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import os
from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split, Value, Features
class MyDataset(GeneratorBasedBuilder):
def _info(self):
return DatasetInfo(
description="Custom dataset with images and labels in separate folders",
features=Features({
"image": Value("string"), # filepath, will cast later
"label": Value("string")
}),
)
def _split_generators(self, dl_manager):
data_dir = self.config.data_dir or ""
return [
SplitGenerator(name=Split.TRAIN, gen_kwargs={"split_dir": os.path.join(data_dir, "train")}),
SplitGenerator(name=Split.TEST, gen_kwargs={"split_dir": os.path.join(data_dir, "test")}),
]
def _generate_examples(self, split_dir):
image_dir = os.path.join(split_dir, "images")
label_dir = os.path.join(split_dir, "labels")
idx = 0
for image_name in sorted(os.listdir(image_dir)):
if not image_name.lower().endswith((".jpg", ".png", ".jpeg")):
continue
image_path = os.path.join(image_dir, image_name)
label_path = os.path.join(label_dir, os.path.splitext(image_name)[0] + ".txt")
if not os.path.exists(label_path):
continue
with open(label_path, "r") as f:
label = f.read().strip()
yield idx, {
"image": image_path,
"label": label,
}
idx += 1 |