| --- |
| pretty_name: Manga109 Segmentation |
| license: other |
| language: |
| - ja |
| task_categories: |
| - image-segmentation |
| - object-detection |
| size_categories: |
| - 10K<n<100K |
| tags: |
| - manga |
| - comics |
| - layout-analysis |
| - instance-segmentation |
| - text-detection |
| - reading-order |
| --- |
| |
| # Manga109 Segmentation |
|
|
| Manga109 Segmentation is an **annotation-only** dataset for manga layout and |
| instance segmentation. The current release is **v2.0.0**. It contains COCO RLE |
| masks for `text`, `onomatopoeia`, `bubble`, and `panel`, plus containment |
| relations and Japanese transcriptions where available. |
|
|
| > **Manga109 images are not included.** Obtain Manga109 separately and follow |
| > its terms. Every `images[].file_name` is relative to the Manga109 `images/` |
| > directory. |
| |
| ## What changed in v2.0.0 |
| |
| This is a breaking supervision update intended for standard RF-DETR-style |
| instance-segmentation training: |
| |
| - Text masks on 449 pages use the manually painted Zenodo Manga109 text-mask |
| dataset as the highest-priority pixel source. |
| - The remaining pages use |
| [`mayocream/koharu-text-sam-ts-l`](https://huggingface.co/mayocream/koharu-text-sam-ts-l) |
| to refine text/COO pixels inside authoritative human geometry. |
| - Good existing text masks are unioned with clipped teacher ink. Filled |
| box/polygon fallbacks are replaced when the teacher has sufficient support. |
| - PP-DocLayoutV3 is used **only for bounding-box proposals**. For the 3,372 |
| accepted train-only pseudo instances, the mask is always TextSeg ink clipped |
| to the proposal; the stored box is tightened to the resulting mask. |
| - 504 pages with materially incomplete positive labels were removed so their |
| unlabeled text cannot become false-negative COCO background. This includes |
| 102 `000.jpg` cover pages. |
| - All 454,606 published annotations have `iscrowd: 0`. No custom dense head, |
| ignore-region encoding, or synthetic negative-mask class is required. |
| |
| The previous release remains available at the immutable `v1.1.0` tag. |
| |
| ## Dataset summary |
| |
| The split remains book-disjoint. Filtering removes pages, not books. |
| |
| | Split | Books | Pages | Text | COO | Bubbles | Panels | All annotations | |
| |---|---:|---:|---:|---:|---:|---:|---:| |
| | Train | 87 | 8,128 | 129,608 | 45,165 | 102,088 | 81,638 | 358,499 | |
| | Validation | 11 | 1,001 | 15,877 | 7,395 | 13,784 | 11,157 | 48,213 | |
| | Test | 11 | 969 | 16,826 | 6,388 | 13,835 | 10,845 | 47,894 | |
| | **Total** | **109** | **10,098** | **162,311** | **58,948** | **129,707** | **103,640** | **454,606** | |
| |
| The annotations contain 355,817 geometric containment relations. The three |
| `review/*.jsonl` files contain sanitized per-page diagnostics for all 10,602 |
| candidate pages, including the 504 excluded pages; they are not training |
| annotations. |
| |
| ## Package layout |
| |
| ```text |
| manga109-segmentation/ |
| ├── annotations/ |
| │ ├── train.coco.json |
| │ ├── validation.coco.json |
| │ └── test.coco.json |
| ├── review/ |
| │ ├── train.jsonl |
| │ ├── validation.jsonl |
| │ └── test.jsonl |
| ├── build.json |
| ├── checksums.sha256 |
| └── package_manifest.json |
| ``` |
| |
| Use the relative image paths with a separately obtained Manga109 release: |
| |
| ```python |
| import json |
| from pathlib import Path |
|
|
| dataset_root = Path("manga109-segmentation") |
| image_root = Path("Manga109_released_2026_05_21/images") |
|
|
| with (dataset_root / "annotations/train.coco.json").open(encoding="utf-8") as f: |
| coco = json.load(f) |
| |
| image_path = image_root / coco["images"][0]["file_name"] |
| ``` |
| |
| Masks use compressed COCO RLE. `bbox` is COCO `[x, y, width, height]`, `area` |
| is the mask-pixel count, and every annotation uses `iscrowd: 0`. |
| |
| ## Categories and relations |
| |
| | ID | Category | |
| |---:|---| |
| | 1 | `text` | |
| | 2 | `onomatopoeia` | |
| | 3 | `bubble` | |
| | 4 | `panel` | |
| |
| The top-level `relations` array records `contained_by_bubble` and |
| `contained_by_panel` geometry. Image and bubble reading-order fields are |
| heuristic hints, not human reading-order ground truth. |
| |
| ## Mask provenance |
| |
| `attributes.quality_tier` gives the direct training provenance: |
|
|
| - `gold_mangaseg`: retained MangaSegmentation bubble/panel mask. |
| - `gold_zenodo_refined`: human-geometry instance refined with manually painted |
| Zenodo text-mask pixels. |
| - `silver_textseg_refined`: human-geometry instance refined with TextSeg. |
| - `silver_pp_bbox_textseg_mask`: PP-DocLayoutV3 proposal whose pixels come from |
| TextSeg; used only in train. |
|
|
| Counts by split are recorded in `build.json`. Detailed page-level agreement, |
| teacher coverage, proposal boxes, exclusion reasons, and visual-review flags |
| are in `review/*.jsonl` without local filesystem paths. |
|
|
| ## Page filtering and negative supervision |
|
|
| A page is excluded when it has no target typography but at least 512 teacher |
| foreground pixels, or when it has at least 10,000 teacher pixels and final |
| recall below 0.20. The two tests may overlap. |
|
|
| Seven retained pages have no typography instances and a near-empty teacher |
| mask (at most 382 pixels). They provide safe implicit background supervision. |
| There is deliberately no `negative` segmentation category: ordinary COCO |
| background is the negative signal, while incomplete pages are omitted. |
|
|
| ## Limitations |
|
|
| - Most text/COO instance identities and envelopes are human-authored, but many |
| final pixel masks are model-assisted. |
| - PP-DocLayoutV3 can introduce class/proposal errors in the 3,372 train-only |
| pseudo instances, even though TextSeg supplies their pixels. |
| - Validation and test include teacher-refined pixels, so use independent human |
| or Zenodo evaluation when measuring absolute mask quality. |
| - Bubble/panel masks inherit MangaSegmentation ambiguity and source errors. |
| - Relations and reading order are geometric heuristics. |
| - Manga109 images and their usage rights are not distributed here. |
|
|
| ## License and sources |
|
|
| `license: other` is intentional because the package combines derived |
| annotations from multiple sources. Users must follow every upstream license |
| and attribution requirement. In particular: |
|
|
| - [Manga109 and Manga109-v2026](https://manga109.github.io/manga109-project-website/en/) |
| - [MangaSegmentation](https://huggingface.co/datasets/MS92/MangaSegmentation) |
| - [COO: Comic Onomatopoeia Dataset](https://github.com/ku21fan/COO-Comic-Onomatopoeia) |
| - [Zenodo Manga text-mask dataset](https://doi.org/10.5281/zenodo.4511796) |
| (CC BY 4.0) |
| - [`mayocream/koharu-text-sam-ts-l`](https://huggingface.co/mayocream/koharu-text-sam-ts-l) |
| - [`PaddlePaddle/PP-DocLayoutV3_safetensors`](https://huggingface.co/PaddlePaddle/PP-DocLayoutV3_safetensors) |
|
|
| The package does not grant access to or a license for Manga109 images. Never |
| upload the Manga109 image files with this repository. Exact source revisions, |
| policy thresholds, split counts, and quality-tier counts are in `build.json`; |
| file integrity is recorded in `checksums.sha256`. |
|
|
