metadata
license: mit
tags:
- scene-text-recognition
- scene-text-detection
- ocr
- indic
- paddleocr
library_name: paddleocr
IndicSTSpotter — model weights
Detector + recognizer for IndicSTSpotter, a unified multilingual scene-text spotter covering 11 Indic scripts + Latin with a single detector, a single recognizer, and one frozen 1,638-character dictionary — no script identification, no per-language weights.
Private while the paper is under review.
Contents
| Path | Model | Params | Notes |
|---|---|---|---|
rec_stage2/ |
recognizer (SVTR + CTC head, PP-OCRv6_medium_rec) |
15.8M | synthetic pretrain → real fine-tune; the paper's headline recognizer |
det_mist/ |
detector (DB, PP-OCRv6_medium_det) |
15.5M | trained on real + MIST; used for dense-scene detection & end-to-end |
unified_dict.txt |
— | — | the frozen 1,638-char dictionary shared by all recognizers |
Usage
from huggingface_hub import snapshot_download
d = snapshot_download("MahimaSinghal/IndicSTSpotter", repo_type="model")
from paddleocr import TextRecognition, TextDetection
rec = TextRecognition(model_name="PP-OCRv6_medium_rec", model_dir=f"{d}/rec_stage2")
det = TextDetection(model_name="PP-OCRv6_medium_det", model_dir=f"{d}/det_mist")
For dense scenes, run the detector at a higher inference resolution (long side 1920).
See the code repository's REPRODUCE.md for the exact per-table evaluation commands.
License
MIT (code). Model weights released for research use.