There Be Dragons
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
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- I am nfedyashev on github.
- I am nfedyashev (https://keybase.io/nfedyashev) on keybase.
- I have a public key ASDinTHZ0p1CqRzPQVphLzIPY6iqBCZ1G0BbtuDhHj0TRQo
To claim this, I am signing this object:
|# Disable NewRelic pinging|
|curl https://heroku.newrelic.com/accounts/xxxxx/applications/yyyyyyyy/ping_targets/disable -X POST -H "X-Api-Key: xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"|
|heroku maintenance:on --app yourapp-staging|
|heroku pg:reset DATABASE --confirm yourapp-staging --app yourapp-staging|
|heroku pgbackups:restore DATABASE `heroku pgbackups:url --app yourapp-production` --app yourapp-staging --confirm yourapp-staging|
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|heroku maintenance:off --app yourapp-staging|