Datasets:
Tasks:
Image Classification
Size:
< 1K
| import os | |
| import datasets | |
| from datasets.tasks import ImageClassification | |
| _HOMEPAGE = "https://universe.roboflow.com/yolo-po0ro/proj-2-qmdk0/dataset/3" | |
| _LICENSE = "CC BY 4.0" | |
| _CITATION = """\ | |
| @misc{ proj-2-qmdk0_dataset, | |
| title = { proj 2 Dataset }, | |
| type = { Open Source Dataset }, | |
| author = { Yolo }, | |
| howpublished = { \\url{ https://universe.roboflow.com/yolo-po0ro/proj-2-qmdk0 } }, | |
| url = { https://universe.roboflow.com/yolo-po0ro/proj-2-qmdk0 }, | |
| journal = { Roboflow Universe }, | |
| publisher = { Roboflow }, | |
| year = { 2023 }, | |
| month = { oct }, | |
| note = { visited on 2023-10-18 }, | |
| } | |
| """ | |
| _CATEGORIES = ['Thermostat', 'Housing', 'Insert'] | |
| class THERMOCLASSIFICATIONConfig(datasets.BuilderConfig): | |
| """Builder Config for thermo-classification""" | |
| def __init__(self, data_urls, **kwargs): | |
| """ | |
| BuilderConfig for thermo-classification. | |
| Args: | |
| data_urls: `dict`, name to url to download the zip file from. | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| super(THERMOCLASSIFICATIONConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs) | |
| self.data_urls = data_urls | |
| class THERMOCLASSIFICATION(datasets.GeneratorBasedBuilder): | |
| """thermo-classification image classification dataset""" | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| THERMOCLASSIFICATIONConfig( | |
| name="full", | |
| description="Full version of thermo-classification dataset.", | |
| data_urls={ | |
| "train": "https://huggingface.co/datasets/sargishunanyan/thermo-classification/resolve/main/data/train.zip", | |
| "validation": "https://huggingface.co/datasets/sargishunanyan/thermo-classification/resolve/main/data/valid.zip", | |
| "test": "https://huggingface.co/datasets/sargishunanyan/thermo-classification/resolve/main/data/test.zip", | |
| } | |
| , | |
| ), | |
| THERMOCLASSIFICATIONConfig( | |
| name="mini", | |
| description="Mini version of thermo-classification dataset.", | |
| data_urls={ | |
| "train": "https://huggingface.co/datasets/sargishunanyan/thermo-classification/resolve/main/data/valid-mini.zip", | |
| "validation": "https://huggingface.co/datasets/sargishunanyan/thermo-classification/resolve/main/data/valid-mini.zip", | |
| "test": "https://huggingface.co/datasets/sargishunanyan/thermo-classification/resolve/main/data/valid-mini.zip", | |
| }, | |
| ) | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| features=datasets.Features( | |
| { | |
| "image_file_path": datasets.Value("string"), | |
| "image": datasets.Image(), | |
| "labels": datasets.features.ClassLabel(names=_CATEGORIES), | |
| } | |
| ), | |
| supervised_keys=("image", "labels"), | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| license=_LICENSE, | |
| task_templates=[ImageClassification(image_column="image", label_column="labels")], | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_files = dl_manager.download_and_extract(self.config.data_urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "files": dl_manager.iter_files([data_files["train"]]), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "files": dl_manager.iter_files([data_files["validation"]]), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "files": dl_manager.iter_files([data_files["test"]]), | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, files): | |
| for i, path in enumerate(files): | |
| file_name = os.path.basename(path) | |
| if file_name.endswith((".jpg", ".png", ".jpeg", ".bmp", ".tif", ".tiff")): | |
| yield i, { | |
| "image_file_path": path, | |
| "image": path, | |
| "labels": os.path.basename(os.path.dirname(path)), | |
| } | |