Initialize (#1)

* add README.md

* add script

* add poetry files

* add scripts for tests

* add settings for CI

* add .gitignore

* update README.md

* add settings for CI

* update README

.github/workflows/ci.yaml

@@ -0,0 +1,45 @@
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+    paths-ignore:
+      - 'README.md'
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.8', '3.9', '3.10']
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        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 flake8 . --ignore=E501,W503,E203
+      - 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@v2
+        
+      - 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}/CAMERA main

.gitignore

@@ -0,0 +1,176 @@
+# 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

CAMERA.py

@@ -0,0 +1,147 @@
+import ast
+import os
+from typing import Optional
+
+import datasets as ds
+import pandas as pd
+
+_CITATION = """\
+@inproceedings{mita-et-al:nlp2023,
+    author =    "三田 雅人 and 村上 聡一朗 and 張 培楠",
+    title =	    "広告文生成タスクの規定とベンチマーク構築",
+    booktitle = "言語処理学会 第29回年次大会",
+    year =      2023,
+}
+"""
+
+_DESCRIPTION = """\
+CAMERA (CyberAgent Multimodal Evaluation for Ad Text GeneRAtion) is the Japanese ad text generation dataset.
+"""
+
+_HOMEPAGE = "https://github.com/CyberAgentAILab/camera"
+
+_LICENSE = """\
+This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
+"""
+
+_URLS = {
+    "without-lp-images": "https://storage.googleapis.com/camera-public/camera-v1-minimal.tar.gz",
+    "with-lp-images": "https://storage.googleapis.com/camera-public/camera-v1.tar.gz",
+}
+
+
+class CameraDataset(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        ds.BuilderConfig(
+            name="without-lp-images",
+            version=VERSION,
+            description="The CAMERA dataset w/o LP images (ver.1.0.0 | 126.2 MiB)",
+        ),
+        ds.BuilderConfig(
+            name="with-lp-images",
+            version=VERSION,
+            description="The CAMERA dataset w/ LP images (ver.1.0.0 | 61.5 GiB)",
+        ),
+    ]
+
+    def _info(self) -> ds.DatasetInfo:
+        features = ds.Features(
+            {
+                "asset_id": ds.Value("int64"),
+                "kw": ds.Value("string"),
+                "lp_meta_description": ds.Value("string"),
+                "title_org": ds.Value("string"),
+                "title_ne1": ds.Value("string"),
+                "title_ne2": ds.Value("string"),
+                "title_ne3": ds.Value("string"),
+                "domain": ds.Value("string"),
+                "parsed_full_text_annotation": ds.Sequence(
+                    {
+                        "text": ds.Value("string"),
+                        "xmax": ds.Value("int64"),
+                        "xmin": ds.Value("int64"),
+                        "ymax": ds.Value("int64"),
+                        "ymin": ds.Value("int64"),
+                    }
+                ),
+            }
+        )
+
+        if self.config.name == "with-lp-images":
+            features["lp_image"] = ds.Image()
+
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            features=features,
+        )
+
+    def _split_generators(self, dl_manager: ds.DownloadManager):
+        base_dir = dl_manager.download_and_extract(_URLS[self.config.name])
+        lp_image_dir: Optional[str] = None
+
+        if self.config.name == "without-lp-images":
+            camera_dir_name = f"camera-v{self.VERSION.major}-minimal"
+        elif self.config.name == "with-lp-images":
+            camera_dir_name = f"camera-v{self.VERSION.major}"
+            lp_image_dir = os.path.join(base_dir, camera_dir_name, "lp-screenshot")
+        else:
+            raise ValueError(f"Invalid config name: {self.config.name}")
+
+        tng_path = os.path.join(base_dir, camera_dir_name, "train.csv")
+        dev_path = os.path.join(base_dir, camera_dir_name, "dev.csv")
+        tst_path = os.path.join(base_dir, camera_dir_name, "test.csv")
+
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={"file_path": tng_path, "lp_image_dir": lp_image_dir},
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.VALIDATION,
+                gen_kwargs={"file_path": dev_path, "lp_image_dir": lp_image_dir},
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.TEST,
+                gen_kwargs={"file_path": tst_path, "lp_image_dir": lp_image_dir},
+            ),
+        ]
+
+    def _generate_examples(self, file_path: str, lp_image_dir: Optional[str] = None):
+        df = pd.read_csv(file_path)
+        for i in range(len(df)):
+            data_dict = df.iloc[i].to_dict()
+
+            asset_id = data_dict["asset_id"]
+            keywords = data_dict["kw"]
+            lp_meta_description = data_dict["lp_meta_description"]
+            domain = data_dict.get("domain", "")
+            text_anns = ast.literal_eval(data_dict["parsed_full_text_annotation"])
+
+            title_org = data_dict["title_org"]
+            title_ne1 = data_dict.get("title_ne1", "")
+            title_ne2 = data_dict.get("title_ne2", "")
+            title_ne3 = data_dict.get("title_ne3", "")
+
+            example_dict = {
+                "asset_id": asset_id,
+                "kw": keywords,
+                "lp_meta_description": lp_meta_description,
+                "title_org": title_org,
+                "title_ne1": title_ne1,
+                "title_ne2": title_ne2,
+                "title_ne3": title_ne3,
+                "domain": domain,
+                "parsed_full_text_annotation": text_anns,
+            }
+
+            if self.config.name == "with-lp-images" and lp_image_dir is not None:
+                lp_image_file_name = f"screen-1200-{asset_id}.png"
+                example_dict["lp_image"] = os.path.join(
+                    lp_image_dir, lp_image_file_name
+                )
+
+            yield i, example_dict

README.md

@@ -0,0 +1,347 @@
+---
+annotations_creators:
+- crowdsourced
+language:
+- ja-JP
+language_creators:
+- found
+license:
+- cc-by-nc-sa-4.0
+multilinguality:
+- monolingual
+pretty_name: CAMERA
+size_categories: []
+source_datasets:
+- original
+tags: []
+task_categories:
+- text-generation
+task_ids: []
+---
+
+# Dataset Card for CAMERA 📷
+
+[![CI](https://github.com/shunk031/huggingface-datasets_CAMERA/actions/workflows/ci.yaml/badge.svg)](https://github.com/shunk031/huggingface-datasets_CAMERA/actions/workflows/ci.yaml)
+
+## Table of Contents
+- [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)
+  - [Annotations](#annotations)
+  - [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://github.com/CyberAgentAILab/camera
+- **Repository:** https://github.com/shunk031/huggingface-datasets_CAMERA
+
+### Dataset Summary
+
+From [the official README.md](https://github.com/CyberAgentAILab/camera#camera-dataset):
+
+> CAMERA (CyberAgent Multimodal Evaluation for Ad Text GeneRAtion) is the Japanese ad text generation dataset. We hope that our dataset will be useful in research for realizing more advanced ad text generation models.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+#### Supported Tasks
+
+[More Information Needed]
+
+#### Leaderboard
+
+[More Information Needed]
+
+### Languages
+
+The language data in CAMERA is in Japanese ([BCP-47 ja-JP](https://www.rfc-editor.org/info/bcp47)).
+
+## Dataset Structure
+
+### Data Instances
+
+When loading a specific configuration, users has to append a version dependent suffix:
+
+#### without-lp-images
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("shunk031/CAMERA", name="without-lp-images")
+
+print(dataset)
+# DatasetDict({
+#     train: Dataset({
+#         features: ['asset_id', 'kw', 'lp_meta_description', 'title_org', 'title_ne1', 'title_ne2', 'title_ne3', 'domain', 'parsed_full_text_annotation'],
+#         num_rows: 12395
+#     })
+#     validation: Dataset({
+#         features: ['asset_id', 'kw', 'lp_meta_description', 'title_org', 'title_ne1', 'title_ne2', 'title_ne3', 'domain', 'parsed_full_text_annotation'],
+#         num_rows: 3098
+#     })
+#     test: Dataset({
+#         features: ['asset_id', 'kw', 'lp_meta_description', 'title_org', 'title_ne1', 'title_ne2', 'title_ne3', 'domain', 'parsed_full_text_annotation'],
+#         num_rows: 872
+#     })
+# })
+```
+
+An example of the CAMERA (w/o LP images) dataset looks as follows:
+
+```json
+{
+    "asset_id": 13861, 
+    "kw": "仙台 ホテル", 
+    "lp_meta_description": "仙台のホテルや旅館をお探しなら楽天トラベルへ！楽天ポイントが使えて、貯まって、とってもお得な宿泊予約サイトです。さらに割引クーポンも使える！国内ツアー・航空券・レンタカー・バス予約も！", 
+    "title_org": "仙台市のホテル", 
+    "title_ne1": "", 
+    "title_ne2": "", 
+    "title_ne3": "", 
+    "domain": "", 
+    "parsed_full_text_annotation": {
+        "text": [
+            "trivago", 
+            "Oops...AccessDenied 可", 
+            "Youarenotallowedtoviewthispage!Ifyouthinkthisisanerror,pleasecontacttrivago.", 
+            "Errorcode:0.3c99e86e.1672026945.25ba640YourIP:240d:1a:4d8:2800:b9b0:ea86:2087:d141AffectedURL:https://www.trivago.jp/ja/odr/%E8%BB%92", "%E4%BB%99%E5%8F%B0-%E5%9B%BD%E5%86%85?search=20072325", 
+            "Backtotrivago"
+        ], 
+        "xmax": [
+            653, 
+            838, 
+            765, 
+            773, 
+            815, 
+            649
+        ], 
+        "xmin": [
+            547, 
+            357, 
+            433, 
+            420, 
+            378, 
+            550
+        ], 
+        "ymax": [
+            47, 
+            390, 
+            475, 
+            558, 
+            598, 
+            663
+        ], 
+        "ymin": [
+            18, 
+            198, 
+            439, 
+            504, 
+            566, 
+            651
+        ]
+    }
+}
+```
+
+#### with-lp-images
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("shunk031/CAMERA", name="with-lp-images")
+
+print(dataset)
+# DatasetDict({
+#     train: Dataset({
+#         features: ['asset_id', 'kw', 'lp_meta_description', 'title_org', 'title_ne1', 'title_ne2', 'title_ne3', 'domain', 'parsed_full_text_annotation', 'lp_image'],
+#         num_rows: 12395
+#     })
+#     validation: Dataset({
+#         features: ['asset_id', 'kw', 'lp_meta_description', 'title_org', 'title_ne1', 'title_ne2', 'title_ne3', 'domain', 'parsed_full_text_annotation', 'lp_image'],
+#         num_rows: 3098
+#     })
+#     test: Dataset({
+#         features: ['asset_id', 'kw', 'lp_meta_description', 'title_org', 'title_ne1', 'title_ne2', 'title_ne3', 'domain', 'parsed_full_text_annotation', 'lp_image'],
+#         num_rows: 872
+#     })
+# })
+```
+
+An example of the CAMERA (w/ LP images) dataset looks as follows:
+
+```json
+{
+    "asset_id": 13861, 
+    "kw": "仙台 ホテル", 
+    "lp_meta_description": "仙台のホテルや旅館をお探しなら楽天トラベルへ！楽天ポイントが使えて、貯まって、とってもお得な宿泊予約サイトです。さらに割引クーポンも使える！国内ツアー・航空券・レンタカー・バス予約も！", 
+    "title_org": "仙台市のホテル", 
+    "title_ne1": "", 
+    "title_ne2": "", 
+    "title_ne3": "", 
+    "domain": "", 
+    "parsed_full_text_annotation": {
+        "text": [
+            "trivago", 
+            "Oops...AccessDenied 可", 
+            "Youarenotallowedtoviewthispage!Ifyouthinkthisisanerror,pleasecontacttrivago.", 
+            "Errorcode:0.3c99e86e.1672026945.25ba640YourIP:240d:1a:4d8:2800:b9b0:ea86:2087:d141AffectedURL:https://www.trivago.jp/ja/odr/%E8%BB%92", "%E4%BB%99%E5%8F%B0-%E5%9B%BD%E5%86%85?search=20072325", 
+            "Backtotrivago"
+        ], 
+        "xmax": [
+            653, 
+            838, 
+            765, 
+            773, 
+            815, 
+            649
+        ], 
+        "xmin": [
+            547, 
+            357, 
+            433, 
+            420, 
+            378, 
+            550
+        ], 
+        "ymax": [
+            47, 
+            390, 
+            475, 
+            558, 
+            598, 
+            663
+        ], 
+        "ymin": [
+            18, 
+            198, 
+            439, 
+            504, 
+            566, 
+            651
+        ]
+    },
+    "lp_image": <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1200x680 at 0x7F8513446B20>
+}
+```
+
+### Data Fields
+
+#### without-lp-images
+
+- `asset_id`: ids (associated with LP images)
+- `kw`: search keyword
+- `lp_meta_description`: meta description extracted from LP (i.e., LP Text)
+- `title_org`: ad text (original gold reference)
+- `title_ne{1-3}`: ad text (additonal gold references for multi-reference evaluation)
+- `domain`: industry domain (HR, EC, Fin, Edu) for industry-wise evaluation
+- `parsed_full_text_annotation`: OCR results for LP images
+
+#### with-lp-images
+
+- `asset_id`: ids (associated with LP images)
+- `kw`: search keyword
+- `lp_meta_description`: meta description extracted from LP (i.e., LP Text)
+- `title_org`: ad text (original gold reference)
+- `title_ne{1-3}`: ad text (additional gold references for multi-reference evaluation)
+- `domain`: industry domain (HR, EC, Fin, Edu) for industry-wise evaluation
+- `parsed_full_text_annotation`: OCR results for LP images
+- `lp_image`: Landing page (LP) image
+
+### Data Splits
+
+From [the official paper](https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/H11-4.pdf):
+
+| Split | # of data | # of reference ad text | industry domain label |
+|-------|----------:|-----------------------:|:---------------------:|
+| Train | 12,395    | 1                      | -                     |
+| Valid | 3,098     | 1                      | -                     |
+| Test  | 869       | 4                      | ✔                     |
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### 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
+
+[More Information Needed]
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+> This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
+
+### Citation Information
+
+```bibtex
+@inproceedings{mita-et-al:nlp2023,
+    author =    "三田 雅人 and 村上 聡一朗 and 張 培楠",
+    title =	    "広告文生成タスクの規���とベンチマーク構築",
+    booktitle = "言語処理学会 第 29 回年次大会",
+    year =      2023,
+}
+```
+
+### Contributions
+
+Thanks to [Masato Mita](https://github.com/chemicaltree), [Soichiro Murakami](https://github.com/ichiroex), and [Peinan Zhang](https://github.com/peinan) for creating this dataset.

pyproject.toml

@@ -0,0 +1,24 @@
+[tool.poetry]
+name = "huggingface-datasets-camera"
+version = "0.1.0"
+description = ""
+authors = ["Shunsuke KITADA <[email protected]>"]
+readme = "README.md"
+packages = []
+
+[tool.poetry.dependencies]
+python = "^3.8"
+datasets = "^2.10.1"
+pillow = "^9.4.0"
+
+
+[tool.poetry.group.dev.dependencies]
+black = "^23.1.0"
+isort = "^5.12.0"
+flake8 = "^6.0.0"
+mypy = "^1.1.1"
+pytest = "^7.2.2"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

tests/CAMERA_test.py

@@ -0,0 +1,41 @@
+import os
+
+import datasets as ds
+import pytest
+
+
+@pytest.fixture
+def dataset_path() -> str:
+    return "CAMERA.py"
+
+
+def test_load_dataset_without_lp_images(
+    dataset_path: str,
+    expected_train_num_rows: int = 12395,
+    expected_val_num_rows: int = 3098,
+    expected_test_num_rows: int = 872,
+):
+    dataset = ds.load_dataset(path=dataset_path, name="without-lp-images")
+
+    assert dataset["train"].num_rows == expected_train_num_rows  # type: ignore
+    assert dataset["validation"].num_rows == expected_val_num_rows  # type: ignore
+    assert dataset["test"].num_rows == expected_test_num_rows  # type: ignore
+
+
+@pytest.mark.skipif(
+    bool(os.environ.get("CI", False)),
+    reason="Because this test downloads a large data set, we will skip running it on CI.",
+)
+def test_load_dataset_with_lp_images(
+    dataset_path: str,
+    expected_train_num_rows: int = 12395,
+    expected_val_num_rows: int = 3098,
+    expected_test_num_rows: int = 872,
+):
+    dataset = ds.load_dataset(path=dataset_path, name="with-lp-images")
+
+    assert dataset["train"].num_rows == expected_train_num_rows  # type: ignore
+    assert dataset["validation"].num_rows == expected_val_num_rows  # type: ignore
+    assert dataset["test"].num_rows == expected_test_num_rows  # type: ignore
+
+    assert "lp_image" in dataset["train"].column_names