Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
1M<n<10M
Tags:
License:
File size: 2,067 Bytes
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"""Rock Glacier dataset with images of the chilean andes."""
import os
import datasets
from datasets.tasks import ImageClassification
_HOMEPAGE = "https://github.com/alcazar90/rock-glacier-detection"
_CITATION = """\
@ONLINE {rock-glacier-dataset,
author="CMM-Glaciares",
title="Rock Glacier Dataset",
month="October",
year="2022",
url="https://github.com/alcazar90/rock-glacier-detection"
}
"""
_DESCRIPTION = """\
TODO: Add a description...
"""
_URLS = {
"train": "https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/train.zip",
"validation": "https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/validation.zip"
}
_NAMES = ["glaciar", "cordillera"]
class RockGlacierDataset(datasets.GeneratorBasedBuilder):
"""Rock Glacier images dataset."""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"image": datasets.Image(),
"labels": datasets.features.ClassLabel(names=_NAMES),
}
),
supervised_keys=("image", "labels"),
homepage=_HOMEPAGE,
citation=_CITATION,
task_templates=[ImageClassification(image_column="image", label_column="labels")],
)
def _split_generators(self, dl_manager):
data_files = dl_manager.download_and_extract(_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"]]),
},
),
]
def _generate_examples(self, files):
for i, path in enumerate(files):
file_name = os.path.basename(path)
if file_name.endswith(".png"):
yield i, {
"image": path,
"labels": os.path.basename(os.path.dirname(path)).lower(),
}
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