Listing pods with kubectl get pods, then select a pod name and copy paste it into kubectl logs [pod name]
| # AWS specific install of Docker | |
| sudo yum update -y | |
| sudo yum install -y docker | |
| sudo service docker start | |
| sudo usermod -a -G docker ec2-user | |
| # exit the SSH session, login again | |
| # Docker | |
| docker run -d --hostname my-rabbit --name some-rabbit -p 4369:4369 -p 5671:5671 -p 5672:5672 -p 15672:15672 rabbitmq |
| require 'rubygems' | |
| require 'v8' | |
| require 'johnson' | |
| require 'ruby_parser' | |
| sexp=Johnson::Parser.parse %{ | |
| var sum=function sum (x,y) { | |
| return x+y | |
| }; |
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
| set :sync_directories, ["public/assets", "public/galleries"] | |
| set :sync_backups, 3 |
| # Sandi Metz - Less - The Path to Better Design | |
| # http://vimeo.com/26330100 | |
| # http://less-goruco.heroku.com/ | |
| # | |
| # Abstractions are more stable than concretions. | |
| class Trip | |
| attr_reader :bicycles, :customers, :vehicle | |
| def prepare(preparers) |