Overview
Sketch-RNN is a recurrent neural network model that learns to generate sketches of common objects. Trained on millions of doodles from the Quick, Draw! game, it can predict the continuation of a user's drawing or interpolate between different sketches. The model uses a variational autoencoder architecture, enabling it to mimic user drawings and generate similar doodles. It is implemented in TensorFlow and TensorFlow.js, allowing for web-based interactive experiments. Users can experiment with different categories and observe how the model interprets and completes their sketches. The system's novelty lies in its ability to understand and reproduce abstract representations of drawings, offering a unique tool for creative exploration and machine learning education.