Datasets:
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import datasets
import logging
# Configure logging
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
class ForestSegmentationDataset(datasets.GeneratorBasedBuilder):
def _info(self):
logger.info("Defining dataset schema...")
return datasets.DatasetInfo(
features=datasets.Features({
"sample_id": datasets.Value("string"),
"image_paths": datasets.Sequence(datasets.Value("string")),
"mask": datasets.Value("string"),
}),
)
def _split_generators(self, dl_manager):
logger.info("Loading sample stream from index.parquet...")
sample_stream = dl_manager.iter_parquet("index.parquet")
logger.info("Sample stream loaded successfully.")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"samples": sample_stream}
)
]
def _generate_examples(self, samples):
logger.info("Starting to generate examples...")
for i, sample in enumerate(samples):
if i % 1000 == 0:
logger.info(f"Processed {i} samples...")
try:
yield sample["sample_id"], {
"sample_id": sample["sample_id"],
"image_paths": sample["image_paths"],
"mask": sample["mask_path"],
}
except Exception as e:
logger.error(f"Error processing sample {sample.get('sample_id', 'unknown')}: {e}")
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