TEATH - Text Extraction And THresholding

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A Streamlit-Heroku WebApp for Extracting Text from Images and applying various thresholding methods using Pytesseract and OpenCV.

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Try the app. It's live here.. http://teath.herokuapp.com

Wanna try on your own and make changes?
Feel free to fork/clone!
Follow these steps.

1. Clone the repository git clone https://github.com/rohankokkula/teath.git
2. For Localhost:
   1. pip install -r requirements.txt
   2. Install tesseract executable from https://github.com/UB-Mannheim/tesseract/wiki,
      keep an eye on installation path.
   3. Open app.py, change tesseract_cmd path to installation path's executable file(eg. C:\Users\rohan\AppData\Local\Tesseract-OCR\tesseract.exe)
   4. Run cmd in current folder and enter streamlit run app.py
   5. App will be deployed at localhost:8501(mostly)
3. For Heroku Deployment:
   1. Create Heroku account and Install Heroku CLI: https://devcenter.heroku.com/articles/heroku-cli#download-and-install
   2. Create APP from Heroku Dashboard.
   3. Go to your APP dashboard settings on heroku website and in the buildpacks URL,
      enter https://github.com/heroku/heroku-buildpack-apt
      Now, Reveal Config vars and add
      KEY: TESSDATA_PREFIX
      VALUE:./.apt/usr/share/tesseract-ocr/4.00/tessdata
   4. Run cmd in current folder and enter heroku login( Logging into your account)
   5. After successful login, follow these steps:

   git add .
   git commit -am "First commit"
   heroku git:remote -a app-name
   git push heroku master
   

   5. App will be deployed at app-name.herokuapp.com

References:

1. Streamlit: https://docs.streamlit.io/en/stable/api.html
2. OpenCV Thresholding: https://docs.opencv.org/master/d7/d4d/tutorial_py_thresholding.html
3. Pytesseract: https://pypi.org/project/pytesseract/
4. TextBlob: https://pypi.org/project/textblob/
5. Tesseract deployment on Heroku using Flask: https://towardsdatascience.com/deploy-python-tesseract-ocr-on-heroku-bbcc39391a8d