metadata
license: mit
language:
- en
metrics:
- accuracy
pipeline_tag: image-classification
tags:
- art
Realtime Digit Draw
Framework: PyTorch
Purpose: Interactive handwritten digit recognition for learning and experimentation.
Overview
Realtime Digit Draw allows users to draw a digit in a Pygame window and see a real-time prediction from a trained ANN model.
This project is for learning purposes and demonstrates a simple ANN trained on MNIST with live inference.
Features
- Draw digits directly using the mouse
- Real-time predictions using a small PyTorch ANN model
- Preprocessing compatible with MNIST 28×28 grayscale inputs
- Lightweight and fully offline
Files
| File | Description |
|---|---|
app.py |
Main interactive drawing UI |
model.py |
ANN architecture definition |
inference.py |
Load model and predict digits |
weights.pth |
Trained model weights |
train.py |
Script used for training the model |
requirements.txt |
Required Python packages |
.gitignore |
Folders/files ignored in the repo |