clovaai/deep-text-recognition-benchmark

Health v2 · maintenance only

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Adoption not part of the score

3942 stars · 1132 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementation of a four-stage scene text recognition (OCR) framework from an ICCV 2019 paper, with training and evaluation code for models like CRNN, RARE, and STAR-Net. It provides consistent datasets, pretrained models, and module-wise benchmarking for comparing STR models.

Use cases

• recognize text in scene images with deep learning
• train an OCR text recognition model in PyTorch
• benchmark scene text recognition models fairly
• download pretrained scene text recognition models
• evaluate OCR accuracy on ICDAR benchmarks
• compare CRNN vs RARE vs STAR-Net performance

When to choose

• you need a research-grade baseline for scene text recognition
• you want to reproduce or extend ICCV 2019 STR model comparisons
• you need pretrained text recognition models and standardized LMDB training data

When to avoid

• you need a production-ready OCR service with layout analysis and document parsing
• you want a maintained library with frequent updates and broad API support
• you need handwriting or full-page document OCR rather than cropped word recognition

Facets

library · maturity maintenance

ocr machine-learning deep-learning image-processing computer-vision image-processing deep-learning machine-learning python cross-platform scene-text-recognition pytorch iccv-2019 crnn research-code text-recognition gpu

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