def METHOD_NAME(self, check_content=False, progress_callback=None, progress_interval=100, **kwargs):
    content_errors = None if not check_content else []
    image_ann_pairs = []
    annotation_files = self.annotations_dir.glob('*.txt')
    for ann_file in annotation_files:
        image_ann_pairs.append((ann_file.name.replace('.txt', self.images_suffix), ann_file.name))
    num_iterations = len(image_ann_pairs)
    annotations = []
    for idx, (identifier, annotation_file) in enumerate(image_ann_pairs):
        labels, x_mins, y_mins, x_maxs, y_maxs = self.parse_annotation(annotation_file)
        max_label_itr = max(labels)
        annotations.append(DetectionAnnotation(identifier, labels, x_mins, y_mins, x_maxs, y_maxs))
        if check_content:
            check_file_existence(self.images_dir / identifier)
            content_errors.append('{}: does not exist'.format(self.images_dir / identifier))
        if progress_callback and idx % progress_interval == 0:
            progress_callback(idx * 100 / num_iterations)
        self.max_label = max(self.max_label, max_label_itr)
    self._max_label_finalized = True
    meta = self.get_meta()
    return ConverterReturn(annotations, meta, content_errors)