| """Tel Aviv Urban Photography Dataset""" |
|
|
| import csv |
| import os |
| import datasets |
|
|
| _CITATION = """\ |
| @dataset{tel_aviv_pics_2025, |
| title={Tel Aviv Urban Photography Dataset}, |
| author={Rosehill, Daniel}, |
| year={2025}, |
| publisher={Hugging Face}, |
| howpublished={\\url{https://huggingface.co/datasets/danielrosehill/Tel-Aviv-Pics}} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| This dataset contains 53 high-quality photographs of Tel Aviv's urban environment, |
| captured to serve as reference material for game development, 3D world creation, |
| and digital environment design. |
| |
| All photographs were taken by Daniel Rosehill and are available on Pexels: |
| https://www.pexels.com/@danielrosehill/ |
| """ |
|
|
| _HOMEPAGE = "https://huggingface.co/datasets/danielrosehill/Tel-Aviv-Pics" |
|
|
| _LICENSE = "cc-by-4.0" |
|
|
| _URLS = { |
| "images": "data/images/", |
| "metadata": "metadata.csv", |
| } |
|
|
|
|
| class TelAvivPics(datasets.GeneratorBasedBuilder): |
| """Tel Aviv Urban Photography Dataset for game development and 3D world creation.""" |
|
|
| VERSION = datasets.Version("1.0.0") |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "image": datasets.Image(), |
| "filename": datasets.Value("string"), |
| "image_number": datasets.Value("string"), |
| "file_size_bytes": datasets.Value("int64"), |
| "photographer": datasets.Value("string"), |
| "photographer_url": datasets.Value("string"), |
| "location": datasets.Value("string"), |
| } |
| ), |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "images_dir": "data/images", |
| "metadata_file": "metadata.csv", |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, images_dir, metadata_file): |
| """Yields examples.""" |
| |
| with open(metadata_file, encoding="utf-8") as f: |
| reader = csv.DictReader(f) |
| for idx, row in enumerate(reader): |
| image_path = os.path.join(images_dir, row["filename"]) |
|
|
| yield idx, { |
| "image": image_path, |
| "filename": row["filename"], |
| "image_number": row["image_number"], |
| "file_size_bytes": int(row["file_size_bytes"]), |
| "photographer": row["photographer"], |
| "photographer_url": row["photographer_url"], |
| "location": row["location"], |
| } |
|
|
