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"""
author: Peb Ruswono Aryan

Binarization Algorithm by Su et al.

@inproceedings{Su:2010:BHD:1815330.1815351,
 author = {Su, Bolan and Lu, Shijian and Tan, Chew Lim},
 title = {Binarization of Historical Document Images Using the Local Maximum and Minimum},
 booktitle = {Proceedings of the 9th IAPR International Workshop on Document Analysis Systems},
 series = {DAS '10},

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import numpy as np
import faiss



def search_knn(xq, xb, k, distance_type=faiss.METRIC_L2): 
    """ wrapper around the faiss knn functions without index """
    nq, d = xq.shape
    nb, d2 = xb.shape
    assert d == d2

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#!/bin/bash

# Purge existign CUDA first
sudo apt --purge remove "cublas*" "cuda*"
sudo apt --purge remove "nvidia*"

# Install CUDA Toolkit 10
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub && sudo apt update
sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb

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Intel for display, NVIDIA for computing

This guide will show you how to use Intel graphics for rendering display and NVIDIA graphics for CUDA computing on Ubuntu 18.04 / 20.04 desktop.

I made this work on an ordinary gaming PC with two graphics devices, an Intel UHD Graphics 630 plus an NVIDIA GeForce GTX 1080 Ti. Both of them can be shown via lspci | grep VGA.

00:02.0 VGA compatible controller: Intel Corporation Device 3e92
01:00.0 VGA compatible controller: NVIDIA Corporation GP102 [GeForce GTX 1080 Ti] (rev a1)

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"""
Create widget with available icons from qt and based on freedesktop.org
https://specifications.freedesktop.org/icon-naming-spec/icon-naming-spec-latest.html
"""
from PyQt5.QtCore import QSize
from PyQt5.QtGui import QIcon
from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget, QGridLayout, QStyle, \
    QFormLayout, QLabel, QScrollArea, QLineEdit, QTabWidget

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m3u8 Downloading

1. Open Chrome Developer tools and click the Network tab.
2. Navigate to the page with the video and get it to start playing.
3. Filter the list of files to "m3u8".
4. Find master.m3u8 or index.m3u8 and click on it.
5. Save the file to disk and look inside it.
6. If the file contains a single m3u8 master url, copy that one instead.
7. Run the program m3u8x.
8. Paste the same m3u8 url in both textboxes (URL and Quality URL) and click "Headers" and set the referral url and user-agent from the request as found in Chrome.

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Purposes

1. iGPU will be used for main display and rendering daily-use softwares in default
2. Dedicated GPUs will be used for computing or offload rendering
3. Reduce the used VRAM of Dedicated GPU, which is mostly used for X11 server rendering

---

Tested Hardware Configuration

OS: Ubuntu 18.04.4 LTS
Mainboads
├── iGPU

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#! /usr/bin/python

import socket,time,string,base64,hashlib,xml.etree.ElementTree as ET
import sys


RTSP_VERSION        = "RTSP/1.0"

LINE_SPLIT_STR      = "\r\n"
HEADER_END_STR      = LINE_SPLIT_STR*2

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Git Crash Course for Beginners

Preface

A good understanding of Git is an incredibly valuable tool for anyone working amongst a group on a single project. At first, learning how to use Git will appear quite complicated and difficult to grasp, but it is actually quite simple and easy to understand.

Git is a version control system that allows multiple developers to contribute to a project simultaneously. It is a command-line application with a set of commands to manipulate commits and branches (explained below). This tutorial will help you get started, and in no time you will be a Git Ninja!

Contents:

• How Git Works
• Installing Git on your Machine