The repository as a whole is labelled GPL-3.0, the stricter of the two licenses.
Apache-2.0 is one-way compatible with GPL-3.0, so redistributing them together is fine.
What was changed
Only the manga-ocr encoder/decoder are modified: int8 dynamic quantisation of
MatMul ops only. The detector is byte-identical to upstream.
Quantising Conv too would emit ConvInteger, which the ONNX Runtime CPU
execution provider does not implement — the model then fails to load. The ViT
patch-embedding convolution is negligible in FLOPs anyway, so nothing is lost.
Measured on a Pixel 6, 4 threads, single text region:
fp32
int8
5 tokens
550 ms
184 ms
14 tokens
640 ms
240 ms
25 tokens
900 ms
380 ms
Recognition output is character-for-character identical to fp32 (verified on
both desktop and device), while the two files shrink from 461 MB to 133 MB.
Model I/O
comic-text-detector
in images [1,3,1024,1024] float, RGB, 0-1
out blk [1,64512,7] YOLOv5 head, decoded in-graph: cx,cy,w,h,obj,cls0,cls1
seg [1,1,1024,1024] (unused)
det [1,2,1024,1024] (unused)
manga-ocr encoder
in pixel_values [1,3,224,224] -> out last_hidden_state [1,197,768]
manga-ocr decoder
in input_ids [1,L] + encoder_hidden_states [1,197,768] -> out logits [1,L,6144]
start token 2, eos 3; preprocessing is greyscale, mean=std=0.5
Note manga-ocr's known behaviour: it hallucinates plausible Japanese for regions
that contain no text, so only feed it crops produced by the detector.
