# Copyright 2022 AI Singapore
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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"""
Mosaics area bounded by bounding boxes over detected object
"""
from typing import Any, Dict, List
import cv2
import numpy as np
from peekingduck.pipeline.nodes.abstract_node import AbstractNode
[docs]class Node(AbstractNode): # pylint: disable=too-few-public-methods
"""Mosaics areas bounded by bounding boxes on image.
The :mod:`draw.mosaic_bbox` node helps to anonymize detected objects by
pixelating the areas bounded by bounding boxes in an image.
Inputs:
|img_data|
|bboxes_data|
Outputs:
|img_data|
Configs:
mosaic_level (:obj:`int`): **default = 7**. |br|
Defines the resolution of a mosaic filter (width |times| height).
The number corresponds to the number of rows and columns used to
create a mosaic. For example, the default setting
(``mosaic_level = 7``) creates a :math:`7 \\times 7` mosaic filter.
Increasing the number increases the intensity of pixelization over
an area.
"""
def __init__(self, config: Dict[str, Any] = None, **kwargs: Any) -> None:
super().__init__(config, node_path=__name__, **kwargs)
def run(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
mosaic_img = self._mosaic_bbox(inputs["img"], inputs["bboxes"])
outputs = {"img": mosaic_img}
return outputs
def _get_config_types(self) -> Dict[str, Any]:
"""Returns dictionary mapping the node's config keys to respective types."""
return {"mosaic_level": int}
def _mosaic_bbox(self, image: np.ndarray, bboxes: List[np.ndarray]) -> np.ndarray:
"""Mosaics areas bounded by bounding boxes on ``image``.
Args:
image (np.ndarray): Image in numpy array.
bboxes (List[np.ndarray]): numpy array of detected bboxes
Returns:
(np.ndarray): Image with mosaicked bounding box regions.
"""
height, width = image.shape[:2]
# Prevent calculating mosaic on a mosaicked area
original_image = image.copy()
for bbox in bboxes:
# bbox can contain negative values sometimes, ensures the ROI
# selection is within bounds and without wrapping
rows = slice(int(max(0, bbox[1]) * height), int(min(1, bbox[3]) * height))
cols = slice(int(max(0, bbox[0]) * width), int(min(1, bbox[2]) * width))
image[rows, cols] = self._mosaic(original_image[rows, cols])
return image
def _mosaic(self, image: np.ndarray) -> np.ndarray:
"""Mosaics a given input image.
Args:
image (np.ndarray): Image in numpy array.
Returns:
(np.ndarray): Mosaicked image in numpy array.
"""
height, width = image.shape[:2]
image = cv2.resize(
image,
(self.mosaic_level, self.mosaic_level),
interpolation=cv2.INTER_LANCZOS4,
)
image = cv2.resize(image, (width, height), interpolation=cv2.INTER_NEAREST)
return image