paulaksm

/*
 * September 21, 2009
 * Author Tawat Atigarbodee
 * Modified in March 03, 2018
 * This program creates a Control Window for controlling NXT brick running NXTtr.java via USB.
 *
 * To compile this program.
 *  -   Install Lejos 0.8.5
 *  -   Include Lejos_nxj library to the project path
 *  -   Compiled with nxjpcc

paulaksm

/* Application for brick, compiled with nxjc 
   Client-Server architecture
   Commands sent by NXTremoteControl_TA.java*/
import java.io.*;
import lejos.nxt.*;
import lejos.nxt.comm.*;


public class NXTtr
{ 

paulaksm

# USB socket communication with LEGO Minstorms NXT -- adapted from nxt-python library
# Copyright (C) 2006, 2007  Douglas P Lau
# Copyright (C) 2009  Marcus Wanner
# Copyright (C) 2011  Paul Hollensen, Marcus Wanner
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#

paulaksm

import cv2
import numpy as np
'''
CAMERA TEST
'''
cam = cv2.VideoCapture(0)
ret, frame = cam.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imwrite('gray.png', gray)

paulaksm

'''
Uses USB connection (requires pyusb and udev rules for lego USB)
Tries to increase velocity using synchronized motors for forward and backward motion.
Is possible to increase power up to 60 in weak_turn() calls, but it best behaves with 40
'''
import nxt
import time
import keyboard as key
import USBInterface

paulaksm

/* Application for brick, compiled with nxjc 
   Client-Server architecture
   Commands sent by NXTremoteControl_TA.java*/
import java.io.*;
import lejos.nxt.*;
import lejos.nxt.comm.*;


public class NXTpy
{ 

paulaksm

#!/bin/bash
wget https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv

paulaksm

# If under a valid institutional IP address, the followng command will download an IEEE hosted paper of a specific <ID-NUMBER> 
and saved it as paper.pdf

wget "http://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=&isnumber=&arnumber=<ID-NUMBER>" -O paper.pdf

paulaksm

''' Generate HDF5 files for array images and their labels... unfortunately this function won't work inside the Kaggle kernel 
because of its limited resources
'''
def create_data_labels(height=256, width=455, channels=3, filename='driving'):
    data_filename = filename + '_data'
    label_filename = filename + '_labels'
    txt_labels = pd.read_csv('../input/driving_dataset/driving_dataset/data.txt', sep=" ", header=None)
    path = '../input/driving_dataset/driving_dataset/'
    hdf5_file = h5py.File('self_driving_dataset.hdf5', mode='w')
    hdf5_file.create_dataset(data_filename, (txt_labels.shape[0], height, width, channels), np.uint8)

paulaksm

!ln -sf /opt/bin/nvidia-smi /usr/bin/nvidia-smi
!pip install gputil

import psutil
import humanize
import os
import GPUtil as GPU
GPUs = GPU.getGPUs()
# XXX: only one GPU on Colab and isn’t guaranteed
gpu = GPUs[0]