DCGAN Digit Generator

This project implements a Deep Convolutional Generative Adversarial Network (DCGAN) using PyTorch to generate realistic handwritten digits based on the MNIST dataset. The project includes a fully functional Streamlit app that allows users to generate digits or simulate retraining the generator using their own uploaded images.

Model Type: Deep Convolutional GAN

Dataset: MNIST (handwritten digits)

Libraries: PyTorch, TorchVision, Streamlit

Output: 28x28 grayscale digit images generated from random noise