README.md

metadata

license: cc-by-nc-4.0
task_categories:
  - object-detection
language:
  - ja
tags:
  - manga
  - speech-bubble
  - comics
  - yolo
  - computer-vision
  - object-detection
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: images/train/*.jpg
      - split: validation
        path: images/val/*.jpg
      - split: test
        path: images/test/*.jpg

Manga Speech Bubble Detection Dataset

Dataset for detecting speech bubble locations in manga pages.
2 671 images — 1 class: location-of-bubbles.

Dataset Structure

Split	Images	Labels
train	2 056	2 056
val	404	404
test	211	211

images/
  train/   # 2056 × .jpg
  val/     # 404  × .jpg
  test/    # 211  × .jpg
labels/    # YOLO .txt, mirrors images/
dataset.yaml
manga_bubbles_detect.py   # HF loading script

Annotation Format

YOLO — each .txt contains one row per bounding box:

<class_id> <cx> <cy> <w> <h>   # normalized [0..1], class 0 = location-of-bubbles

When loaded via load_dataset() the script converts bboxes to COCO format (absolute pixels [x_min, y_min, width, height]) and also exposes the raw YOLO values in bbox_yolo.

Usage

from datasets import load_dataset

ds = load_dataset("PSImera/manga_bubbles_detect")

sample = ds["train"][0]
print(sample["image_id"])          # e.g. "img_000001"
print(sample["width"], sample["height"])
for obj in sample["objects"]:
    print(obj["category"], obj["bbox"])   # [x_min, y_min, w, h] absolute px

Sources

1. Roboflow — manga-6puie (pre-labeled)
2. Google Drive / ikefir34/DLS_Manga_Translator — Drive · GitHub (labeled manually in CVAT)

License

CC BY-NC 4.0 — non-commercial use only.

The underlying manga images remain the intellectual property of their respective publishers. This dataset is intended solely for academic research and non-commercial purposes. Do not use for commercial applications without obtaining rights from the original copyright holders.