fumetodev/PP-OCRv6_small_rec_manga_ONNX

PP-OCRv6 small rec — manga fine-tune

PaddlePaddle's PP-OCRv6 small text recogniser, fine-tuned on a manga corpus for Japanese manga lettering — vertical text, small kana, elongation marks, decorative symbols, stylised fonts — then interpolated back toward the base weights so it keeps its general Japanese OCR ability. Same architecture, input contract, dictionary and CTC decode as the stock model: a 21 MB drop-in replacement.

Results

Scored per bubble on 422 hand-transcribed manga speech bubbles, held out from training:

	stock PP-OCRv6 small rec	this model
Mean CER (strict)	0.0615	0.0402
Mean CER (lenient)	0.0449	0.0343
Bubbles read exactly	63.3 %	75.1 %

Downstream, the better transcriptions were worth +3.4 chrF++ through a Japanese→English manga translation model. Against larger whole-bubble OCR models (up to 30× the parameters), this 5.3 M-parameter model stays within a few thousandths of CER at a fraction of the compute.

Usage

• Input [N, 3, 48, W], RGB, height 48 with aspect preserved, normalised (x / 255 − 0.5) / 0.5.
• Output [N, T, 18710]: stock ppocrv6_dict.txt + space + CTC blank (index 0); greedy CTC decode.
• Recogniser only — pair it with a PP-OCR detector and feed it line crops.
• ONNX opset 13; Softmax axes set to −1 so it runs under ONNX Runtime's XNNPACK provider on Android.

SHA-256: c5cc5038a98c3df3e2d37de5716f603e2b0bcd3536c74078fdd91876a48a25ef

Limitations

Japanese only. Furigana is not suppressed by the model; drop ruby lines before recognition. Rare kanji outside the manga distribution and the ♥ glyph remain the most common residual errors.

License

Apache-2.0, as the base model.