Demo Site : https://digit-recog-torch.uc.r.appspot.com/

• handwritten digit recognition using MNIST dataset
• two CNN layers, Batch Normalization, Adam Optimizer
• centering input digit for better recognition
• 99.3% of accuracy at validation

• Flask for web framework
• d3.js for drawing bar graph

• pip install -r requirements.txt
• Tested on Python 3.9.13, pytorch 2.0.0, CUDA 11.8

• Run WebApp

  • python3 server.py (then access to localhost:5000)

• Training Model

  • Training on CPU: python3 train.py
  • Training on GPU: python3 train.py --use_gpu (enabled when gpu and cuda is available)