torufurukawa

class DotDict(dict):
    """dict class that allows you to access values by dot notation"""
    def __init__(self,arg):
        for k in arg.keys():
            if (type(arg[k]) is dict):
                self[k]=DotDict(arg[k])
            else:
                self[k]=arg[k]

    def __getattr__(self, attr):

AmitThakur

opencvp

OpenCV Practice Repository https://github.com/AmitThakur/opencvp.git

Installing OpenCV on Linux platform (Ubuntu)

Credits: [http://www.raben.com/book/export/html/3] [http://karytech.blogspot.in/2012/05/opencv-24-on-ubuntu-1204.html]

liulixiang1988

import os
# We'll render HTML templates and access data sent by POST
# using the request object from flask. Redirect and url_for
# will be used to redirect the user once the upload is done
# and send_from_directory will help us to send/show on the
# browser the file that the user just uploaded
from flask import Flask, render_template, request, redirect, url_for, send_from_directory
from werkzeug import secure_filename

# Initialize the Flask application

aidin-zadeh

import os
import datetime
import numpy as np
os.environ['KERAS_BACKEND'] = 'theano'
os.environ['THEANO_FLAGS'] = \
    'mode=FAST_RUN,device=cuda0,floatX=float32,optimizer=None'
import keras as ks

pyRobShrk

import numpy as np
from scipy.interpolate import RectBivariateSpline as Spline
import pygeodesy as geo
from pygeodesy.ellipsoidalVincenty import LatLon

class Geoid12B(): #NAD 83 Ellipsoid
    # https://www.ngs.noaa.gov/GEOID/GEOID12B/GEOID12B_CONUS.shtml
    # Download a Geoid Grid in little endian binary format ('g2012bu5.bin')
    def __init__(self, leBinFile):
        glamn, glomn, dla, dlo = np.fromfile(leBinFile,'<f8',4)

berkorbay

## Paketler yüklü değilse install.packages kullanın
## install.packages(c("tidyverse","jsonlite"),repos="https://cran.r-project.org")
library(tidyverse)
library(jsonlite)

ispark_query_url <- "https://data.ibb.gov.tr/api/3/action/datastore_search_sql?sql=SELECT%20*%20from%20%22c3eb0d72-1ce4-4983-a3a8-6b0b4b19fcb9%22"

raw_value <- fromJSON(ispark_query_url)
raw_df <- raw_value$result$records %>% rename_all(~gsub("^_","",.)) %>% rename_all(~gsub(" |\\(|\\)|/","_",.)) %>% tbl_df()

MittalShruti

#Get PPA repo drivers and Install CUDA 10.0
curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_10.0.130-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1604_10.0.130-1_amd64.deb
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda-10-0 cuda-drivers -y

#Install cuda-compatibility 10.0
sudo nvidia-smi -pm 1
sudo apt-get install cuda-compat-10.0

zhaoweizhong

import json
import argparse
import copy


def load_json(file_name):
    file = open(file_name, 'r').read()
    return json.loads(file)

resultakak

#!/bin/sh

#Check the Drive Space Used by Cached Files
du -sh /var/cache/apt/archives

#Clean all the log file
#for logs in `find /var/log -type f`;  do > $logs; done

logs=`find /var/log -type f`
for i in $logs