Datasets:
Tasks:
Image Segmentation
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
1K<n<10K
License:
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"]), | |
} |