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.gitattributes

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+data.tar.gz filter=lfs diff=lfs merge=lfs -text

.gitignore

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+env
+.idea

LADaS.py

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+import glob
+import os
+import yaml
+import datasets
+from PIL import Image
+
+
+_VERSION = "2024-06-04"
+_URL = f"https://github.com/DEFI-COLaF/LADaS/archive/refs/tags/{_VERSION}.tar.gz"
+_HOMEPAGE = "https://github.com/DEFI-COLaF/LADaS"
+_LICENSE = "CC BY 4.0"
+_CITATION = """\
+@misc{Clerice_Layout_Analysis_Dataset,
+    author = {Clérice, Thibault and Janès, Juliette and Scheithauer, Hugo and Bénière, Sarah and Langlais, Pierre-Carl and Romary, Laurent and Sagot, Benoit and Bougrelle, Roxane},
+    title = {{Layout Analysis Dataset with SegmOnto (LADaS)}},
+    url = {https://github.com/DEFI-COLaF/LADaS}
+}
+"""
+
+_CATEGORIES = ['AdvertisementZone', 'DigitizationArtefactZone', 'DropCapitalZone', 'FigureZone', 'FigureZone-FigDesc', 'FigureZone-Head', 'GraphicZone', 'GraphicZone-Decoration', 'GraphicZone-FigDesc', 'GraphicZone-Head', 'GraphicZone-Maths', 'GraphicZone-Part', 'GraphicZone-TextualContent', 'MainZone-Date', 'MainZone-Entry', 'MainZone-Entry-Continued', 'MainZone-Form', 'MainZone-Head', 'MainZone-Lg', 'MainZone-Lg-Continued', 'MainZone-List', 'MainZone-List-Continued', 'MainZone-Other', 'MainZone-P', 'MainZone-P-Continued', 'MainZone-Signature', 'MainZone-Sp', 'MainZone-Sp-Continued', 'MarginTextZone-ManuscriptAddendum', 'MarginTextZone-Notes', 'MarginTextZone-Notes-Continued', 'NumberingZone', 'PageTitleZone', 'PageTitleZone-Index', 'QuireMarkZone', 'RunningTitleZone', 'StampZone', 'StampZone-Sticker', 'TableZone', 'TableZone-Continued', 'TableZone-Head']
+
+
+class LadasConfig(datasets.BuilderConfig):
+    """Builder Config for LADaS"""
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+
+class LadasDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version(_VERSION.replace("-", "."))
+    BUILDER_CONFIGS = [
+        LadasConfig(
+            name="full",
+            description="Full version of the dataset"
+        )
+    ]
+
+    def _info(self) -> datasets.DatasetInfo:
+        features = datasets.Features({
+            "image_path": datasets.Value("string"),
+            "image": datasets.Image(),
+            # "width": datasets.Value("int32"),
+            # "height": datasets.Value("int32"),
+            "objects": datasets.Sequence(
+                {
+                    "bbox": datasets.Sequence(datasets.Value("float32"), length=4),
+                    "category": datasets.ClassLabel(names=_CATEGORIES),
+                }
+            )
+        })
+        return datasets.DatasetInfo(
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = _URL
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "local_dir": downloaded_files,
+                    "split": "train"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "local_dir": downloaded_files,
+                    "split": "valid"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "local_dir": downloaded_files,
+                    "split": "test"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, local_dir: str, split: str):
+
+        idx = 0
+
+        for file in glob.glob(os.path.join(local_dir, "*", "data", "*", split, "labels", "*.txt")):
+            objects = []
+            with open(file) as f:
+                for line in f:
+                    cls, *bbox = line.strip().split()
+                    objects.append({"category": _CATEGORIES[int(cls)], "bbox": list(map(float, bbox))})
+
+            image_path = os.path.normpath(file).split(os.sep)
+            image_path = os.path.join(*image_path[:-2], "images", image_path[-1].replace(".txt", ".jpg"))
+            if file.startswith("/") and not image_path.startswith("/"):
+                image_path = "/" + image_path
+
+            with open(image_path, "rb") as f:
+                image_bytes = f.read()
+                f.seek(0)
+
+            with Image.open(image_path) as im:
+                width, height = im.size
+
+            yield idx, {
+                "image_id": f"{image_path[-4]}/{image_path[-1]}",
+                "image": {"path": image_path, "bytes": image_bytes},
+                "width": width,
+                "height": height,
+                "objects": objects,
+            }
+            idx += 1

README.md

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+---
+task_categories:
+- object-detection
+license: cc-by-4.0
+pretty_name: LADaS
+size_categories:
+- 1K<n<10K
+---
+
+# LADaS: Layout Analysis Dataset with Segmonto
+