# ankush-me/SynthText

Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.

Repository: https://github.com/ankush-me/SynthText
Canonical: https://ross.abutalabs.com/products/synthtext
Homepage: http://www.robots.ox.ac.uk/~vgg/data/scenetext/
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2023-08-09T09:44:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3643, "days_push": 1120, "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 2146, forks 624 (observed 2026-08-28T04:06:18.819827+00:00)

## What it is
SynthText is a Python tool for generating synthetic scene-text images with ground-truth bounding boxes, as described in the CVPR 2016 paper 'Synthetic Data for Text Localisation in Natural Images'. It renders text onto natural images using depth and segmentation maps, and a pre-generated dataset of ~800k synthetic images is also available.

## Use cases
- generate synthetic training data for text detection models
- create scene text images with ground truth bounding boxes
- augment OCR training datasets with synthetic text
- render text onto natural background images
- train text localisation networks without manual annotation
- produce synthetic scene-text dataset like SynthText 800k

## When to choose
- you need labeled scene-text training data for object detection or OCR models
- you want to reproduce the SynthText dataset or customize its generation
- you have background images with depth and segmentation maps available

## When to avoid
- you need a ready-made OCR or text detection model rather than training data
- your background images lack depth maps and segmentation
- you need actively maintained software with modern Python packaging

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, data-generation, computer-vision, machine-learning
- domain: computer-vision, machine-learning, image-processing, deep-learning
- platform: python, windows
- tags: synthetic-data, scene-text, text-detection, ocr, text-localisation, dataset-generation, cvpr-2016, linux, macos

## Member repositories
- ankush-me/SynthText (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:18.819827+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 2026-08-30T02:51:09.794113+00:00, confidence not recorded.
  - readme: https://github.com/ankush-me/SynthText (fetched 2026-08-28T04:06:18.819827+00:00, sha 10a1ade9a9f8)
- Data as of 2026-08-30T08:39:29.467469+00:00.