Update parquet files

.gitignore

@@ -1,4 +0,0 @@
-env
-.idea
-*.json
-*.arrow

README.md

@@ -1,11 +0,0 @@
----
-task_categories:
-- object-detection
-license: cc-by-4.0
-pretty_name: LADaS
-size_categories:
-- 1K<n<10K
----
-
-# LADaS: Layout Analysis Dataset with Segmonto
-

build.py

@@ -1,50 +0,0 @@
-import os
-from datasets import load_dataset
-from datasets import config
-from datasets.utils.py_utils import convert_file_size_to_int
-from datasets.table import embed_table_storage
-from tqdm import tqdm
-
-
-def build_parquet(split):
-    # Source: https://discuss.huggingface.co/t/how-to-save-audio-dataset-with-parquet-format-on-disk/66179
-    dataset = load_dataset("./src/LADaS.py", split=split, trust_remote_code=True)
-    max_shard_size = '500MB'
-
-    dataset_nbytes = dataset._estimate_nbytes()
-    max_shard_size = convert_file_size_to_int(max_shard_size or config.MAX_SHARD_SIZE)
-    num_shards = int(dataset_nbytes / max_shard_size) + 1
-    num_shards = max(num_shards, 1)
-    shards = (dataset.shard(num_shards=num_shards, index=i, contiguous=True) for i in range(num_shards))
-
-    def shards_with_embedded_external_files(shards):
-        for shard in shards:
-            format = shard.format
-            shard = shard.with_format("arrow")
-            shard = shard.map(
-                embed_table_storage,
-                batched=True,
-                batch_size=1000,
-                keep_in_memory=True,
-            )
-            shard = shard.with_format(**format)
-            yield shard
-
-    shards = shards_with_embedded_external_files(shards)
-
-    os.makedirs("data", exist_ok=True)
-
-    for index, shard in tqdm(
-        enumerate(shards),
-        desc="Save the dataset shards",
-        total=num_shards,
-    ):
-        shard_path = f"data/{split}-{index:05d}-of-{num_shards:05d}.parquet"
-        shard.to_parquet(shard_path)
-
-
-if __name__ == "__main__":
-    build_parquet("train")
-    build_parquet("validation")
-    build_parquet("test")
-

src/LADaS.py

@@ -1,125 +0,0 @@
-import glob
-import os
-from typing import List, Any
-
-import yaml
-import datasets
-from PIL import Image
-
-
-_VERSION = "2024-07-17"
-_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 Romary, Laurent and Sagot, Benoit and Bougrelle, Roxane},
-    title = {{Layout Analysis Dataset with SegmOnto (LADaS)}},
-    url = {https://github.com/DEFI-COLaF/LADaS}
-}
-"""
-
-_CATEGORIES: list[str] = ["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", "TitlePageZone", "TitlePageZone-Index", "QuireMarksZone", "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()
-
-            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