imamdigmi

import os
import sys

from PyPDF2 import PdfFileReader, PdfFileWriter
from PyPDF2.generic import NameObject, createStringObject


DIR = '/home/idiot/Documents'
FILE = 'contoh.pdf'
FILE_IN = os.path.join(DIR, FILE)

imamdigmi

server {
    listen 80;
    listen 443 ssl;
 
    ssl_certificate /etc/ssl/imamdigmi.crt;
    ssl_certificate_key /etc/ssl/imamdigmi.key;
 
    server_name ~^www\.(?<user>.+\.)?imamdigmi\.com$;
    return 301 "$scheme://${user}imamdigmi.com$request_uri";
}

imamdigmi

# save it as /etc/profile.d/ssh-telegram.sh
# use sed to parse JSON from ipinfo.io
# you can get your user_id by writing to @get_id_bot
USERID="<target_user_id>"
KEY="<bot_private_key>"
TIMEOUT="10"
URL="https://api.telegram.org/bot$KEY/sendMessage"
DATE_EXEC="$(date "+%d %b %Y %H:%M")"
TMPFILE='/tmp/ipinfo-$DATE_EXEC.txt'
if [ -n "$SSH_CLIENT" ] && [ -z "$TMUX" ]; then

imamdigmi

#!/bin/bash
# Install i3-gaps on Ubuntu 16
set -e
set -x
sudo apt-get update && sudo apt-get -y dist-upgrade && \
sudo apt-get install -y libxcb1-dev libxcb-keysyms1-dev libpango1.0-dev libxcb-util0-dev libxcb-icccm4-dev libyajl-dev libstartup-notification0-dev libxcb-randr0-dev libev-dev libxcb-cursor-dev libxcb-xinerama0-dev libxcb-xkb-dev libxkbcommon-dev libxkbcommon-x11-dev autoconf xutils-dev dh-autoreconf

mkdir -p $HOME/repos
cd $HOME/repos

imamdigmi

"""
This notebook will demontrate a pre-trained model to recognition plate number in an image.
Make sure to follow the [installation instructions](https://github.com/imamdigmi/plate-number-recognition#setup) before you start.
"""
import numpy as np
import os
import six.moves.urllib as urllib
import sys
import tarfile
import tensorflow as tf

imamdigmi

People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

imamdigmi

"""
This file I created for generating image file for training and validation datasets for CNN
"""

import matplotlib.path as mpath
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import random
import math

imamdigmi

# Typical setup to include TensorFlow.
import tensorflow as tf

# Make a queue of file names including all the JPEG images files in the relative
# image directory.
filename_queue = tf.train.string_input_producer(
    tf.train.match_filenames_once("./images/*.jpg"))

# Read an entire image file which is required since they're JPEGs, if the images
# are too large they could be split in advance to smaller files or use the Fixed

imamdigmi

Section "ServerLayout"
    Identifier     "layout"
    Screen      0  "nvidia"
    Inactive	   "intel"
EndSection

Section "Device"
    Identifier	   "intel"
    Driver	   "modesetting"
    BusID 	   "PCI:0:2:0"

imamdigmi

{
    "workbench.iconTheme": "eq-material-theme-icons",
    "atomKeymap.promptV3Features": true,
    "editor.multiCursorModifier": "ctrlCmd",
    "editor.formatOnPaste": true,
    "workbench.colorTheme": "Material Theme",
    "editor.fontFamily": "'Fira Code Retina', 'Droid Sans Mono', 'monospace', monospace, 'Droid Sans Fallback'",
    "editor.tabCompletion": true,
    "editor.lineHeight": 27,
    "editor.minimap.enabled": false,