Robert Armenski T1T4N

Moving from jQuery

Events

// jQuery
$(document).ready(function() {
  // code
})

Guide to install PyQt5 on Mac OS X with python 3.4 virtualenv

Description

A simple guide to install PyQt5 on Mac OS X 10.9 (Maverick) and use python 3.4 on a virtualenv.

Requirements

xcode 5.1.1
python 3.4.0
Qt libraries 5.2.1

Using Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

	void *find_sys_call_table(void kernel_addr, int kernel_size)
	{
	/*
	Check for the system_call_fastpath() signature, hand-written piece of
	assembly code from arch/x86/kernel/entry_64.S:

	ja badsys
	mov rcx, r10
	call sys_call_table[rax * 8]
	mov [rsp + 20h], rax

	void TestCopy()
	{
	BOOL cond = FALSE;
	IFileOperation *FileOperation1 = NULL;
	IShellItem isrc = NULL, idst = NULL;
	BIND_OPTS3 bop;
	SHELLEXECUTEINFOW shexec;
	HRESULT r;

	do {

	#include "stdafx.h"

	#define DB(_val_) __asm __emit (_val_)

	#define INVALID_SYSCALL (DWORD)(-1)

	// code selectors
	#define CS_32 0x23
	#define CS_64 0x33