mayocream/koharu-yolo26s

Koharu YOLO26s

Koharu YOLO26s is a unified comic-page instance-segmentation model. It detects and segments four classes:

ID	Class
0	frame
1	dialogue_text
2	balloon
3	onomatopoeia_text

The model was fine-tuned from ShadowB/Manga109-panel-balloon-text-yolov26-segmentation using MangaSeg annotations and locally licensed Manga109 page images. The published repository contains no dataset images or annotations.

Files

• model.safetensors: inference state dictionary; this is the only weight file.
• yolo26s-seg.yaml: YOLO26s segmentation architecture.
• config.json: class names and recommended image size.
• export-manifest.json: weight checksum and conversion validation.

The SafeTensors export contains 844 tensors for 11,437,172 parameters. It was validated with strict state-dictionary loading and an exact forward comparison against the training checkpoint (max_abs_diff = 0).

Loading

import json
from pathlib import Path

from huggingface_hub import snapshot_download
from safetensors.torch import load_file
from ultralytics import YOLO

root = Path(
    snapshot_download(
        "mayocream/koharu-yolo26s",
        allow_patterns=["*.safetensors", "*.yaml", "*.json"],
    )
)
config = json.loads((root / "config.json").read_text())
model = YOLO(root / "yolo26s-seg.yaml", task="segment")
model.model.load_state_dict(load_file(root / "model.safetensors"), strict=True)
model.model.names = {int(key): value for key, value in config["names"].items()}

results = model.predict("page.jpg", imgsz=1280, conf=0.25)

The checkpoint intentionally is not distributed as a PyTorch pickle (.pt).

Evaluation

Evaluation used a held-out 1,539-page, book-disjoint test split.

Evaluation	Box mAP50	Box mAP50-95	Mask mAP50	Mask mAP50-95
Four classes	0.879	0.795	0.830	0.422
Shared three classes	0.975	0.923	0.946	0.492
Upstream checkpoint, shared classes	0.932	0.877	0.741	0.380

The largest shared-class improvement is dialogue-text segmentation. Balloon mask AP remained approximately equal to the upstream checkpoint. The new onomatopoeia class reached box mAP50-95 0.414 and mask mAP50-95 0.236.

Training

• Input size: 1280 pixels
• Epochs: 41
• Training images: 7,532
• Validation images: 1,531
• Test images: 1,539
• Optimizer: MuSGD
• Best epoch: 36
• Ultralytics: 8.4.43

Terms and attribution

This checkpoint is a derived research artifact. Use and redistribution must comply with the terms of Manga109, MangaSeg, COO, the upstream checkpoint, and Ultralytics. Review those terms before commercial use or redistribution.

• Manga109
• MangaSegmentation
• COO: Comic Onomatopoeia