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On the recordRead 11 Oct 202616 facts
VietOCR
Plans and prices
VietOCR
Free
Open-source Python library · Apache 2.0 license
Read 11 Oct 2026 · github.com
On the record
- Dataset format
- Training and test annotation files contain an image filename and label separated by a tab.github.com · read 11 Oct 2026
- Handwriting OCR
- Yesgithub.com · read 23 Sep 2026
- Inference
- The Python Predictor can run inference using a pretrained model or user-trained weights, with CUDA or CPU device settings shown.pbcquoc.github.io · read 11 Oct 2026
- Supported inputs
- imagegithub.com · read 23 Sep 2026
- Installation
- The project README gives `pip install vietocr` as the installation command.github.com · read 11 Oct 2026
- Known limitation
- The author says pretrained models can be sensitive to small input-image changes on new datasets and recommends retraining for practical use.pbcquoc.github.io · read 11 Oct 2026
- License
- The GitHub repository states that the library is released under the Apache 2.0 license.github.com · read 11 Oct 2026
- Model architectures
- It provides Attention Seq2Seq and Transformer OCR model types.github.com · read 11 Oct 2026
- Model data
- The project says its models were trained on a 10-million-image dataset that includes generated images, handwriting, and scanned documents.github.com · read 11 Oct 2026
- Model options
- The project offers VGG Transformer and VGG Seq2Seq pretrained models.github.com · read 11 Oct 2026
- Performance
- The README reports full-sequence precision of 0.8800 for VGG Transformer and 0.8701 for VGG Seq2Seq on its 10-million-image experiment.github.com · read 11 Oct 2026
- Purpose
- VietOCR is a library for OCR, with models for recognizing handwritten and printed Vietnamese text.github.com · read 11 Oct 2026
- Speed tradeoff
- The README reports prediction times of 86 ms for VGG Transformer and 12 ms for VGG Seq2Seq on a 1080 Ti.github.com · read 11 Oct 2026
- Support
- The README directs users with problems to create an issue or contact the author by email.github.com · read 11 Oct 2026
- Training
- Users can train models on their own datasets and define custom image augmentation.pbcquoc.github.io · read 11 Oct 2026
