Modelpublic

mayocream/manga-ocr

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Model Card

Manga OCR

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

Loading

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.