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StudiOCR

StudiOCR is an application to index notes and make them searchable by using OCR.

  • Select JPEG or PNG files to create a document
  • Search through a document to see if it has any matching text
  • Any matching text will be highlighted with a colored box based on confidence level

Installation Instructions

Prerequisites

  • You must have Qt, Tesseract OCR, and Poppler installed.
  • Ubuntu or Debian
    • sudo apt install qt5-default tesseract-ocr poppler-utils
  • Arch or Manjaro
    • sudo pacman -S qt5-base tesseract poppler

Install through PyPi

  • Optionally, create a fresh venv for installing the package in
    • python3 -m venv venv_StudiOCR
    • source venv_StudiOCR/bin/activate
      • To deactivate the venv run deactivate
  • pip install StudiOCR
  • Once installed, run StudiOCR to launch the application

Install from Source

  • Optionally, create a fresh venv for installing the package dependencies in
    • python3 -m venv venv_StudiOCR
    • source venv_StudiOCR/bin/activate
      • To deactivate the venv, rundeactivate
  • git clone https://github.com/BSpwr/StudiOCR
  • cd StudiOCR
  • pip install -r requirements.txt
  • Once installed, cd into the source directory cd StudiOCR and run python3 main.py to launch the application

Usage

Main Window

  • Click the Add New Document button to open the add new document window interface
  • Click on a document thumbnail (which is generated from the first page) to open the document window interface
  • Toggle remove mode to remove existing documents
  • Search for a document based on document name by typing in the search bar with the DOC bullet selected
  • Search for a document based on matching OCR text by typing in the search bar with the OCR bullet selected

Add New Document Window

  • Add/Remove *.png, *.jpg, *.jpeg, or *.pdf files to be processed by OCR into a document in the database
  • Input the document name
  • Click show document preview to preview the document with all images as pages on the side
  • Change the preset for image analysis optimization between: Custom, Screenshot, Printed Text (PDF), Written Paragraph, or Written Page
  • Underneath the Process Document button is a status bar for processing any PDFs selected into images
  • Click on the info icon to display a window explaining document options
  • Select the processing model you wish to use: Best (for accuracy) or Fast (for speed)
  • Select whether you wish to do image preprocessing (convert to grayscale and increase text contrast)
  • PSM Number:
PSM Number Value
3 Fully automatic page segmentation, but no OSD. (Default)
4 Assume a single column of text of variable sizes.
5 Assume a single uniform block of vertically aligned text.
6 Assume a single uniform block of text.
7 Treat the image as a single text line.
8 Treat the image as a single word.
9 Treat the image as a single word in a circle.
10 Treat the image as a single character.
11 Sparse text. Find as much text as possible in no particular order.
12 Sparse text with OSD.
13 Raw line. Treat the image as a single text line, bypassing hacks that are Tesseract-specific.

Document Window

  • Enter text in the search bar to search for matching text in the document
  • Click the Next/Previous Page buttons to cycle through the pages in the document
  • The current page number is shown at the bottom of the window and can be manually entered
  • Toggle show matching pages to only display pages with matching text and to cycle through them
  • Hold Ctrl and scroll up/down to zoom in and out. Users can also pan around the image. This applies to any images being displayed.
  • Toggle Case Sensitive to do a case sensitive search
  • Right click the image and click Save Image As to save the image as a JPEG
  • Click the Export as PDF button to export the document as a pdf
  • Click the Rename doc button to rename the document
  • Click the Add pages button to add more pages to the current document
  • Box Color:
Box Color Confidence Value
Green Greater than or equal to 80
Blue Less than 80 and greater than or equal to 40
Red Less than 40
  • Click on the info icon to display a window explaining document features

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Indexing of Notes using OCR

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