!/bin/bash
export MAKEFLAGS="-j 3"
set -e

VERSION="1.18.0"
LIBNICE_VERSION="0.1.17" # libnice (v>=0.1.14) needed for webrtcbin
LIBSRTP_VERSION="2.3.0" # libsrtp (v>=2.2.0) required for srtp plugin
WEBRTCAUDIO_VERSION="0.3.1" # webrtc-audio-processing required for webrtcdsp
USRSCTP_VERSION="0.9.3.0" # usrsctp required for webrtc data channels (sctp)

kuasha

//Initialize the Lidar
#include <Wire.h>
#include <LIDARLite.h>

LIDARLite myLidarLite;

//Initialize the Servo
#include <Servo.h>

Servo myservo;  // create servo object to control a servo

kuasha

Installing Nvidia drivers on Ubuntu 16.04 for GTX1070

Build Specification:

• Intel i7-6850K @ 3.60GHz
• GTX 1070

Prerequisites

• Fresh install of Ubuntu 16.04

Note - did not encrypt home directory or xda drive

kuasha

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

kuasha

from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.layers.normalization import BatchNormalization

#AlexNet with batch normalization in Keras 
#input image is 224x224

model = Sequential()
model.add(Convolution2D(64, 3, 11, 11, border_mode='full'))

kuasha

from scipy.misc import imread, imresize

from keras.layers import Input, Dense, Convolution2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, merge, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD
from googlenet_custom_layers import PoolHelper,LRN


def create_googlenet(weights_path=None):