initialize (#1)

* add files

* update

* update

* update

* add CI

* update files

* update

* update

* update

* update

* update

* update

* update

.github/workflows/ci.yaml

@@ -0,0 +1,49 @@
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+    paths-ignore:
+      - "README.md"
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.9", "3.10"]
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: |
+          pip install -U pip setuptools wheel poetry
+          poetry install
+
+      - name: Format
+        run: |
+          poetry run black --check .
+
+      - name: Lint
+        run: |
+          poetry run ruff .
+
+      - name: Type check
+        run: |
+          poetry run mypy . \
+            --ignore-missing-imports \
+            --no-strict-optional \
+            --no-site-packages \
+            --cache-dir=/dev/null
+
+      - name: Run tests
+        run: |
+          poetry run pytest --color=yes -rf

.github/workflows/push_to_hub.yaml

@@ -0,0 +1,26 @@
+name: Sync to Hugging Face Hub
+
+on:
+  workflow_run:
+    workflows:
+      - CI
+    branches:
+      - main
+    types:
+      - completed
+
+jobs:
+  push_to_hub:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Push to Huggingface hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_USERNAME: ${{ secrets.HF_USERNAME }}
+        run: |
+          git fetch --unshallow
+          git push --force https://${HF_USERNAME}:${HF_TOKEN}@huggingface.co/datasets/${HF_USERNAME}/Magazine main

.gitignore

@@ -0,0 +1,178 @@
+# Created by https://www.toptal.com/developers/gitignore/api/python
+# Edit at https://www.toptal.com/developers/gitignore?templates=python
+
+datasets
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+# ruff
+.ruff_cache/
+
+# LSP config files
+pyrightconfig.json
+
+# End of https://www.toptal.com/developers/gitignore/api/python

Magazine.py

@@ -0,0 +1,317 @@
+import os
+import pathlib
+import xml.etree.ElementTree as ET
+from dataclasses import asdict, dataclass
+from typing import Any, Dict, List, TypedDict
+
+from PIL import Image
+from PIL.Image import Image as PilImage
+
+import datasets as ds
+from datasets.utils.logging import get_logger
+
+logger = get_logger(__name__)
+
+JsonDict = Dict[str, Any]
+
+_DESCRIPTION = "A large-scale magazine layout dataset with fine-grained layout annotations and keyword labeling"
+
+_CITATION = """\
+@article{zheng2019content,
+  title={Content-aware generative modeling of graphic design layouts},
+  author={Zheng, Xinru and Qiao, Xiaotian and Cao, Ying and Lau, Rynson WH},
+  journal={ACM Transactions on Graphics (TOG)},
+  volume={38},
+  number={4},
+  pages={1--15},
+  year={2019},
+  publisher={ACM New York, NY, USA}
+}
+"""
+
+_HOMEPAGE = "https://xtqiao.com/projects/content_aware_layout/"
+
+_LICENSE = """\
+Copyright (c) 2019, Xiaotian Qiao
+All rights reserved.
+
+This code is copyrighted by the authors and is for non-commercial research
+purposes only.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+"""
+
+
+class URLs(TypedDict):
+    image: str
+    layout: str
+
+
+_URLS: URLs = {
+    # The author of this loading script has uploaded the image and layout annotation files to the HuggingFace's private repository to facilitate testing.
+    # If you are using this loading script, please download the annotations from the appropriate channels, such as the OneDrive link provided by the Magazine dataset's author.
+    # (To the author of Magazine dataset, if there are any issues regarding this matter, please contact us. We will address it promptly.)
+    "image": "https://huggingface.co/datasets/shunk031/Magazine-private/resolve/main/MagImage.zip",
+    "layout": "https://huggingface.co/datasets/shunk031/Magazine-private/resolve/main/MagLayout.zip",
+}
+
+
+@dataclass
+class LayoutSize(object):
+    width: int
+    height: int
+
+
+@dataclass
+class LayoutElement(object):
+    label: str
+    polygon_x: List[int]
+    polygon_y: List[int]
+
+    @classmethod
+    def parse_polygon(cls, polygon_str: str) -> List[float]:
+        return list(map(lambda x: float(x), polygon_str.split()))
+
+    @classmethod
+    def parse_polygons(cls, json_dict: JsonDict) -> JsonDict:
+        json_dict["polygon_x"] = cls.parse_polygon(json_dict["polygon_x"])
+        json_dict["polygon_y"] = cls.parse_polygon(json_dict["polygon_y"])
+        return json_dict
+
+    @classmethod
+    def from_dict(cls, json_dict: JsonDict) -> "LayoutElement":
+        json_dict = cls.parse_polygons(json_dict)
+        return cls(**json_dict)
+
+
+def get_filename(annotation: ET.Element) -> str:
+    filename = annotation.find("filename")
+    assert filename is not None
+    return filename.text
+
+
+def get_layout_category(annotation: ET.Element) -> str:
+    elem = annotation.find("category")
+    assert elem is not None
+    return elem.text
+
+
+def get_layout_size(annotation: ET.Element) -> LayoutSize:
+    size = annotation.find("size")
+    assert size is not None
+
+    h_elem = size.find("height")
+    assert h_elem is not None
+
+    w_elem = size.find("width")
+    assert w_elem is not None
+
+    return LayoutSize(width=int(w_elem.text), height=int(h_elem.text))
+
+
+def get_layout_elements(annotation: ET.Element) -> List[LayoutElement]:
+    layouts = annotation.find("layout")
+    assert layouts is not None
+
+    elements = layouts.findall("element")
+    layout_elements = [LayoutElement.from_dict(element.attrib) for element in elements]
+    return layout_elements
+
+
+def get_keywords(annotation: ET.Element) -> List[str]:
+    texts = annotation.find("text")
+    assert texts is not None
+    keywords = texts.findall("keyword")
+    return [keyword.text for keyword in keywords]
+
+
+def load_image(file_path: pathlib.Path) -> PilImage:
+    return Image.open(file_path)
+
+
+def load_images(
+    image_base_dir: pathlib.Path, category: str, filename: str
+) -> List[PilImage]:
+    image_files = (image_base_dir / category).glob(f"{filename}_*")
+    return [load_image(file_path) for file_path in image_files]
+
+
+@dataclass
+class LayoutAnnotation(object):
+    filename: str
+    category: str
+    size: LayoutSize
+    elements: List[LayoutElement]
+    keywords: List[str]
+    images: List[PilImage]
+
+    @classmethod
+    def get_annotation_from_xml(cls, xml_file: pathlib.Path) -> ET.Element:
+        tree = ET.parse(xml_file)
+        return tree.getroot()
+
+    @classmethod
+    def from_xml(
+        cls, xml_file: pathlib.Path, image_base_dir: pathlib.Path
+    ) -> "LayoutAnnotation":
+        annotation = cls.get_annotation_from_xml(xml_file)
+        filename = get_filename(
+            annotation=annotation,
+        )
+        category = get_layout_category(
+            annotation=annotation,
+        )
+        layout_size = get_layout_size(
+            annotation=annotation,
+        )
+        layout_elements = get_layout_elements(
+            annotation=annotation,
+        )
+        keywords = get_keywords(
+            annotation=annotation,
+        )
+        images = load_images(
+            image_base_dir=image_base_dir,
+            category=category,
+            filename=filename,
+        )
+        return cls(
+            filename=filename,
+            category=category,
+            size=layout_size,
+            elements=layout_elements,
+            keywords=keywords,
+            images=images,
+        )
+
+
+class MagazineDataset(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("1.0.0")
+    BUILDER_CONFIGS = [ds.BuilderConfig(version=VERSION, description=_DESCRIPTION)]
+
+    @property
+    def _manual_download_instructions(self) -> str:
+        return (
+            "To use Magazine dataset, you need to download the annotations "
+            "from the OneDrive in the official webpage "
+            "(https://portland-my.sharepoint.com/:f:/g/personal/xqiao6-c_my_cityu_edu_hk/EhmRh5SFoQ9Hjl_aRjCOltkBKFYefiSagR6QLJ7pWvs3Ww?e=y8HO5Q)."
+        )
+
+    def _info(self) -> ds.DatasetInfo:
+        features = ds.Features(
+            {
+                "filename": ds.Value("string"),
+                "category": ds.ClassLabel(
+                    num_classes=6,
+                    names=["fashion", "food", "news", "science", "travel", "wedding"],
+                ),
+                "size": {
+                    "width": ds.Value("int64"),
+                    "height": ds.Value("int64"),
+                },
+                "elements": ds.Sequence(
+                    {
+                        "label": ds.ClassLabel(
+                            num_classes=5,
+                            names=[
+                                "text",
+                                "image",
+                                "headline",
+                                "text-over-image",
+                                "headline-over-image",
+                            ],
+                        ),
+                        "polygon_x": ds.Sequence(ds.Value("float32")),
+                        "polygon_y": ds.Sequence(ds.Value("float32")),
+                    }
+                ),
+                "keywords": ds.Sequence(ds.Value("string")),
+                "images": ds.Sequence(ds.Image()),
+            }
+        )
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            features=features,
+        )
+
+    def _download_from_hf(self, dl_manager: ds.DownloadManager) -> URLs:
+        return dl_manager.download_and_extract(_URLS)
+
+    def _download_from_local(self, dl_manager: ds.DownloadManager) -> URLs:
+        assert dl_manager.manual_dir is not None, dl_manager.manual_dir
+        dir_path = os.path.expanduser(dl_manager.manual_dir)
+
+        image_zip_path = os.path.join(dir_path, "MagImage.zip")
+        layout_zip_path = os.path.join(dir_path, "MagLayout.zip")
+
+        if (
+            not os.path.exists(dir_path)
+            or not os.path.exists(image_zip_path)
+            or not os.path.exists(layout_zip_path)
+        ):
+            raise FileNotFoundError(
+                "Make sure you have downloaded and placed the `MagImage.zip` and `MagLayout.zip` correctly. "
+                'Furthermore, you should check that a manual dir via `datasets.load_dataset("shunk031/Magazine", data_dir=...)` '
+                "that includes zip files from the downloaded files. "
+                f"Manual downloaded instructions: {self._manual_download_instructions}"
+            )
+        return dl_manager.extract(
+            path_or_paths={
+                "image": image_zip_path,
+                "layout": layout_zip_path,
+            }
+        )
+
+    def _split_generators(self, dl_manager: ds.DownloadManager):
+        file_paths = (
+            self._download_from_hf(dl_manager)
+            if dl_manager.download_config.token
+            else self._download_from_local(dl_manager)
+        )
+        layout_xml_dir = (
+            pathlib.Path(file_paths["layout"]) / "layoutdata" / "annotations"
+        )
+        image_base_dir = pathlib.Path(file_paths["image"]) / "images"
+
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={
+                    "layout_xml_dir": layout_xml_dir,
+                    "image_base_dir": image_base_dir,
+                },
+            )
+        ]
+
+    def _generate_examples(
+        self, layout_xml_dir: pathlib.Path, image_base_dir: pathlib.Path
+    ):
+        xml_files = [f for f in layout_xml_dir.iterdir() if f.suffix == ".xml"]
+        for i, xml_file in enumerate(xml_files):
+            layout_annotation = LayoutAnnotation.from_xml(
+                xml_file=xml_file,
+                image_base_dir=image_base_dir,
+            )
+            yield i, asdict(layout_annotation)

README.md

@@ -0,0 +1,182 @@
+---
+annotations_creators:
+- machine-generated
+language:
+- en
+language_creators:
+- found
+license:
+- unknown
+multilinguality:
+- monolingual
+pretty_name: Magazine
+size_categories: []
+source_datasets:
+- original
+tags:
+- graphic design
+- layout
+- content-aware
+task_categories:
+- image-to-image
+- text-to-image
+- unconditional-image-generation
+task_ids: []
+---
+
+# Dataset Card for Magazine dataset
+
+## Table of Contents
+- [Dataset Card Creation Guide](#dataset-card-creation-guide)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+    - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://xtqiao.com/projects/content_aware_layout/
+- **Repository:** https://github.com/shunk031/huggingface-datasets_Magazine
+- **Paper (SIGGRAPH2019):** https://dl.acm.org/doi/10.1145/3306346.3322971
+
+### Dataset Summary
+
+A large-scale magazine layout dataset with fine-grained layout annotations and keyword labeling.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+To use Magazine dataset, you need to download the image and layout annotations from the [OneDrive](https://portland-my.sharepoint.com/:f:/g/personal/xqiao6-c_my_cityu_edu_hk/EhmRh5SFoQ9Hjl_aRjCOltkBKFYefiSagR6QLJ7pWvs3Ww?e=y8HO5Q) in the official page. 
+Then place the downloaded files in the following structure and specify its path.
+
+```shell
+/path/to/datasets
+├── MagImage.zip
+└── MagLayout.zip
+```
+
+```python
+import datasets as ds
+
+dataset = ds.load_dataset(
+    path="shunk031/Magazine",
+    data_dir="/path/to/datasets/", # Specify the path of the downloaded directory.
+)
+```
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+```bibtex
+@article{zheng2019content,
+  title={Content-aware generative modeling of graphic design layouts},
+  author={Zheng, Xinru and Qiao, Xiaotian and Cao, Ying and Lau, Rynson WH},
+  journal={ACM Transactions on Graphics (TOG)},
+  volume={38},
+  number={4},
+  pages={1--15},
+  year={2019},
+  publisher={ACM New York, NY, USA}
+}
+```
+
+### Contributions
+
+Thanks to [Xinru Zheng and Xiaotian Qiao*](https://xtqiao.com/projects/content_aware_layout/) for creating this dataset.

pyproject.toml

@@ -0,0 +1,21 @@
+[tool.poetry]
+name = "huggingface-datasets-magazine"
+version = "0.1.0"
+description = ""
+authors = ["Shunsuke KITADA <shunsuke.kitada.0831@gmail.com>"]
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = "^3.9"
+datasets = {extras = ["vision"], version = "^2.14.6"}
+
+
+[tool.poetry.group.dev.dependencies]
+ruff = "^0.1.3"
+black = "^23.10.1"
+mypy = "^1.6.1"
+pytest = "^7.4.3"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

tests/Magazine_test.py

@@ -0,0 +1,27 @@
+import os
+
+import pytest
+
+import datasets as ds
+
+
+@pytest.fixture
+def dataset_path() -> str:
+    return "Magazine.py"
+
+
+@pytest.mark.skipif(
+    condition=bool(os.environ.get("CI", False)),
+    reason=(
+        "Because this loading script downloads a large dataset, "
+        "we will skip running it on CI."
+    ),
+)
+@pytest.mark.parametrize(
+    argnames=("expected_num_dataset",),
+    argvalues=((3919,),),
+)
+def test_load_dataset(dataset_path: str, expected_num_dataset: int):
+    dataset = ds.load_dataset(path=dataset_path, token=True)
+
+    assert dataset["train"].num_rows == expected_num_dataset