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""" |
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import datasets |
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import os |
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import pyarrow.parquet as pq |
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from PIL import Image |
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from io import BytesIO |
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import numpy as np |
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import pandas as pd |
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def load_data(data_dir): |
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parquet_file = [file for file in os.listdir(data_dir) if file.endswith('.parquet')][0] |
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print(parquet_file) |
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parquet_path = os.path.join(data_dir, parquet_file) |
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parquet_path = data_dir |
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table = pq.read_table(parquet_path) |
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for row in table.iterrecords(): |
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image_bytes = row['image'] |
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image = Image.open(BytesIO(image_bytes)) |
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label = row['label'] |
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yield image, label |
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class SATINConfig(datasets.BuilderConfig): |
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def __init__(self, name, description, data_url, class_names, **kwargs): |
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Args: |
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data_url: `string`, url to download the zip file from. |
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metadata_urls: dictionary with keys 'train' and 'validation' containing the archive metadata URLs |
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**kwargs: keyword arguments forwarded to super. |
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super(SATINConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs) |
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self.name = name |
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self.data_url = data_url |
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self.description = description |
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self.class_names = class_names |
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class SATIN(datasets.GeneratorBasedBuilder): |
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SATIN Images dataset |
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_SAT_4_NAMES = ['barren land', 'grassland', 'other', 'trees'] |
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_SAT_6_NAMES = ['barren land', 'building', 'grassland', 'road', 'trees', 'water'] |
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BUILDER_CONFIGS = [ |
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SATINConfig( |
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name="SAT_4", |
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description="SAT_4.", |
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data_url="https://huggingface.co/datasets/jonathan-roberts1/SAT-4/tree/main/data/",#train-00000-of-00001-e2dcb38bc165dfb0.parquet", |
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class_names = _SAT_4_NAMES |
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#metadata_urls={ |
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# "train": "https://link-to-breakfast-foods-train.txt", |
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), |
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SATINConfig( |
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name="SAT_6", |
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description="SAT_6.", |
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data_url="https://huggingface.co/datasets/jonathan-roberts1/SAT-6/tree/main/data/",#train-00000-of-00001-c47ada2c92f814d2.parquet", |
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class_names = _SAT_6_NAMES |
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) |
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] |
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@property |
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def url_prefix(self): |
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return { |
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"SAT-4": "https://huggingface.co/datasets/jonathan-roberts1/SAT-4/tree/main/data/",#train-00000-of-00001-e2dcb38bc165dfb0.parquet",#train-00000-of-00001-e2dcb38bc165dfb0.parquet", |
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"SAT-6": "https://huggingface.co/datasets/jonathan-roberts1/SAT-6/tree/main/data/", |
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} |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=self.config.description, |
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features=datasets.Features( |
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{ |
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"image": datasets.Image(), |
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"label": datasets.ClassLabel(names=self.config.class_names), |
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} |
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), |
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supervised_keys=("image", "label"), |
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#homepage=_HOMEPAGE, |
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#citation=_CITATION, |
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#license=_LICENSE, |
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#task_templates=[ImageClassification(image_column="image", label_column="label")], |
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) |
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def _split_generators(self, dl_manager): |
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url = self.config.data_url |
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data_dir = dl_manager.download_and_extract(url)#, use_auth_token=True) |
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print(data_dir) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"data_dir": data_dir}, |
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), |
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] |
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def _generate_examples(self, data_dir): |
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#base_url = self.url_prefix[self.config.name] |
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file_url = self.config.data_url |
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use_auth_token = os.environ.get("HUGGINGFACE_TOKEN") |
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with NamedTemporaryFile() as file: |
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download(file_url, file.name, use_auth_token=use_auth_token) |
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df = pd.read_parquet(file.name) |
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for idx, row in df.iterrows(): |
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example = { |
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"image": row["image"], |
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"label": row["label"], |
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} |
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yield idx, example |
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#def _generate_examples(self, data_dir): |
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# for idx, (image, label) in enumerate(load_data(data_dir)): |
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# image_array = np.array(image) |
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# yield idx, {"image": image_array, "label": label} |
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""" |
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from datasets.utils.download_manager import DownloadManager |
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import tempfile |
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import datasets |
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import os |
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import pyarrow.parquet as pq |
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from PIL import Image |
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from io import BytesIO |
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import numpy as np |
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import pandas as pd |
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class SATINConfig(datasets.BuilderConfig): |
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def __init__(self, name, description, data_url, class_names, **kwargs): |
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super(SATINConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs) |
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self.name = name |
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self.data_url = data_url |
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self.description = description |
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self.class_names = class_names |
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class SATIN(datasets.GeneratorBasedBuilder): |
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"""SATIN Images dataset""" |
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_SAT_4_NAMES = ['barren land', 'grassland', 'other', 'trees'] |
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_SAT_6_NAMES = ['barren land', 'building', 'grassland', 'road', 'trees', 'water'] |
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BUILDER_CONFIGS = [ |
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SATINConfig( |
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name="SAT_4", |
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description="SAT_4.", |
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data_url="jonathan-roberts1/SAT-4", |
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class_names=_SAT_4_NAMES |
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), |
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SATINConfig( |
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name="SAT_6", |
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description="SAT_6.", |
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data_url="jonathan-roberts1/SAT-6", |
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class_names=_SAT_6_NAMES |
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) |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=self.config.description, |
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features=datasets.Features( |
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{ |
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"image": datasets.Image(), |
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"label": datasets.ClassLabel(names=self.config.class_names), |
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} |
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), |
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supervised_keys=("image", "label"), |
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) |
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def _split_generators(self, dl_manager): |
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from datasets import load_dataset |
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dataset = load_dataset(self.config.data_url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"data_path": dataset}, |
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), |
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] |
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def _generate_examples(self, data_path): |
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huggingface_dataset = data_path["train"] |
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for idx, row in enumerate(huggingface_dataset): |
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yield idx, {"image": row["image"], "label": row["label"]} |
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