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import csv
import datasets
import requests
import os
from PIL import Image
from io import BytesIO
from datasets.tasks import ImageClassification
_HOMEPAGE = "https://huggingface.co/datasets/rshrott/renovation"
_CITATION = """\
@ONLINE {renovationquality,
author="Your Name",
title="Renovation Quality Dataset",
month="Your Month",
year="Your Year",
url="https://huggingface.co/datasets/rshrott/renovation"
}
"""
_DESCRIPTION = """\
This dataset contains images of various properties, along with labels indicating the quality of renovation - 'cheap', 'average', 'expensive'.
"""
_URL = "https://huggingface.co/datasets/rshrott/renovation/raw/main/labels.csv"
_NAMES = ["cheap", "average", "expensive"]
class RenovationQualityDataset(datasets.GeneratorBasedBuilder):
"""Renovation Quality Dataset."""
VERSION = datasets.Version("1.0.0")
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"image_file_path": datasets.Value("string"),
"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):
csv_path = dl_manager.download(_URL)
with open(csv_path, "r") as f:
reader = csv.reader(f)
next(reader) # skip header
rows = list(reader)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"rows": rows[:int(0.9 * len(rows))],
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"rows": rows[int(0.9 * len(rows)):],
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"rows": rows[int(0.9 * len(rows)):],
},
),
]
def _generate_examples(self, rows):
def url_to_image(url):
response = requests.get(url)
img = Image.open(BytesIO(response.content))
return img
for id_, row in enumerate(rows):
if len(row) < 2:
print(f"Row with id {id_} has less than 2 elements: {row}")
else:
image_file_path = str(row[0])
image = url_to_image(image_file_path)
yield id_, {
'image_file_path': image_file_path,
'image': image,
'labels': row[1],
}
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