| import datasets |
| import pandas as pd |
|
|
| _CITATION = """\ |
| @InProceedings{huggingface:dataset, |
| title = {spam-text-messages-dataset}, |
| author = {TrainingDataPro}, |
| year = {2023} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| The SMS spam dataset contains a collection of text messages. The dataset |
| includes a diverse range of spam messages, including promotional offers, |
| fraudulent schemes, phishing attempts, and other forms of unsolicited |
| communication. |
| Each SMS message is represented as a string of text, and each entry in the |
| dataset also has a link to the corresponding screenshot. The dataset's content |
| represents real-life examples of spam messages that users encounter in their |
| everyday communication. |
| """ |
| _NAME = 'spam-text-messages-dataset' |
|
|
| _HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}" |
|
|
| _LICENSE = "" |
|
|
| _DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/" |
|
|
|
|
| class SpamTextMessagesDataset(datasets.GeneratorBasedBuilder): |
| """Small sample of image-text pairs""" |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features({ |
| 'image': datasets.Image(), |
| 'text': datasets.Value('string') |
| }), |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| images = dl_manager.download(f"{_DATA}images.tar.gz") |
| annotations = dl_manager.download(f"{_DATA}{_NAME}.csv") |
| images = dl_manager.iter_archive(images) |
| return [ |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "images": images, |
| 'annotations': annotations |
| }), |
| ] |
|
|
| def _generate_examples(self, images, annotations): |
| annotations_df = pd.read_csv(annotations, sep=';') |
|
|
| for idx, (image_path, image) in enumerate(images): |
| yield idx, { |
| "image": { |
| "path": image_path, |
| "bytes": image.read() |
| }, |
| 'text': |
| annotations_df.loc[annotations_df['image'].str.lower() == |
| image_path.lower()]['text'].values[0] |
| } |
|
|
