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shoe41k / script.py

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	# coding=utf-8
	# Copyright 2021 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.
	"""Dataset class for Shoe40k dataset."""

	import datasets
	from datasets.tasks import ImageClassification
	import pandas as pd
	import json
	import requests


	_HOMEPAGE = "https://huggingface.co/datasets/aidystark/shoe41k"

	_DESCRIPTION = (
	"----------------------------------------"
	)

	_CITATION = """\

	"""

	_LICENSE = """\
	LICENSE AGREEMENT
	=================
	"""

	_NAMES = ['Dressing Shoe', 'Boot', 'Crocs', 'Heels', 'Sandals', 'Sneakers']
	_CSV = "https://huggingface.co/datasets/aidystark/shoe41k/resolve/main/FOOT40K.csv"
	_URL = "https://huggingface.co/datasets/aidystark/shoe41k/resolve/main/shoe40k"



	df = pd.read_csv(_CSV)
	imgLabels = df['Label']


	class shoe40k(datasets.GeneratorBasedBuilder):
	"""-------"""

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"image": datasets.Image(),
	"label": datasets.ClassLabel(names=_NAMES),
	}
	),
	supervised_keys=("image", "label"),
	homepage=_HOMEPAGE,
	citation=_CITATION,
	license=_LICENSE,
	task_templates=[ImageClassification(image_column="image", label_column="label")],
	)

	def _split_generators(self, dl_manager):
	path = dl_manager.download(_URL)
	image_iters = dl_manager.iter_archive(path)
	return [datasets.SplitGenerator(datasets.Split.TRAIN,gen_kwargs={"images":image_iters,})]


	def _generate_examples(self, images):
	"""Generate images and labels for splits."""
	idx = 0
	#Iterate through images
	for filepath,image in images:
	yield idx, {
	"image":{"path":filepath, "bytes":image.read()},
	"label":imgLabels[idx]
	}
	idx += 1