Portfolio Project

Shape Classifier Demo

Handwritten Shape Recognition

Machine Learning Python PyTorch AWS Docker

Draw one of the supported shapes and let the model classify it.

  • Draw on the canvas (circle, triangle, square, hexagon, or octagon).
  • Click “Classify” to submit the drawing.
  • Use the eraser button (or press C) to clear and try again.
  • Review the confidence bar and per-shape scores on the right.

STAR Summary

Situation
I wanted a model that can tell what shape someone drew.
Task
Owned the end-to-end build, from implementation through the final deliverable.
Action
  • Used Google's QuickDraw sketches and built train/validation splits.
  • Trained a small ResNet18 classifier in PyTorch.
  • Deployed a CPU-only AWS Lambda endpoint so the browser can request predictions.
Result
  • High accuracy on a five-shape subset (results vary by split and drawing style): circle, triangle, square, hexagon, and octagon.
  • Predictions return quickly once the Lambda container is warm; cold starts can take longer.