MhLiao/DB
A PyTorch implementation of "Real-time Scene Text Detection with Differentiable Binarization". observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2480
- days_rel: n/a
- days_push: 905
- n_releases_24m: 0
Adoption not part of the score
2260 stars · 486 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A PyTorch implementation of DBNet and DBNet++, real-time arbitrary-shape scene text detection models based on differentiable binarization. It includes training, evaluation, demo scripts, and pretrained models.
Use cases
- detect text in natural scene images
- train a scene text detection model
- run real-time text detection on images
- extract text regions from photos before OCR
- reproduce DBNet research results
- use pretrained DBNet++ models
When to choose
- you need arbitrary-shape scene text detection in PyTorch
- you want a research-grade DBNet implementation with pretrained weights
- you need real-time text detection performance
When to avoid
- you need a production OCR pipeline rather than a research codebase
- you want a maintained library with a license and modern PyTorch support
- you need text recognition, not just detection
Facets
library · maturity maintenance
computer-vision ocr machine-learning deep-learning computer-vision image-processing machine-learning python dbnet dbnet-plus scene-text-detection pytorch text-detection research-code natural-language-processing linux gpu
1 source
- readme: https://github.com/MhLiao/DB · fetched 2026-08-28 · 2c9b563dea06
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| MhLiao/DB | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem