How to use the imgviz.label2rgb function in imgviz

def test_label2rgb():
    data = imgviz.data.arc2017()
    H, W = data["class_label"].shape[:2]

    labelviz = imgviz.label2rgb(label=data["class_label"])
    assert labelviz.dtype == np.uint8
    assert labelviz.shape == (H, W, 3)

    labelviz = imgviz.label2rgb(label=data["class_label"], img=data["rgb"])
    assert labelviz.dtype == np.uint8
    assert labelviz.shape == (H, W, 3)

    labelviz = imgviz.label2rgb(
        label=data["class_label"],
        img=data["rgb"],
        label_names=data["class_names"],
    )
    assert labelviz.dtype == np.uint8
    assert labelviz.shape == (H, W, 3)

def test_label2rgb():
    data = imgviz.data.arc2017()
    H, W = data["class_label"].shape[:2]

    labelviz = imgviz.label2rgb(label=data["class_label"])
    assert labelviz.dtype == np.uint8
    assert labelviz.shape == (H, W, 3)

    labelviz = imgviz.label2rgb(label=data["class_label"], img=data["rgb"])
    assert labelviz.dtype == np.uint8
    assert labelviz.shape == (H, W, 3)

    labelviz = imgviz.label2rgb(
        label=data["class_label"],
        img=data["rgb"],
        label_names=data["class_names"],
    )
    assert labelviz.dtype == np.uint8
    assert labelviz.shape == (H, W, 3)

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)

            if not args.noviz:
                viz = imgviz.label2rgb(
                    label=lbl,
                    img=imgviz.rgb2gray(img),
                    font_size=15,
                    label_names=class_names,
                    loc='rb',
                )
                imgviz.io.imsave(out_viz_file, viz)

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)

    label_names = [None] * (max(label_name_to_value.values()) + 1)
    for name, value in label_name_to_value.items():
        label_names[value] = name
    lbl_viz = imgviz.label2rgb(
        label=lbl, img=imgviz.rgb2gray(img), label_names=label_names, loc='rb'
    )

    PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
    utils.lblsave(osp.join(out_dir, 'label.png'), lbl)
    PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))

    with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
        for lbl_name in label_names:
            f.write(lbl_name + '\n')

    logger.warning('info.yaml is being replaced by label_names.txt')
    info = dict(label_names=label_names)
    with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
        yaml.safe_dump(info, f, default_flow_style=False)

def label2rgb():
    data = imgviz.data.voc()

    rgb = data["rgb"]
    label = data["class_label"]

    label_names = [
        "{}:{}".format(i, n) for i, n in enumerate(data["class_names"])
    ]
    labelviz_withname1 = imgviz.label2rgb(
        label, label_names=label_names, font_size=25
    )
    labelviz_withname2 = imgviz.label2rgb(
        label, label_names=label_names, font_size=25, loc="rb"
    )
    img = imgviz.color.rgb2gray(rgb)
    labelviz_withimg = imgviz.label2rgb(label, img=img)

    # -------------------------------------------------------------------------

    plt.figure(dpi=200)

    plt.subplot(131)
    plt.title("+img")
    plt.imshow(labelviz_withimg)
    plt.axis("off")

img = np.asarray(PIL.Image.open(img_file))
            PIL.Image.fromarray(img).save(out_img_file)

            cls, ins = labelme.utils.shapes_to_label(
                img_shape=img.shape,
                shapes=data['shapes'],
                label_name_to_value=class_name_to_id,
                type='instance',
            )
            ins[cls == -1] = 0  # ignore it.

            # class label
            labelme.utils.lblsave(out_clsp_file, cls)
            np.save(out_cls_file, cls)
            if not args.noviz:
                clsv = imgviz.label2rgb(
                    label=cls,
                    img=imgviz.rgb2gray(img),
                    label_names=class_names,
                    font_size=15,
                    loc='rb',
                )
                imgviz.io.imsave(out_clsv_file, clsv)

            # instance label
            labelme.utils.lblsave(out_insp_file, ins)
            np.save(out_ins_file, ins)
            if not args.noviz:
                instance_ids = np.unique(ins)
                instance_names = [str(i) for i in range(max(instance_ids) + 1)]
                insv = imgviz.label2rgb(
                    label=ins,

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)

    label_names = [None] * (max(label_name_to_value.values()) + 1)
    for name, value in label_name_to_value.items():
        label_names[value] = name
    lbl_viz = imgviz.label2rgb(
        label=lbl,
        img=imgviz.rgb2gray(img),
        label_names=label_names,
        font_size=30,
        loc='rb',
    )

    plt.subplot(121)
    plt.imshow(img)
    plt.subplot(122)
    plt.imshow(lbl_viz)
    plt.show()

clsv = imgviz.label2rgb(
                    label=cls,
                    img=imgviz.rgb2gray(img),
                    label_names=class_names,
                    font_size=15,
                    loc='rb',
                )
                imgviz.io.imsave(out_clsv_file, clsv)

            # instance label
            labelme.utils.lblsave(out_insp_file, ins)
            np.save(out_ins_file, ins)
            if not args.noviz:
                instance_ids = np.unique(ins)
                instance_names = [str(i) for i in range(max(instance_ids) + 1)]
                insv = imgviz.label2rgb(
                    label=ins,
                    img=imgviz.rgb2gray(img),
                    label_names=instance_names,
                    font_size=15,
                    loc='rb',
                )
                imgviz.io.imsave(out_insv_file, insv)

def get_images():
    data = imgviz.data.arc2017()
    yield data["rgb"]
    yield imgviz.depth2rgb(data["depth"], min_value=0.3, max_value=1)
    yield imgviz.label2rgb(data["class_label"])