Handwritten-digit-recognition

• Digit recognition system is the working of a machine to train itself or recognizing the digits from different sources like emails, bank cheque, papers, images, etc. and in different real-world scenarios for online handwriting recognition on computer tablets or system, recognize number plates of vehicles, processing bank cheque amounts, numeric entries in forms filled up by hand (say-tax forms) and so on.
• First I have done some exploratory data analysis to discover certain features of the data.Then with a little pre-processing and re-shaping of the data,I have made the data fit for CNN model.
• I have first tried a logistic regression model which gave a 91% accuracy,the I have tried a basic CNN model which gave aroun 99% accuracy and finally a well built CNN which gave around 99.6% accuracy.
• Then I have deployed the model using flask on my local machine.I have uploaded all the files including the model json and h5,css,html,js,python files used in this project.

Some Implementation details

• Download and install Anaconda using this documentation https://docs.anaconda.com/anaconda/install/
• I have used Kaggle instead of my local computer so as to improve the computational speed,since the dataset is quite large,your local machine might hang.
• After running Digit_Recognizer_10(1).ipynb on Kaggle,two files namely model.h5 and model.json are generated,download these two files to your local computer.
• It's a good practice to use virtual environment.Create a virtual environment in Anaconda.To learn how use this link- https://heartbeat.fritz.ai/creating-python-virtual-environments-with-conda-why-and-how-180ebd02d1db
• Activate the virtual environment and install Flask using pip (pip install Flask)
• Create a separate folder and then subfolders containing the files as follows namely
  • model
    • load.py(python file)
    • model.h5(downloaded earlier)
    • model.json(downloaded earlier)
  • static(files created using notepad and saved with the required extensions)
    • index.js
    • style.css
  • templates(files created using notepad and saved with the required extensions)
    • index.html
• Create the python file app.py,type the code for deployment of model to flask.
• Go to Anaconda Terminal and run app.py by simply typing app.py in the terminal.
• This should run the application and launch a simple server.
• Run http://127.0.0.1:5000/ to see the final deployed model.