Datasets:
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import datasets
import os
class BrainCancerMRIConfig(datasets.BuilderConfig):
"""BuilderConfig for Brain Cancer MRI Classification."""
def __init__(self, **kwargs):
"""BuilderConfig for the dataset.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(BrainCancerMRIConfig, self).__init__(**kwargs)
class BrainCancerMRIClassification(datasets.GeneratorBasedBuilder):
"""Brain Cancer MRI Classification dataset."""
# Define the classes for the 'label' feature
CLASSES = ['glioma', 'meningioma', 'notumor', 'pituitary']
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
# Define the features of the dataset, including the image and its corresponding label
features=datasets.Features({
"image": datasets.Image(),
"label": datasets.ClassLabel(names=self.CLASSES),
}),
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
# The data is already in the repository, so we just need the path
# `dl_manager.manual_dir` will point to the root of the dataset repository
data_dir = os.path.join(dl_manager.manual_dir or ".", "classification")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# Provide the path to the training data directory
gen_kwargs={"path": os.path.join(data_dir, "Training")},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# Provide the path to the testing data directory
gen_kwargs={"path": os.path.join(data_dir, "Testing")},
),
]
def _generate_examples(self, path):
"""This function will yield examples: a unique key and a dictionary of features."""
# Iterate over each class directory (e.g., 'glioma', 'meningioma', etc.)
for label in self.CLASSES:
class_path = os.path.join(path, label)
# Check if the class directory exists to avoid errors
if os.path.isdir(class_path):
# Iterate over each image file in the class directory
for filename in os.listdir(class_path):
image_path = os.path.join(class_path, filename)
# Check if it is a file to avoid including subdirectories
if os.path.isfile(image_path):
key = f"{label}_{filename}"
yield key, {
"image": image_path,
"label": label,
} |