def METHOD_NAME(
    self,
    file_path: Path,
    meta: Optional[Dict[str, str]] = None,
    remove_numeric_tables: Optional[bool] = None,
    valid_languages: Optional[List[str]] = None,
    encoding: Optional[str] = "utf-8",
    **kwargs: Any,
) -> List[Dict[str, Any]]:
    """
    Extract text from image file using the pytesseract library (https://github.com/madmaze/pytesseract)
    :param file_path: path to image file
    :param meta: Optional dictionary with metadata that shall be attached to all resulting documents.
                 Can be any custom keys and values.
    :param remove_numeric_tables: This option uses heuristics to remove numeric rows from the tables.
                                  The tabular structures in documents might be noise for the reader model if it
                                  does not have table parsing capability for finding answers. However, tables
                                  may also have long strings that could possible candidate for searching answers.
                                  The rows containing strings are thus retained in this option.
    :param valid_languages: validate languages from a list of languages supported by tessarect
                            (https://tesseract-ocr.github.io/tessdoc/Data-Files-in-different-versions.html).
                            This option can be used to add test for encoding errors. If the extracted text is
                            not one of the valid languages, then it might likely be encoding error resulting
                            in garbled text.
    """
    pages = self._image_to_text(file_path)
    if remove_numeric_tables is None:
        remove_numeric_tables = self.remove_numeric_tables
    if valid_languages is None:
        valid_languages = self.valid_languages
    cleaned_pages = []
    for page in pages:
        lines = page.splitlines()
        cleaned_lines = []
        for line in lines:
            words = line.split()
            digits = [word for word in words if any(i.isdigit() for i in word)]
            # remove lines having > 40% of words as digits AND not ending with a period(.)
            if remove_numeric_tables:
                if words and len(digits) / len(words) > 0.4 and not line.strip().endswith("."):
                    logger.debug(f"Removing line '{line}' from file")
                    continue
            cleaned_lines.append(line)
        cleaned_pages.append(page)
    if valid_languages:
        document_text = "".join(cleaned_pages)
        if not self.validate_language(document_text, valid_languages):
            logger.warning(
                f"The language for image is not one of {valid_languages}. The file may not have "
                f"been decoded in the correct text format."
            )
    documents = []
    for page in cleaned_pages:
        document = {"content": page, "meta": meta}
        documents.append(document)
    return documents