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"""MNIST Point Cloud Data Set""" |
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import struct |
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import numpy as np |
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import datasets |
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_VERSION = "0.0.3" |
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_DESCRIPTION = """\ |
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The MNIST dataset consists of 70,000 28x28 black-and-white points in 10 classes (one for each digits), with 7,000 |
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points per class. There are 60,000 training points and 10,000 test points. |
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""" |
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_URL = f"https://huggingface.co/datasets/cgarciae/point-cloud-mnist/resolve/{_VERSION}/data/" |
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_URLS = { |
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"train_points": "X_train.npy", |
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"train_labels": "y_train.npy", |
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"test_points": "X_test.npy", |
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"test_labels": "y_test.npy", |
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} |
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class MNIST(datasets.GeneratorBasedBuilder): |
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"""MNIST Data Set""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="point-cloud-mnist", |
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version=datasets.Version(_VERSION), |
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description=_DESCRIPTION, |
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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=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"points": datasets.Array2D(shape=(351, 3), dtype="uint8"), |
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"label": datasets.features.ClassLabel( |
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names=["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"] |
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), |
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} |
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), |
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supervised_keys=("points", "label"), |
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) |
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def _split_generators(self, dl_manager): |
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urls_to_download = {key: _URL + fname for key, fname in _URLS.items()} |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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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={ |
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"filepath": [ |
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downloaded_files["train_points"], |
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downloaded_files["train_labels"], |
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], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepath": [ |
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downloaded_files["test_points"], |
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downloaded_files["test_labels"], |
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], |
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"split": "test", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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"""This function returns the examples in the raw form.""" |
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with open(filepath[0], "rb") as f: |
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points = np.load(f) |
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with open(filepath[1], "rb") as f: |
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labels = np.load(f) |
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for idx in range(len(points)): |
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yield ( |
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idx, |
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{ |
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"points": points[idx], |
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"label": str(labels[idx]), |
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}, |
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) |
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