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@dannguyen
dannguyen / README.md
Last active December 28, 2023 15:21
Using Python 3.x and Google Cloud Vision API to OCR scanned documents to extract structured data

Using Python 3 + 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

var active = false;
function changeRefer(details) {
if (!active) return;
for (var i = 0; i < details.requestHeaders.length; ++i) {
if (details.requestHeaders[i].name === 'Referer') {
details.requestHeaders[i].value = 'http://www.google.com/';
break;
}
@cmod
cmod / minmal_twitter.css
Created September 13, 2012 18:45 — forked from maxfenton/gist:3670929
Twitter stylebot
/* -------------------------------------------------
MINIMAL TWITTER FOR FLUID / USERSTYLES
Special thanks to:
Max Fenton (@maxfenton) for kicking this off
------------------------------------------------- */
.trends, .bird-topbar-etched, .wtf-module, .site-footer, .topics {