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# coding=utf-8
# Copyright 2022 the HuggingFace Datasets Authors.
#
# 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.
# This script was modified from the imagenet-1k HF dataset repo
import os
import datasets
from datasets.tasks import ImageClassification
from .classes import IMAGENET2012_CLASSES
_CITATION = """\
@article{BibTeX
}
"""
_HOMEPAGE = "https://arielnlee.github.io/PatchMixing/"
_DESCRIPTION = """\
SMD is an occluded ImageNet-1K validation set, created to be an additional way to evaluate the impact of occlusion on model performance. This experiment used a variety of occluder objects that are not in the ImageNet-1K label space and are unambiguous in relationship to objects that reside in the label space.
"""
_DATA_URL = {
"rod": [
f"https://huggingface.co/datasets/ariellee/Superimposed-Masked-Dataset/resolve/main/smd_{i}.tar.gz"
for i in range(1, 41)
]
}
class SMD(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
DEFAULT_WRITER_BATCH_SIZE = 1000
def _info(self):
assert len(IMAGENET2012_CLASSES) == 1000
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"image": datasets.Image(),
"label": datasets.ClassLabel(names=list(IMAGENET2012_CLASSES.values())),
}
),
homepage=_HOMEPAGE,
citation=_CITATION,
task_templates=[ImageClassification(image_column="image", label_column="label")],
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
archives = dl_manager.download(_DATA_URL)
return [
datasets.SplitGenerator(
name="SMD", # "SMD (occluded IN-1K val set)"
gen_kwargs={
"archives": [dl_manager.iter_archive(archive) for archive in archives["smd"]],
},
),
]
def _generate_examples(self, archives):
"""Yields examples."""
idx = 0
for archive in archives:
for path, file in archive:
if path.endswith(".png"):
synset_id = os.path.basename(os.path.dirname(path))
label = IMAGENET2012_CLASSES[synset_id]
ex = {"image": {"path": path, "bytes": file.read()}, "label": label}
yield idx, ex
idx += 1 |