def to_argilla(hf_dataset: "HFDataset", mapper: "IngestedRecordMapper") -> "HFDataset":
        """Check if the Hugging Face dataset contains image features.

        Parameters:
            hf_dataset (HFDataset): The Hugging Face dataset to check.

        Returns:
            bool: True if the Hugging Face dataset contains image features, False otherwise.
        """
        id_column_name = mapper.mapping.id.source
        if id_column_name not in hf_dataset.column_names:
            split = hf_dataset.split
            warnings.warn(
                message="Record id column not found in Hugging Face dataset. "
                "Using row index and split for record ids.",
            )

            hf_dataset = hf_dataset.map(
                lambda row, idx: {id_column_name: f"{split}_{idx}"},
                with_indices=True,
            )

        image_columns = []
        class_label_columns = []
        class_label_sequence_columns = []

        for name, feature in hf_dataset.features.items():
            if isinstance(feature, Image):
                image_columns.append(name)
            elif isinstance(feature, ClassLabel):
                class_label_columns.append(name)
            elif isinstance(feature, Sequence) and isinstance(feature.feature, ClassLabel):
                class_label_sequence_columns.append(name)

        if image_columns:
            hf_dataset = _cast_images_as_urls(hf_dataset, image_columns)

        if class_label_columns:
            hf_dataset = _cast_classlabels_as_strings(hf_dataset, class_label_columns)

        if class_label_sequence_columns:
            hf_dataset = _cast_class_label_sequence_as_string_list(hf_dataset, class_label_sequence_columns)

        return hf_dataset
Check if the Hugging Face dataset contains image features.

        Parameters:
            hf_dataset (HFDataset): The Hugging Face dataset to check.

        Returns:
            bool: True if the Hugging Face dataset contains image features, False otherwise.
        
argilla/src/argilla/records/_io/_datasets.py