prthamesh pratos

## README.md

      
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                pratos
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              Created
              September 11, 2017 13:29
                — forked from dannguyen/README.md
            
              
                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

  
## how-do-i-into-git.md

      
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                pratos
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              Created
              September 10, 2017 08:15
                — forked from mplewis/how-do-i-into-git.md
            
          
    How Do I Into Git?

a helpful primer for users sick of git's poorly-named commands
I've used Git since 2011, and this is the stuff that I've always had to Google to remember. I hope it helps you not hate Git so much.
Learning About the Repo

Learning About History


## gist:b32f6a780b462c68c18b6ed2b0a5f891

      
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                pratos
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              Created
              July 13, 2016 04:20
                — forked from debasishg/gist:8172796
            
              
                A collection of links for streaming algorithms and data structures
              
          
General Background and Overview


Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&amp;rep