Davidnet

#!/bin/bash
fileid="### file id ###"
filename="MyFile.csv"
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" > /dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=`awk '/download/ {print $NF}' ./cookie`&id=${fileid}" -o ${filename}

Davidnet

def get_current_wifi_connection():
    for line in iw('dev', 'wlan0', 'link', _iter=True):
        if "SSID" in line:
            return line.split(":")[1]

Davidnet

from sh import iw, grep


print(grep(iw("wlan0", "scan"), "-P", "\"(^|\s)KiwiNet(?=\s|$)\"", "-B", "2"))

Davidnet

# Remap prefix to Control + a
set -g prefix C-a
unbind C-b
bind C-a send-prefix

# force a reload of the config file
unbind r
bind r source-file ~/.tmux.conf

# Set fish as my own shell

Davidnet

#######################
# CUDA 9.0 CUDNN 7.0  #
#######################

sudo apt-get update && sudo apt-get install -y wget tar bzip2

#######################
# CUDA 9.0            #
#######################

Davidnet

ERROR: /home/nvidia/Documents/tensorflow/tensorflow/contrib/layers/BUILD:36:1: Linking of rule '//tensorflow/contrib/layers:gen_sparse_feature_cross_op_py_wrappers_cc' failed (Exit 1): crosstool_wrapper_driver_is_not_gcc failed: error executing command                       
  (cd /home/nvidia/.cache/bazel/_bazel_nvidia/38f510ce87073e6e7989e37d45036c24/execroot/org_tensorflow && \                              
  exec env - \
    LD_LIBRARY_PATH=/usr/local/cuda/lib64/: \
    PATH=/usr/local/cuda/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin \       
    PWD=/proc/self/cwd \
  external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc -o bazel-out/host/bin/tensorflow/contrib/layers/gen_sparse_feature_cross_op_py_wrappers_cc '-Wl,-rpath,$ORIGIN/../../../_solib_local/_U_S_Stensorflow_Scontrib_Slayers_Cgen_Usparse_Ufeature_Ucross_Uop_Upy_Uwrappers_Ucc___Utensorflow' '-Wl,-rpath,$ORIGIN/../../../_solib_local/_U@local_Uconfig_Ucuda_S_S

Davidnet

import numpy as np
import PIL.Image as Image
import PIL.ImageColor as ImageColor
import PIL.ImageDraw as ImageDraw
import PIL.ImageFont as ImageFont

STANDARD_COLORS = [
    'AliceBlue', 'Chartreuse', 'Aqua', 'Aquamarine', 'Azure', 'Beige', 'Bisque',
    'BlanchedAlmond', 'BlueViolet', 'BurlyWood', 'CadetBlue', 'AntiqueWhite',
    'Chocolate', 'Coral', 'CornflowerBlue', 'Cornsilk', 'Crimson', 'Cyan',

Davidnet

import numpy as np
import PIL.Image as Image
import PIL.ImageColor as ImageColor
import PIL.ImageDraw as ImageDraw
import PIL.ImageFont as ImageFont
import random


STANDARD_COLORS = [
    'AliceBlue', 'Chartreuse', 'Aqua', 'Aquamarine', 'Azure', 'Beige', 'Bisque',

Davidnet

import tensorflow as tf
import cv2
import objectdetection

config = tf.ConfigProto()
config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
    detector = objectdetection.ObjectDetection('ssd_mobilenet_v2_coco_2018_03_29/frozen_inference_graph.pb', session=sess)
    cam = cv2.VideoCapture(0)
    while True:

Davidnet

#!/usr/bin/env python
import numpy as np
import cv2, time, re, subprocess, os
from threading import Thread, Event
import json


NUM_LIDARS = 3
LATERAL_CUTOFF = 150
dir_path = os.path.dirname(os.path.realpath(__file__))