Add support for annotated HOCR files

    def get_confidence(element):

        return float(len(get_element_text(element)))

    assert algorithm in ('OLDA', 'NLDA', 'paragraph', 'word')

    for paragraph in xml_document.xpath('//p[@lang]'):

        paragraph_language_code = paragraph.attrib['lang']

        paragraph_confidence = get_confidence(paragraph)

        if algorithm == 'OLDA' or algorithm == 'paragraph':

            languages[paragraph_language_code] += paragraph_confidence

        elif algorithm == 'NLDA' or algorithm == 'word':

            if not paragraph_confidence:

    assert algorithm in ('OLDA', 'NLDA', 'paragraph', 'word', 'annotated')

    if algorithm == 'annotated':

        # The annotated HOCR files produced by

        # https://gitlab.fi.muni.cz/nlp/ahisto-language-detection do not have

        # paragraph-level language annotations, so we will only consider

        # word-level annotations.

        for word in xml_document.xpath('//span[@class="ocrx_word" and @lang]'):

            word_language_code = word.attrib['lang']

            word_confidence = get_confidence(word)

            if not word_confidence:

                continue

            for word in paragraph.xpath('.//span[@class="ocrx_word" and @lang]'):

                word_language_code = word.attrib['lang']

                word_confidence = get_confidence(word)

                if not word_confidence:

            languages[word_language_code] += word_confidence

    else:

        for paragraph in xml_document.xpath('//p[@lang]'):

            paragraph_language_code = paragraph.attrib['lang']

            paragraph_confidence = get_confidence(paragraph)

            if algorithm == 'OLDA' or algorithm == 'paragraph':

                # With the old paragraph-only algorithm, we only take

                # paragraph-level language annotations into account.

                languages[paragraph_language_code] += paragraph_confidence

            elif algorithm == 'NLDA' or algorithm == 'word':

                # With the new paragraph-and-word algorithm, we take

                # both paragraph-level and word-level language annotations

                # into account.

                if not paragraph_confidence:

                    continue

                languages[word_language_code] += word_confidence

                paragraph_confidence -= word_confidence

            assert paragraph_confidence >= 0.0

            languages[paragraph_language_code] += paragraph_confidence

                for word in paragraph.xpath('.//span[@class="ocrx_word" and @lang]'):

                    word_language_code = word.attrib['lang']

                    word_confidence = get_confidence(word)

                    if not word_confidence:

                        continue

                    languages[word_language_code] += word_confidence

                    paragraph_confidence -= word_confidence

                assert paragraph_confidence >= 0.0

                languages[paragraph_language_code] += paragraph_confidence

    return languages