# tonybeltramelli/pix2code

pix2code: Generating Code from a Graphical User Interface Screenshot

Repository: https://github.com/tonybeltramelli/pix2code
Canonical: https://ross.abutalabs.com/products/pix2code
Language: Python
License: Apache-2.0
License Family: permissive
Topics: deep-learning, datasets, deep-neural-networks, front-end-development, graphical-user-interface
Last push: 2024-05-29T04:48:27+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3388, "days_push": 826, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 12023, forks 1427 (observed 2026-08-28T04:10:51.441405+00:00)

## What it is
A research project and model that uses deep learning to generate front-end code (iOS, Android, web) from a single GUI screenshot. It includes the trained model code, datasets, and accompanying research paper, shared for educational purposes only.

## Use cases
- generate code from a UI screenshot
- convert design mockups to front-end code
- train a model to turn images into code
- research image-to-code generation
- get a dataset of GUI screenshots paired with code

## When to choose
- you are researching image-to-code or screenshot-to-code models
- you need a labeled dataset of UI screenshots with corresponding DSL code
- you want a reference implementation of a CNN+RNN encoder-decoder for code generation

## When to avoid
- you need production-ready code generation from designs
- you want a maintained tool with support for modern frameworks
- you need accurate, real-world usable output rather than a proof of concept

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: deep-learning, machine-learning, image-processing
- domain: deep-learning, computer-vision, frontend
- platform: python, cross-platform
- tags: screenshot-to-code, research-project, neural-networks, educational, dataset, gui, code-generation, research

## Member repositories
- tonybeltramelli/pix2code (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:51.441405+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:14:59.679163+00:00, confidence not recorded.
  - readme: https://github.com/tonybeltramelli/pix2code (fetched 2026-08-28T04:10:51.441405+00:00, sha a5b7b4673c5f)
- Data as of 2026-08-30T08:39:29.467469+00:00.