labelmeWithAI/labelme/utils/shape.py

import math

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

from labelme import logger


def polygons_to_mask(img_shape, polygons, shape_type=None):
    logger.warning(
        "The 'polygons_to_mask' function is deprecated, "
        "use 'shape_to_mask' instead."
    )
    return shape_to_mask(img_shape, points=polygons, shape_type=shape_type)


def shape_to_mask(img_shape, points, shape_type=None):
    mask = np.zeros(img_shape[:2], dtype=np.uint8)
    mask = PIL.Image.fromarray(mask)
    draw = PIL.ImageDraw.Draw(mask)
    if shape_type == 'circle' and len(points) == 2:
        (cx, cy), (px, py) = points
        d = math.sqrt((cx - px) ** 2 + (cy - py) ** 2)
        draw.ellipse([cx - d, cy - d, cx + d, cy + d], outline=1, fill=1)
    elif shape_type == 'rectangle' and len(points) == 2:
        xy = [tuple(point) for point in points]
        draw.rectangle(xy, outline=1, fill=1)
    elif shape_type == 'linestrip':
        xy = [tuple(point) for point in points]
        draw.line(xy=xy, fill=1, width=10)
    else:
        xy = [tuple(point) for point in points]
        draw.polygon(xy=xy, outline=1, fill=1)
    mask = np.array(mask, dtype=bool)
    return mask


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:
        points = shape['points']
        label = shape['label']
        shape_type = shape.get('shape_type', None)
        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 = shape_to_mask(img_shape[:2], points, shape_type)
        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):
    logger.warn('labelme_shapes_to_label is deprecated, so please use '
                'shapes_to_label.')

    label_name_to_value = {'_background_': 0}
    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


def masks_to_bboxes(masks):
    if masks.ndim != 3:
        raise ValueError(
            'masks.ndim must be 3, but it is {}'
            .format(masks.ndim)
        )
    if masks.dtype != bool:
        raise ValueError(
            'masks.dtype must be bool type, but it is {}'
            .format(masks.dtype)
        )
    bboxes = []
    for mask in masks:
        where = np.argwhere(mask)
        (y1, x1), (y2, x2) = where.min(0), where.max(0) + 1
        bboxes.append((y1, x1, y2, x2))
    bboxes = np.asarray(bboxes, dtype=np.float32)
    return bboxes