Datasets:
Tasks:
Image Segmentation
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
1K<n<10K
License:
File size: 1,753 Bytes
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import os
import datasets
class Demo(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features({
"id": datasets.Value("string"),
"problem": datasets.Value("string"),
"solution": datasets.Value("string"),
"image": datasets.Image(), # Enables image previews
"img_height": datasets.Value("int32"),
"img_width": datasets.Value("int32"),
}),
)
def _split_generators(self, dl_manager):
# Get the data files from the config
data_files = dl_manager.download_and_extract(self.config.data_files)
base_path = dl_manager.download_and_extract(".")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": data_files["train"], "base_path": base_path}
),
]
def _generate_examples(self, filepath, base_path):
import pandas as pd
df = pd.read_parquet(filepath)
for idx, row in df.iterrows():
# Handle image path correctly
if isinstance(row["image"], dict) and "path" in row["image"]:
image_path = os.path.join(base_path, row["image"]["path"])
else:
image_path = str(row["image"])
yield idx, {
"id": str(row["id"]),
"problem": str(row["problem"]),
"solution": str(row["solution"]),
"image": image_path, # Full path to the image
"img_height": int(row["img_height"]),
"img_width": int(row["img_width"]),
} |