Automating Receipt Digitization with OCR and Deep Learning

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  • You can optionally use the sample images included with the Face sample app, available on GitHub from the Microsoft/Cognitive-Face-Windows repository. That sample app includes a folder, /Data, which contains multiple images of people. You can recursively clone this repository, as well, by the methods described for the Computer Vision sample app.
  • Image Processing With Python Github Pages | www
  • Preface — Fundamental Tools for Image Processing

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Receipt Processing Using AI Builder In PowerApps

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  • Introduction to Image Processing in Python - Colaboratory
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  • Image processing - GitHub Pages
  • Mxnet and Gluoncv are used for image preprocessing methods and are installed optionally. Also, to speed up image processing by performing all the calculations on the video card, install separately special versions of the dependencies (tensorflow, torch, mxnet, gluoncv and …

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Combine px.imshow and datatables to explore image

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  • import cv2 import numpy as np from matplotlib import pyplot as plt # Read the image img = (,0) # Simple thresholding ret,thresh1 = old(img,210,255,_BINARY) (thresh1,’gray’)

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