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README.md

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----
-annotations_creators:
-- expert-generated
-language: []
-language_creators: []
-license:
-- cc0-1.0
-multilinguality: []
-pretty_name: 19th Century United States Newspaper Advert images with 'illustrated'
-  or 'non illustrated' labels
-size_categories:
-- n<1K
-source_datasets: []
-tags:
-- lam
-- historic newspapers
-task_categories:
-- image-classification
-task_ids:
-- multi-class-image-classification
----
-
-
-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 (chroniclingamerica.loc.gov/). 
-
-> [The Newspaper Navigator dataset](https://news-navigator.labs.loc.gov/) consists of extracted visual content for 16,358,041 historic newspaper pages in Chronicling America. The visual content was identified using an object detection model trained on annotations of World War 1-era Chronicling America pages, including annotations made by volunteers as part of the Beyond Words crowdsourcing project. source: https://news-navigator.labs.loc.gov/
-
-One of these categories is 'advertisements'. This dataset contains a sample of these images with additional labels indicating if the advert is 'illustrated' or 'not illustrated'.
-
-This dataset was created for use in a [Programming Historian tutorial](http://programminghistorian.github.io/ph-submissions/lessons/computer-vision-deep-learning-pt1). The primary aim of the data was to provide a realistic example dataset for teaching computer vision for working with digitised heritage material.
-
-
-# Dataset Card for 19th Century United States Newspaper Advert images with 'illustrated' or 'non illustrated' labels
-
-## 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:**
-- **Repository:**[https://doi.org/10.5281/zenodo.5838410](https://doi.org/10.5281/zenodo.5838410)
-- **Paper:**[https://doi.org/10.46430/phen0101](https://doi.org/10.46430/phen0101)
-- **Leaderboard:**
-- **Point of Contact:**
-
-### Dataset Summary
-
-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 (chroniclingamerica.loc.gov/). 
-
-> [The Newspaper Navigator dataset](https://news-navigator.labs.loc.gov/) consists of extracted visual content for 16,358,041 historic newspaper pages in Chronicling America. The visual content was identified using an object detection model trained on annotations of World War 1-era Chronicling America pages, including annotations made by volunteers as part of the Beyond Words crowdsourcing project. source: https://news-navigator.labs.loc.gov/
-
-One of these categories is 'advertisements. This dataset contains a sample of these images with additional labels indicating if the advert is 'illustrated' or 'not illustrated'.
-
-This dataset was created for use in a [Programming Historian tutorial](http://programminghistorian.github.io/ph-submissions/lessons/computer-vision-deep-learning-pt1). The primary aim of the data was to provide a realistic example dataset for teaching computer vision for working with digitised heritage material.
-
-
-### Supported Tasks and Leaderboards
-
-- `image-classification`: the primary purpose of this dataset is for classifying historic newspaper images identified as being 'advertisements' into 'illustrated' and 'not-illustrated' categories. 
-
-### Languages
-
-[More Information Needed]
-
-## Dataset Structure
-
-### Data Instances
-
-An example instance from this dataset
-
-``` python
-{'file': 'pst_fenske_ver02_data_sn84026497_00280776129_1880042101_0834_002_6_96.jpg',
- 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=L size=388x395 at 0x7F9A72038950>,
- 'label': 0,
- 'pub_date': Timestamp('1880-04-21 00:00:00'),
- 'page_seq_num': 834,
- 'edition_seq_num': 1,
- 'batch': 'pst_fenske_ver02',
- 'lccn': 'sn84026497',
- 'box': [0.649412214756012,
-  0.6045778393745422,
-  0.8002520799636841,
-  0.7152365446090698],
- 'score': 0.9609346985816956,
- 'ocr': "H. II. IIASLKT & SOXN, Dealers in General Merchandise In New Store Room nt HASLET'S COS ITERS, 'JTionoMtii, ln. .Tau'y 1st, 1?0.",
- 'place_of_publication': 'Tionesta, Pa.',
- 'geographic_coverage': "['Pennsylvania--Forest--Tionesta']",
- 'name': 'The Forest Republican. [volume]',
- 'publisher': 'Ed. W. Smiley',
- 'url': 'https://news-navigator.labs.loc.gov/data/pst_fenske_ver02/data/sn84026497/00280776129/1880042101/0834/002_6_96.jpg',
- 'page_url': 'https://chroniclingamerica.loc.gov/data/batches/pst_fenske_ver02/data/sn84026497/00280776129/1880042101/0834.jp2'}
-```
-### Data Fields
-
-[More Information Needed]
-
-### Data Splits
-
-The dataset contains a single split. 
-
-## 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
-
-A description of the annotation process is outlined in this [GitHub repository](https://github.com/Living-with-machines/nnanno)
-[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
-@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}}
-
-```
-
-
-[More Information Needed]
-
-### Contributions
-
-Thanks to [@davanstrien](https://github.com/davanstrien) for adding this dataset.

dataset_infos.json

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-{"default": {"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. \n", "citation": "@dataset{van_strien_daniel_2021_5838410,\n  author       = {van Strien, Daniel},\n  title        = {{19th Century United States Newspaper Advert images \n                   with 'illustrated' or 'non illustrated' labels}},\n  month        = oct,\n  year         = 2021,\n  publisher    = {Zenodo},\n  version      = {0.0.1},\n  doi          = {10.5281/zenodo.5838410},\n  url          = {https://doi.org/10.5281/zenodo.5838410}}\n", "homepage": "https://doi.org/10.5281/zenodo.5838410", "license": "Public Domain", "features": {"file": {"dtype": "string", "id": null, "_type": "Value"}, "image": {"decode": true, "id": null, "_type": "Image"}, "label": {"num_classes": 2, "names": ["text-only", "illustrations"], "id": null, "_type": "ClassLabel"}, "pub_date": {"dtype": "timestamp[ns]", "id": null, "_type": "Value"}, "page_seq_num": {"dtype": "int64", "id": null, "_type": "Value"}, "edition_seq_num": {"dtype": "int64", "id": null, "_type": "Value"}, "batch": {"dtype": "string", "id": null, "_type": "Value"}, "lccn": {"dtype": "string", "id": null, "_type": "Value"}, "box": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "score": {"dtype": "float64", "id": null, "_type": "Value"}, "ocr": {"dtype": "string", "id": null, "_type": "Value"}, "place_of_publication": {"dtype": "string", "id": null, "_type": "Value"}, "geographic_coverage": {"dtype": "string", "id": null, "_type": "Value"}, "name": {"dtype": "string", "id": null, "_type": "Value"}, "publisher": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "page_url": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "illustrated_ads", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 773969, "num_examples": 549, "dataset_name": "illustrated_ads"}}, "download_checksums": {"https://zenodo.org/record/5838410/files/images.zip?download=1": {"num_bytes": 48063000, "checksum": "05f1562bca55a44ff00ad52aec19b59ce10566d6d3d169ef75e0224e4a514295"}, "https://zenodo.org/record/5838410/files/ads.csv?download=1": {"num_bytes": 47362, "checksum": "001098f61be7630d985ffc61713c620a9a78518bda6f7ae569c43d37e032cccb"}, "https://zenodo.org/record/5838410/files/sample.csv?download=1": {"num_bytes": 876387, "checksum": "74f585434b9b644c30fbafe9ff400d52dbfb51d620551a23194ecf961db5d697"}}, "download_size": 48986749, "post_processing_size": null, "dataset_size": 773969, "size_in_bytes": 49760718}}

default/illustrated_ads-train.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:984d73fc2a29bb172f6516f886e127d78c9d524604d789901b17876ff544919a
+size 48009351

illustrated_ads.py

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-# 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
-from PIL import Image
-
-_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