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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""TODO."""
import os
from pathlib import Path
import pandas as pd
import datasets
_CITATION = """TODO"""
_DESCRIPTION = """\
TODO
"""
_HOMEPAGE = "https://doi.org/10.25573/data.17314730.v1"
_LICENSE = "CC BY 4.0"
_URLS = {
"images": "https://smithsonian.figshare.com/ndownloader/files/31975544",
}
class AmazonianFish(datasets.GeneratorBasedBuilder):
"""TODO"""
VERSION = datasets.Version("1.1.0")
def _info(self):
features = datasets.Features(
{
"image": datasets.Image(),
"label": datasets.ClassLabel(
names=[
"Ancistrus",
"Apistogramma",
"Astyanax",
"Bario",
"Bryconops",
"Bujurquina",
"Bunocephalus",
"Characidium",
"Charax",
"Copella",
"Corydoras",
"Creagrutus",
"Curimata",
"Doras",
"Erythrinus",
"Gasteropelecus",
"Gymnotus",
"Hemigrammus",
"Hyphessobrycon",
"Knodus",
"Moenkhausia",
"Otocinclus",
"Oxyropsis",
"Phenacogaster",
"Pimelodella",
"Prochilodus",
"Pygocentrus",
"Pyrrhulina",
"Rineloricaria",
"Sorubim",
"Tatia",
"Tetragonopterus",
"Tyttocharax",
]
),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
images = dl_manager.download_and_extract(_URLS["images"])
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"images": os.path.join(images,"training_images"),
},
),
]
def _generate_examples(self, images):
id_ = 0
for example in Path(images).rglob("*.jpg"):
if example.name.startswith("._"):
continue
id_ += 1
yield id_, {"image": str(example), "label": example.parent.name} |