How to use the labelme.utils function in labelme

data = json.load(f)

            imageData = data.get('imageData')  # labelme annotated file contains source image data(serialized)
            if imageData:
                img = utils.img_b64_to_arr(imageData)
            else:
                img_file = osp.join(osp.dirname(label_file), data['imagePath'])
                img = np.asarray(PIL.Image.open(img_file))
            PIL.Image.fromarray(img).save(out_img_file)

            lbl = labelme.utils.shapes_to_label(
                img_shape=img.shape,
                shapes=data['shapes'],
                label_name_to_value=class_name_to_id,
            )
            labelme.utils.lblsave(out_png_file, lbl)

            np.save(out_lbl_file, lbl)

            viz = labelme.utils.draw_label(
                lbl, img, class_names, colormap=colormap)
            PIL.Image.fromarray(viz).save(out_viz_file)

args.output_dir,
                'SegmentationClassVisualization',
                base + '.jpg',
            )

            data = json.load(f)

            ##
            if data['imageData']:
                imageData = data['imageData']
            else:
                imagePath = os.path.join(os.path.dirname(label_file), data['imagePath'])
                with open(imagePath, 'rb') as f:
                    imageData = f.read()
                    imageData = base64.b64encode(imageData).decode('utf-8')
            img = utils.img_b64_to_arr(imageData)

            label_name_to_value = {'_background_': 0}
            for shape in sorted(data['shapes'], key=lambda x: x['label']):
                label_name = shape['label']
                if label_name in label_name_to_value:
                    label_value = label_name_to_value[label_name]
                else:
                    label_value = len(label_name_to_value)
                    label_name_to_value[label_name] = label_value
            lbl = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value)

            #lb = cv.imread(join(*[args.label_dir, f'{path.stem}.png']))
            #lb = cv.cvtColor(lb, cv.COLOR_BGR2GRAY)
            lbl = (lbl > 0).astype(np.uint8) * 255
            lbl = cv.morphologyEx(src=lbl, op=cv.MORPH_DILATE, kernel=cv.getStructuringElement(cv.MORPH_RECT, (20, 20)))

def load_image_file(filename):
        try:
            image_pil = PIL.Image.open(filename)
        except IOError:
            logger.error('Failed opening image file: {}'.format(filename))
            return

        # apply orientation to image according to exif
        image_pil = utils.apply_exif_orientation(image_pil)

        with io.BytesIO() as f:
            ext = osp.splitext(filename)[1].lower()
            if PY2 and QT4:
                format = 'PNG'
            elif ext in ['.jpg', '.jpeg']:
                format = 'JPEG'
            else:
                format = 'PNG'
            image_pil.save(f, format=format)
            f.seek(0)
            return f.read()

'imageData',
            'imagePath',
            'lineColor',
            'fillColor',
            'shapes',  # polygonal annotations
            'flags',   # image level flags
            'imageHeight',
            'imageWidth',
        ]
        try:
            with open(filename, 'rb' if PY2 else 'r') as f:
                data = json.load(f)
            if data['imageData'] is not None:
                imageData = base64.b64decode(data['imageData'])
                if PY2 and QT4:
                    imageData = utils.img_data_to_png_data(imageData)
            else:
                # relative path from label file to relative path from cwd
                imagePath = osp.join(osp.dirname(filename), data['imagePath'])
                imageData = self.load_image_file(imagePath)
            flags = data.get('flags') or {}
            imagePath = data['imagePath']
            self._check_image_height_and_width(
                base64.b64encode(imageData).decode('utf-8'),
                data.get('imageHeight'),
                data.get('imageWidth'),
            )
            lineColor = data['lineColor']
            fillColor = data['fillColor']
            shapes = (
                (
                    s['label'],