TurkicOCR-SVTRv2-B (ONNX FP32 Deployment Model)

TurkicOCR-SVTRv2-B (ONNX FP32) is the official production export of TurkicOCR-SVTRv2-B optimized for cross-platform CPU and GPU inference without PyTorch dependencies.

Official Links and Resources

• Published Paper (Springer LNCS): https://doi.org/10.1007/978-3-032-41546-2_22
• 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

Quick Usage

import onnxruntime as ort
import numpy as np

session = ort.InferenceSession("model.onnx", providers=["CPUExecutionProvider"])
# Input shape: (batch_size, 3, 48, 640), float32 normalized [-0.5, 0.5]

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)},
  pages={342--358},
  publisher={Springer Nature Switzerland},
  year={2026},
  doi={10.1007/978-3-032-41546-2_22}
}

License

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