A SafeTensors-packaged Japanese manga OCR model based on kha-white/manga-ocr-base. It uses the Transformers Vision Encoder Decoder architecture with a ViT image encoder and a character-level Japanese BERT decoder.

Capabilities

The model is designed for printed Japanese text, particularly manga-specific layouts:

vertical and horizontal text
furigana
text overlaid on illustrations
varied fonts and styles
degraded or low-resolution text crops

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python

from transformers import AutoImageProcessor, AutoTokenizer, VisionEncoderDecoderModel

repo = "mayocream/manga-ocr"
model = VisionEncoderDecoderModel.from_pretrained(repo)
processor = AutoImageProcessor.from_pretrained(repo)
tokenizer = AutoTokenizer.from_pretrained(repo)

Input images should be cropped to the text region before recognition. See the original manga_ocr project for its complete normalization and decoding pipeline.

Model details

Task: Japanese image-to-text OCR
Encoder: ViT/DeiT-style image encoder
Decoder: character-level Japanese BERT with cross-attention
Training dataset metadata: Manga109-s
Format: Transformers-compatible SafeTensors

Limitations

This model does not detect text regions. Results depend on crop quality and can be unreliable for handwriting, unsupported characters, non-Japanese text, extreme perspective, or heavily obscured glyphs. OCR output should be reviewed before use in archival, legal, or accessibility-critical workflows.

License

Apache-2.0, matching the upstream model repository.