Optical Character Recognition (OCR) MasterClass in Python
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Welcome to Course “Optical Character Recognition (OCR) MasterClass in Python”
Optical character recognition (OCR) technology is a business solution for automating data extraction from printed or written text from a scanned document or image file and then converting the text into a machine-readable form to be used for data processing like editing or searching.
BENEFITS OF OCR:
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Reduce costs
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Accelerate workflows
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Automate document routing and content processing
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Centralize and secure data (no fires, break-ins or documents lost in the back vaults)
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Improve service by ensuring employees have the most up-to-date and accurate information
Some Key Learning Outcomes of this course are:
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Recognition of text from images using OpenCV and Pytesseract.
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Learn to work with Image data and manipulate it using Pillow Library in Python.
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Build Projects like License Plate Detection, Extracting Dates and other important information from images using the concepts discussed in this course.
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Learn how Machine Learning can be useful in certain OCR problems.
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This course covers basic fundamentals of Machine Learning required for getting accurate OCR results.
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Build Machine Learning models with text recognition accuracy of above 90%.
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You will learn about different image preprocessing techniques such as grayscaling, binarization, erosion, dilation etc… which will help to improve the image quality for better OCR results.
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3Opening and Viewing an imageVideo lesson
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4Obtaining information about opened imageVideo lesson
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5Rotate and ResizeVideo lesson
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6Crop an image using pillowVideo lesson
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7Add text on an Image using pillowVideo lesson
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8Add Padding to image with pillowVideo lesson
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9Blur an image using pillowVideo lesson
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10Concatenate images using PillowVideo lesson
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11Save an ImageVideo lesson
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