labelmeWithAI/labelme/utils.py

import base64
import io
import warnings

import numpy as np
import PIL.Image
import PIL.ImageDraw


def label_colormap(N=256):

    def bitget(byteval, idx):
        return ((byteval & (1 << idx)) != 0)

    cmap = np.zeros((N, 3))
    for i in range(0, N):
        id = i
        r, g, b = 0, 0, 0
        for j in range(0, 8):
            r = np.bitwise_or(r, (bitget(id, 0) << 7 - j))
            g = np.bitwise_or(g, (bitget(id, 1) << 7 - j))
            b = np.bitwise_or(b, (bitget(id, 2) << 7 - j))
            id = (id >> 3)
        cmap[i, 0] = r
        cmap[i, 1] = g
        cmap[i, 2] = b
    cmap = cmap.astype(np.float32) / 255
    return cmap


def labelcolormap(N=256):
    warnings.warn('labelcolormap is deprecated. Please use label_colormap.')
    return label_colormap(N=N)


# similar function as skimage.color.label2rgb
def label2rgb(lbl, img=None, n_labels=None, alpha=0.3, thresh_suppress=0):
    if n_labels is None:
        n_labels = len(np.unique(lbl))

    cmap = label_colormap(n_labels)
    cmap = (cmap * 255).astype(np.uint8)

    lbl_viz = cmap[lbl]
    lbl_viz[lbl == -1] = (0, 0, 0)  # unlabeled

    if img is not None:
        img_gray = PIL.Image.fromarray(img).convert('LA')
        img_gray = np.asarray(img_gray.convert('RGB'))
        # img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
        # img_gray = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2RGB)
        lbl_viz = alpha * lbl_viz + (1 - alpha) * img_gray
        lbl_viz = lbl_viz.astype(np.uint8)

    return lbl_viz


def img_b64_to_array(img_b64):
    warnings.warn('img_ba64_to_array is deprecated. '
                  'Please use img_b64_to_arr.')
    return img_b64_to_arr(img_b64)


def img_b64_to_arr(img_b64):
    f = io.BytesIO()
    f.write(base64.b64decode(img_b64))
    img_arr = np.array(PIL.Image.open(f))
    return img_arr


def img_arr_to_b64(img_arr):
    img_pil = PIL.Image.fromarray(img_arr)
    f = io.BytesIO()
    img_pil.save(f, format='PNG')
    img_bin = f.getvalue()
    img_b64 = base64.encodestring(img_bin)
    return img_b64


def polygons_to_mask(img_shape, polygons):
    mask = np.zeros(img_shape[:2], dtype=np.uint8)
    mask = PIL.Image.fromarray(mask)
    xy = list(map(tuple, polygons))
    PIL.ImageDraw.Draw(mask).polygon(xy=xy, outline=1, fill=1)
    mask = np.array(mask, dtype=bool)
    return mask


def draw_label(label, img, label_names, colormap=None):
    import matplotlib.pyplot as plt
    backend_org = plt.rcParams['backend']
    plt.switch_backend('agg')

    plt.subplots_adjust(left=0, right=1, top=1, bottom=0,
                        wspace=0, hspace=0)
    plt.margins(0, 0)
    plt.gca().xaxis.set_major_locator(plt.NullLocator())
    plt.gca().yaxis.set_major_locator(plt.NullLocator())

    if colormap is None:
        colormap = label_colormap(len(label_names))

    label_viz = label2rgb(label, img, n_labels=len(label_names))
    plt.imshow(label_viz)
    plt.axis('off')

    plt_handlers = []
    plt_titles = []
    for label_value, label_name in enumerate(label_names):
        if label_value not in label:
            continue
        if label_name.startswith('_'):
            continue
        fc = colormap[label_value]
        p = plt.Rectangle((0, 0), 1, 1, fc=fc)
        plt_handlers.append(p)
        plt_titles.append(label_name)
    plt.legend(plt_handlers, plt_titles, loc='lower right', framealpha=.5)

    f = io.BytesIO()
    plt.savefig(f, bbox_inches='tight', pad_inches=0)
    plt.cla()
    plt.close()

    plt.switch_backend(backend_org)

    out_size = (img.shape[1], img.shape[0])
    out = PIL.Image.open(f).resize(out_size, PIL.Image.BILINEAR).convert('RGB')
    out = np.asarray(out)
    return out


def shapes_to_label(img_shape, shapes, label_name_to_value, type='class'):
    assert type in ['class', 'instance']

    cls = np.zeros(img_shape[:2], dtype=np.int32)
    if type == 'instance':
        ins = np.zeros(img_shape[:2], dtype=np.int32)
        instance_names = ['__background__']
    for shape in shapes:
        polygons = shape['points']
        label = shape['label']
        if type == 'class':
            cls_name = label
        elif type == 'instance':
            cls_name = label.split('-')[0]
            if label not in instance_names:
                instance_names.append(label)
            ins_id = len(instance_names) - 1
        cls_id = label_name_to_value[cls_name]
        mask = polygons_to_mask(img_shape[:2], polygons)
        cls[mask] = cls_id
        if type == 'instance':
            ins[mask] = ins_id

    if type == 'instance':
        return cls, ins
    return cls


def labelme_shapes_to_label(img_shape, shapes):
    warnings.warn('labelme_shapes_to_label is deprecated, so please use '
                  'shapes_to_label.')

    label_name_to_value = {}
    for shape in shapes:
        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 = shapes_to_label(img_shape, shapes, label_name_to_value)
    return lbl, label_name_to_value