Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-class-image-classification
Size Categories:
n<1K
Annotations Creators:
expert-generated
License:
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """Dataset of illustrated and non illustrated 19th Century newspaper ads.""" | |
| import ast | |
| import os | |
| import pandas as pd | |
| import datasets | |
| _CITATION = """\ | |
| @dataset{van_strien_daniel_2021_5838410, | |
| author = {van Strien, Daniel}, | |
| title = {{19th Century United States Newspaper Advert images | |
| with 'illustrated' or 'non illustrated' labels}}, | |
| month = oct, | |
| year = 2021, | |
| publisher = {Zenodo}, | |
| version = {0.0.1}, | |
| doi = {10.5281/zenodo.5838410}, | |
| url = {https://doi.org/10.5281/zenodo.5838410}} | |
| """ | |
| _DESCRIPTION = """\ | |
| The Dataset contains images derived from the Newspaper Navigator (news-navigator.labs.loc.gov/), a dataset of images drawn from the Library of Congress Chronicling America collection. | |
| """ | |
| _HOMEPAGE = "https://doi.org/10.5281/zenodo.5838410" | |
| _LICENSE = "Public Domain" | |
| _URLS = "https://zenodo.org/record/5838410/files/images.zip?download=1" | |
| _DTYPES = { | |
| "page_seq_num": "int64", | |
| "edition_seq_num": "int64", | |
| "batch": "string", | |
| "lccn": "string", | |
| "score": "float64", | |
| "place_of_publication": "string", | |
| "name": "string", | |
| "publisher": "string", | |
| "url": "string", | |
| "page_url": "string", | |
| } | |
| class IllustratedAds(datasets.GeneratorBasedBuilder): | |
| """Illustated Historic Newspaper Ads datasets""" | |
| VERSION = datasets.Version("1.1.0") | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "file": datasets.Value("string"), | |
| "image": datasets.Image(), | |
| "label": datasets.ClassLabel(names=["text-only", "illustrations"]), | |
| "pub_date": datasets.Value("timestamp[ns]"), | |
| "page_seq_num": datasets.Value("int64"), | |
| "edition_seq_num": datasets.Value("int64"), | |
| "batch": datasets.Value("string"), | |
| "lccn": datasets.Value("string"), | |
| "box": datasets.Sequence(datasets.Value("float32")), | |
| "score": datasets.Value("float64"), | |
| "ocr": datasets.Value("string"), | |
| "place_of_publication": datasets.Value("string"), | |
| "geographic_coverage": datasets.Value("string"), | |
| "name": datasets.Value("string"), | |
| "publisher": datasets.Value("string"), | |
| "url": datasets.Value("string"), | |
| "page_url": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| images = dl_manager.download_and_extract(_URLS) | |
| annotations = dl_manager.download( | |
| [ | |
| "https://zenodo.org/record/5838410/files/ads.csv?download=1", | |
| "https://zenodo.org/record/5838410/files/sample.csv?download=1", | |
| ] | |
| ) | |
| df_labels = pd.read_csv(annotations[0], index_col=0) | |
| df_metadata = pd.read_csv( | |
| annotations[1], | |
| index_col=0, | |
| dtype=_DTYPES, | |
| ) | |
| df_metadata["file"] = df_metadata.filepath.str.replace("/", "_") | |
| df_metadata = df_metadata.set_index("file", drop=True) | |
| df = df_labels.join(df_metadata) | |
| df = df.reset_index() | |
| annotations = df.to_dict(orient="records") | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "images": images, | |
| "annotations": annotations, | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, images, annotations): | |
| for id_, row in enumerate(annotations): | |
| box = ast.literal_eval(row["box"]) | |
| row["box"] = box | |
| row.pop("filepath") | |
| ocr = " ".join(ast.literal_eval(row["ocr"])) | |
| row["ocr"] = ocr | |
| image = row["file"] | |
| row["image"] = os.path.join(images, image) | |
| yield id_, row | |