Initialize (#1)

* add files

* update

* add CI settings

* add settings for CI

* update README

* update

* update

* update

.github/workflows/ci.yaml

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+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

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+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}/PKU-PosterLayout main

.gitignore

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+# Created by https://www.toptal.com/developers/gitignore/api/python
+# Edit at https://www.toptal.com/developers/gitignore?templates=python
+
+### 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

PKU-PosterLayout.py

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+import os
+import pathlib
+from typing import List, TypedDict, Union, cast
+
+import datasets as ds
+from datasets.utils.logging import get_logger
+from PIL import Image
+from PIL.Image import Image as PilImage
+
+logger = get_logger(__name__)
+
+_DESCRIPTION = (
+    "A New Dataset and Benchmark for Content-aware Visual-Textual Presentation Layout"
+)
+
+_CITATION = """\
+@inproceedings{hsu2023posterlayout,
+  title={PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout},
+  author={Hsu, Hsiao Yuan and He, Xiangteng and Peng, Yuxin and Kong, Hao and Zhang, Qing},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+  pages={6018--6026},
+  year={2023}
+}
+"""
+
+_HOMEPAGE = "http://59.108.48.34/tiki/PosterLayout/"
+
+_LICENSE = "Images in PKU PosterLayout are distributed under the CC BY-SA 4.0 license."
+
+
+class TrainPoster(TypedDict):
+    original: str
+    inpainted: str
+
+
+class TestPoster(TypedDict):
+    canvas: str
+
+
+class SaliencyMaps(TypedDict):
+    pfpn: str
+    basnet: str
+
+
+class TrainDataset(TypedDict):
+    poster: TrainPoster
+    saliency_maps: SaliencyMaps
+
+
+class TestDataset(TypedDict):
+    poster: TestPoster
+    saliency_maps: SaliencyMaps
+
+
+class DatasetUrls(TypedDict):
+    train: TrainDataset
+    test: TestDataset
+
+
+# The author of this loading script has uploaded the poster image and saliency maps 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.)
+_URLS: DatasetUrls = {
+    "train": {
+        "poster": {
+            "original": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/train/original_poster.zip",
+            "inpainted": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/train/inpainted_poster.zip",
+        },
+        "saliency_maps": {
+            "pfpn": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/train/saliencymaps_pfpn.zip",
+            "basnet": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/train/saliencymaps_basnet.zip",
+        },
+    },
+    "test": {
+        "poster": {
+            "canvas": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/test/image_canvas.zip",
+        },
+        "saliency_maps": {
+            "pfpn": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/test/saliencymaps_pfpn.zip",
+            "basnet": "https://huggingface.co/datasets/shunk031/PKU-PosterLayout-private/resolve/main/test/saliencymaps_basnet.zip",
+        },
+    },
+}
+
+
+def file_sorter(f: pathlib.Path) -> int:
+    idx, *_ = f.stem.split("_")
+    return int(idx)
+
+
+def load_image(file_path: pathlib.Path) -> PilImage:
+    logger.info(f"Load from {file_path}")
+    return Image.open(file_path)
+
+
+def get_original_poster_files(base_dir: str) -> List[pathlib.Path]:
+    poster_dir = pathlib.Path(base_dir) / "original_poster"
+    return sorted(poster_dir.iterdir(), key=lambda f: int(f.stem))
+
+
+def get_inpainted_poster_files(base_dir: str) -> List[pathlib.Path]:
+    inpainted_dir = pathlib.Path(base_dir) / "inpainted_poster"
+    return sorted(inpainted_dir.iterdir(), key=file_sorter)
+
+
+def get_basnet_map_files(base_dir: str) -> List[pathlib.Path]:
+    basnet_map_dir = pathlib.Path(base_dir) / "saliencymaps_basnet"
+    return sorted(basnet_map_dir.iterdir(), key=file_sorter)
+
+
+def get_pfpn_map_files(base_dir: str) -> List[pathlib.Path]:
+    pfpn_map_dir = pathlib.Path(base_dir) / "saliencymaps_pfpn"
+    return sorted(pfpn_map_dir.iterdir(), key=file_sorter)
+
+
+def get_canvas_files(base_dir: str) -> List[pathlib.Path]:
+    canvas_dir = pathlib.Path(base_dir) / "image_canvas"
+    return sorted(canvas_dir.iterdir(), key=lambda f: int(f.stem))
+
+
+class PosterLayoutDataset(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("1.0.0")
+    BUILDER_CONFIGS = [ds.BuilderConfig(version=VERSION)]
+
+    def _info(self) -> ds.DatasetInfo:
+        features = ds.Features(
+            {
+                "original_poster": ds.Image(),
+                "inpainted_poster": ds.Image(),
+                "basnet_saliency_map": ds.Image(),
+                "pfpn_saliency_map": ds.Image(),
+                "canvas": ds.Image(),
+            }
+        )
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            features=features,
+        )
+
+    @property
+    def _manual_download_instructions(self) -> str:
+        return (
+            "To use PKU-PosterLayout dataset, you need to download the poster image "
+            "and saliency maps via [PKU Netdisk](https://disk.pku.edu.cn/link/999C6E97BB354DF8AD0F9E1F9003BE05) "
+            "or [Google Drive](https://drive.google.com/drive/folders/1Gk202RVs9Qy2zbJUNeurC1CaQYNU-Vuv?usp=share_link)."
+        )
+
+    def _download_from_hf(self, dl_manager: ds.DownloadManager) -> DatasetUrls:
+        return dl_manager.download_and_extract(_URLS)
+
+    def _download_from_local(self, dl_manager: ds.DownloadManager) -> DatasetUrls:
+        assert dl_manager.manual_dir is not None, dl_manager.manual_dir
+        dir_path = os.path.expanduser(dl_manager.manual_dir)
+
+        tng_dir_path = os.path.join(dir_path, "train")
+        tst_dir_path = os.path.join(dir_path, "test")
+
+        if not os.path.exists(dir_path):
+            raise FileNotFoundError(
+                "Make sure you have downloaded and placed the PKU-PosterLayout dataset correctly. "
+                'Furthermore, you shoud check that a manual dir via `datasets.load_dataset("shunk031/PKU-PosterLayout", data_dir=...)` '
+                "that include zip files from the downloaded files. "
+                f"Manual downloaded instructions: {self._manual_download_instructions}"
+            )
+        return dl_manager.extract(
+            path_or_paths={
+                "train": {
+                    "poster": {
+                        "original": os.path.join(tng_dir_path, "inpainted_poster.zip"),
+                        "inpainted": os.path.join(tng_dir_path, "inpainted_poster.zip"),
+                    },
+                    "saliency_maps": {
+                        "pfpn": os.path.join(tng_dir_path, "saliencymaps_pfpn.zip"),
+                        "basnet": os.path.join(tng_dir_path, "saliencymaps_basnet.zip"),
+                    },
+                },
+                "test": {
+                    "poster": {
+                        "canvas": os.path.join(tst_dir_path, "image_canvas.zip"),
+                    },
+                    "saliency_maps": {
+                        "pfpn": os.path.join(tst_dir_path, "salieycmaps_pfpn.zip"),
+                        "basnet": os.path.join(tst_dir_path, "saliencymaps_basnet.zip"),
+                    },
+                },
+            }
+        )
+
+    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)
+        )
+
+        tng_files = file_paths["train"]
+        tst_files = file_paths["test"]
+
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={
+                    "poster": tng_files["poster"],
+                    "saliency_maps": tng_files["saliency_maps"],
+                },
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.TEST,
+                gen_kwargs={
+                    "poster": tst_files["poster"],
+                    "saliency_maps": tst_files["saliency_maps"],
+                },
+            ),
+        ]
+
+    def _generate_train_examples(
+        self, poster: TrainPoster, saliency_maps: SaliencyMaps
+    ):
+        poster_files = get_original_poster_files(base_dir=poster["original"])
+        inpainted_files = get_inpainted_poster_files(base_dir=poster["inpainted"])
+
+        basnet_map_files = get_basnet_map_files(base_dir=saliency_maps["basnet"])
+        pfpn_map_files = get_pfpn_map_files(base_dir=saliency_maps["pfpn"])
+
+        assert (
+            len(poster_files)
+            == len(inpainted_files)
+            == len(basnet_map_files)
+            == len(pfpn_map_files)
+        )
+
+        it = zip(poster_files, inpainted_files, basnet_map_files, pfpn_map_files)
+        for i, (
+            original_poster_path,
+            inpainted_poster_path,
+            basnet_map_path,
+            pfpn_map_path,
+        ) in enumerate(it):
+            yield i, {
+                "original_poster": load_image(original_poster_path),
+                "inpainted_poster": load_image(inpainted_poster_path),
+                "basnet_saliency_map": load_image(basnet_map_path),
+                "pfpn_saliency_map": load_image(pfpn_map_path),
+                "canvas": None,
+            }
+
+    def _generate_test_examples(self, poster: TestPoster, saliency_maps: SaliencyMaps):
+        canvas_files = get_canvas_files(base_dir=poster["canvas"])
+
+        basnet_map_files = get_basnet_map_files(base_dir=saliency_maps["basnet"])
+        pfpn_map_files = get_pfpn_map_files(base_dir=saliency_maps["pfpn"])
+
+        assert len(canvas_files) == len(basnet_map_files) == len(pfpn_map_files)
+        it = zip(canvas_files, basnet_map_files, pfpn_map_files)
+        for i, (canvas_path, basnet_map_path, pfpn_map_path) in enumerate(it):
+            yield i, {
+                "original_poster": None,
+                "inpainted_poster": None,
+                "basnet_saliency_map": load_image(basnet_map_path),
+                "pfpn_saliency_map": load_image(pfpn_map_path),
+                "canvas": load_image(canvas_path),
+            }
+
+    def _generate_examples(
+        self, poster: Union[TrainPoster, TestPoster], saliency_maps: SaliencyMaps
+    ):
+        if "original" in poster and "inpainted" in poster:
+            yield from self._generate_train_examples(
+                poster=cast(TrainPoster, poster), saliency_maps=saliency_maps
+            )
+        elif "canvas" in poster:
+            yield from self._generate_test_examples(
+                poster=cast(TestPoster, poster), saliency_maps=saliency_maps
+            )
+        else:
+            raise ValueError("Invalid dataset")

README.md

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+---
+annotations_creators:
+- expert-generated
+language:
+- zh
+language_creators:
+- found
+license:
+- cc-by-sa-4.0
+multilinguality: []
+pretty_name: PKU-PosterLayout
+size_categories: []
+source_datasets:
+- extended
+tags:
+- layout-generation
+task_categories:
+- other
+task_ids: []
+---
+
+# Dataset Card for PKU-PosterLayout
+
+[![CI](https://github.com/shunk031/huggingface-datasets_PKU-PosterLayout/actions/workflows/ci.yaml/badge.svg)](https://github.com/shunk031/huggingface-datasets_PKU-PosterLayout/actions/workflows/ci.yaml)
+
+## 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:** http://59.108.48.34/tiki/PosterLayout/
+- **Repository:** https://github.com/shunk031/huggingface-datasets_PKU-PosterLayout
+- **Paper (Preprint):** https://arxiv.org/abs/2303.15937
+- **Paper (CVPR2023):** https://openaccess.thecvf.com/content/CVPR2023/html/Hsu_PosterLayout_A_New_Benchmark_and_Approach_for_Content-Aware_Visual-Textual_Presentation_CVPR_2023_paper.html
+
+### Dataset Summary
+
+PKU-PosterLayout is a new dataset and benchmark for content-aware visual-textual presentation layout.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+The language data in PKU-PosterLayout is in Chinese ([BCP-47 zh](https://www.rfc-editor.org/info/bcp47)).
+
+## Dataset Structure
+
+### Data Instances
+
+To use PKU-PosterLayout dataset, you need to download the poster image and saliency maps via [PKU Netdisk](https://disk.pku.edu.cn/link/999C6E97BB354DF8AD0F9E1F9003BE05) or [Google Drive](https://drive.google.com/drive/folders/1Gk202RVs9Qy2zbJUNeurC1CaQYNU-Vuv?usp=share_link).
+
+```
+/path/to/datasets
+├── train
+│   ├── inpainted_poster.zip
+│   ├── original_poster.zip
+│   ├── saliencymaps_basnet.zip
+│   └── saliencymaps_pfpn.zip
+└── test
+    ├── image_canvas.zip
+    ├── saliencymaps_basnet.zip
+    └── saliencymaps_pfpn.zip
+```
+
+```python
+import datasets as ds
+
+dataset = ds.load_dataset(
+    path="shunk031/PKU-PosterLayout",
+    data_dir="/path/to/datasets/",
+)
+```
+
+### 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
+@inproceedings{hsu2023posterlayout,
+  title={PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout},
+  author={Hsu, Hsiao Yuan and He, Xiangteng and Peng, Yuxin and Kong, Hao and Zhang, Qing},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+  pages={6018--6026},
+  year={2023}
+}
+```
+
+### Contributions
+
+Thanks to [@PKU-ICST-MIPL](https://github.com/PKU-ICST-MIPL) for creating this dataset.

pyproject.toml

@@ -0,0 +1,21 @@
+[tool.poetry]
+name = "huggingface-datasets-posterlayout"
+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/PKU-PosterLayout_test.py

@@ -0,0 +1,30 @@
+import os
+
+import datasets as ds
+import pytest
+
+
+@pytest.fixture
+def dataset_path() -> str:
+    return "PKU-PosterLayout.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_train",
+        "expected_num_test",
+    ),
+    argvalues=((9974, 905),),
+)
+def test_load_dataset(dataset_path: str, expected_num_train: int, expected_num_test):
+    dataset = ds.load_dataset(path=dataset_path, token=True)
+
+    assert dataset["train"].num_rows == expected_num_train
+    assert dataset["test"].num_rows == expected_num_test