---
title: AlignDRAW
emoji: 🖍️
colorFrom: gray
colorTo: yellow
sdk: gradio
sdk_version: 6.16.0
python_version: "3.10"
app_file: app.py
hardware: zero-a10g
pinned: false
short_description: One of the first text-to-image models (2015), resurrected
---

# 🖍️ AlignDRAW

A resurrection of **AlignDRAW** (Mansimov, Parisotto, Ba, Salakhutdinov — *Generating Images from
Captions with Attention*, ICLR 2016) — **one of the very first neural text-to-image models**,
predating GAN and diffusion text-to-image.

Type a caption and watch a recurrent-attention VAE **draw it onto a 32×32 canvas over 32 steps**,
attending to the caption words at each step. The results are tiny and blurry — but their colour and
layout track the caption (red for "stop sign", yellow for "school bus", green fields for
"elephants") — exactly the fidelity this model had in 2015.

The [original Theano code](https://github.com/mansimov/text2image) shipped **no pretrained
weights**, so this is a faithful **PyTorch re-implementation trained from scratch** on the original
COCO 32×32 caption data (still online at `cs.toronto.edu/~emansim`). Runs on ZeroGPU. Weights +
model + dictionary hosted at
[`mediasynthesismuseum/aligndraw`](https://huggingface.co/mediasynthesismuseum/aligndraw).

Credit: Elman Mansimov, Emilio Parisotto, Jimmy Ba, Ruslan Salakhutdinov; built on DRAW
(Gregor et al., 2015).