Source code for dtlpy.entities.annotation_definitions.segmentation

import numpy as np
import base64
import io
from PIL import Image

from . import BaseAnnotationDefinition

from .box import Box
from .polygon import Polygon

[docs]class Segmentation(BaseAnnotationDefinition): """ Segmentation annotation object """ type = "binary" def __init__(self, geo, label, attributes=None, description=None): super().__init__(description=description, attributes=attributes) self.geo = geo self.label = label @property def x(self): return @property def y(self): return @property def pts(self): return np.where(self.geo > 0) @property def left(self): left = 0 if len(self.pts[1]) > 0: left = np.min(self.pts[1]) return left @property def top(self): top = 0 if len(self.pts[0]) > 0: top = np.min(self.pts[0]) return top @property def right(self): right = 0 if len(self.pts[1]) > 0: right = np.max(self.pts[1]) return right @property def bottom(self): bottom = 0 if len(self.pts[0]) > 0: bottom = np.max(self.pts[0]) return bottom
[docs] def show(self, image, thickness, with_text, height, width, annotation_format, color, alpha=1): """ Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray """ try: import cv2 except (ImportError, ModuleNotFoundError): raise ImportError('opencv not found. Must install to perform this function') if alpha != 1: overlay = image.copy() else: overlay = image # draw annotation overlay[np.where(self.geo)] = color if not isinstance(color, int) and len(color) == 4 and color[3] != 255: # add with opacity image = cv2.addWeighted(src1=overlay, alpha=alpha, src2=image, beta=1 - alpha, gamma=0) else: image = overlay if with_text: image = self.add_text_to_image(image=image, annotation=self) return image
def to_coordinates(self, color=None): if color is None: color = (255, 255, 255) max_val = np.max(self.geo) if max_val > 1: self.geo = self.geo / max_val png_ann = np.stack((color[0] * self.geo, color[1] * self.geo, color[2] * self.geo, 255 * self.geo), axis=2).astype(np.uint8) pil_img = Image.fromarray(png_ann) buff = io.BytesIO(), format="PNG") new_image_string = base64.b64encode(buff.getvalue()).decode("utf-8") coordinates = "data:image/png;base64,%s" % new_image_string return coordinates
[docs] def to_box(self): """ :return: Box annotations list to each separated segmentation """ polygons = Polygon.from_segmentation(mask=self.geo, label=self.label, attributes=self.attributes, max_instances=None) if not isinstance(polygons, list): polygons = [polygons] boxes = [Box(left=polygon.left,, right=polygon.right, bottom=polygon.bottom, label=polygon.label, attributes=polygon.attributes) for polygon in polygons] return boxes
[docs] @classmethod def from_polygon(cls, geo, label, shape, attributes=None): """ :param geo: list of x,y coordinates of the polygon ([[x,y],[x,y]...] :param label: annotation's label :param shape: image shape (h,w) :param attributes: :return: """ try: import cv2 except (ImportError, ModuleNotFoundError): raise ImportError('opencv not found. Must install to perform this function') thickness = -1 # plot polygon on a blank mask with thickness -1 to fill the polyline mask = np.zeros(shape=shape, dtype=np.uint8) mask = cv2.drawContours(image=mask, contours=[np.asarray(geo).astype('int')], contourIdx=-1, color=1, thickness=thickness) return cls( geo=mask, label=label, attributes=attributes, )
@staticmethod def from_coordinates(coordinates): if isinstance(coordinates, dict): data = coordinates["data"][22:] elif isinstance(coordinates, str): data = coordinates[22:] else: raise TypeError('unknown binary data type') decode = base64.b64decode(data) return np.array( @classmethod def from_json(cls, _json): if "coordinates" in _json: mask = cls.from_coordinates(_json["coordinates"]) elif "data" in _json: mask = cls.from_coordinates(_json["data"]) else: raise ValueError('can not find "coordinates" or "data" in annotation. id: {}'.format(_json["id"])) return cls( geo=(mask[:, :, 3] > 127).astype(float), label=_json["label"], attributes=_json.get("attributes", None), )