TurkicOCR-SVTRv2-B (Official PyTorch Weights)

TurkicOCR-SVTRv2-B is a lightweight (~35M parameters) line-grounded visual text recognizer tailored for Kazakh and Kyrgyz Cyrillic scripts, trained on the large-scale synthetic TurkicOCR-Cyrillic benchmark.

Official Links and Resources

• GitHub Repository: https://github.com/alenisaw/turkicocr
• Kaggle Models Hub: https://www.kaggle.com/models/alenissayev/turkicocr-svtrv2-b
• Hugging Face Dataset: https://huggingface.co/datasets/alenisaw/turkicocr-cyrillic
• Model Variations:
  • PyTorch FP32: https://huggingface.co/alenisaw/turkicocr-svtrv2-b
  • ONNX FP32: https://huggingface.co/alenisaw/turkicocr-svtrv2-b-onnx
  • ONNX INT8 Quantized: https://huggingface.co/alenisaw/turkicocr-svtrv2-b-int8

Model Details

• Architecture: SVTRv2-B (Single Visual Model Text Recognizer v2, Base configuration).
• Supervision: Connectionist Temporal Classification (CTC) sequence-to-sequence loss.
• Parameters: ~35M (~84.4 MB FP32 weights).
• Input: Bounded document image crops resized to $48 imes 640$ px.
• Output: UTF-8 encoded Cyrillic text string.
• Supported Scripts: Kazakh Cyrillic, Kyrgyz Cyrillic, Russian Cyrillic (including mixed/bilingual text).

Performance Benchmark

Quick Usage

git clone https://github.com/alenisaw/turkicocr-svtrv2-b.git
cd turkicocr
pip install -e .

import cv2
from turkicocr.recognition.predictor import TurkicOCRPredictor

predictor = TurkicOCRPredictor(model_path="epoch_9.pth")
image = cv2.imread("document_line.jpg")
result = predictor.predict(image)
print(result["text"])

Citation

@inproceedings{issayev2026turkicocr,
  title={TurkicOCR-SVTRv2-B: Lightweight Line-Grounded Recognizer for Kazakh and Kyrgyz Optical Character Recognition},
  author={Issayev, Alen and Zhalgas, Aidana},
  booktitle={Analysis of Images, Social Networks and Texts (AIST 2026)},
  series={Lecture Notes in Computer Science (LNCS)},
  publisher={Springer},
  year={2026},
  doi={10.1007/978-3-031-XXXXX-X_XX}
}

@misc{issayev_2026_turkicocr_cyrillic,
  author       = {Issayev, Alen},
  title        = {TurkicOCR-Cyrillic},
  year         = {2026},
  publisher    = {Hugging Face},
  doi          = {10.57967/hf/9255},
  url          = {https://huggingface.co/datasets/alenisaw/turkicocr-cyrillic}
}

License

Apache 2.0. Full code and model checkpoints available at https://github.com/alenisaw/turkicocr.