Kevin Miller Airswoop1

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

Clarify and agree on the scope of the system

User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?

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

	# The blog post that started it all: https://neocities.org/blog/the-fcc-is-now-rate-limited
	#
	# Current known FCC address ranges:
	# https://news.ycombinator.com/item?id=7716915
	#
	# Confirm/locate FCC IP ranges with this: http://whois.arin.net/rest/net/NET-165-135-0-0-1/pft
	#
	# In your nginx.conf:

	location / {