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license: creativeml-openrail-m
datasets:
- Voxel51/rico
pipeline_tag: unconditional-image-generation
tags:
- diffusion
- unet
- image-generation
- ui-design
- tensorflow
- mobile-ui
---
# Forma-1
`Forma-1` is a diffusion model trained on 36,536 mobile UI screenshots from the
RICO dataset. Give it random noise and it will denoise it into something that
looks like a mobile app screen.
It's the model behind DiffuseUI — a project I'm building to explore generative AI
applied to interface design.
---
## Details
| | |
|---|---|
| **Architecture** | U-Net |
| **Framework** | Tensorflow |
| **Image Size** | 64x64 |
| **Timesteps** | 1000 |
| **Noise Schedule** | Linear |
| **Epochs** | 200 |
| **Batch Size** | 64 |
| **Learning Rate** | 1e-4 |
| **Loss** | MSE |
---
## Training Data
Trained on the `RICO` dataset — 36,536 UI screenshots across 27 app
categories. Images were resized to 64x64 and normalized to [-1, 1] before
training.
---
## How It Works
Standard DDPM setup. Forward process adds Gaussian noise to real UI screenshots
across 1000 steps until they're pure static. The U-Net learns to predict that
noise at each step. At generation time you start from pure static and denoise
1000 times — a new UI screen comes out the other end.
---
## Limitations
- 64x64 resolution — outputs are small
- Unconditional — no control over what category of UI gets generated
- Android only — trained exclusively on Android screenshots
- 200 epochs on this dataset size produces recognizable but rough outputs
---
## About
Built by Ricardo Flores as part of DiffuseUI.
[GitHub](https://github.com/imrichie) · [DiffuseUI](#) |