# 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,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Blurs 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
"""Blurs area bounded by bounding boxes on image.
The :mod:`draw.blur_bbox` node blurs the areas of the image bounded by the
bounding boxes output from an object detection model.
Inputs:
|img_data|
|bboxes_data|
Outputs:
|img_data|
Configs:
blur_kernel_size (:obj:`int`): **default = 50**. |br|
This defines the kernel size used in the blur filter. Larger values
of ``blur_kernel_size`` gives more intense blurring.
"""
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]:
"""Reads the image input and returns the image, with the areas bounded
by the bboxes blurred.
Args:
inputs (dict): Dictionary of inputs with keys "img", "bboxes"
Returns:
outputs (dict): Output in dictionary format with key "img"
"""
blurred_img = self._blur_bbox(inputs["img"], inputs["bboxes"])
outputs = {"img": blurred_img}
return outputs
def _blur_bbox(self, image: np.ndarray, bboxes: List[np.ndarray]) -> np.ndarray:
"""Blurs 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 blurred bounding box regions.
"""
height = image.shape[0]
width = image.shape[1]
for bbox in bboxes:
x_1, y_1, x_2, y_2 = bbox
y_1, y_2 = int(y_1 * height), int(y_2 * height)
x_1, x_2 = int(x_1 * width), int(x_2 * width)
# to get the area bounded by bbox
bbox_image = image[y_1:y_2, x_1:x_2, :]
# apply the blur using blur filter from opencv
blur_bbox_image = cv2.blur(
bbox_image, (self.blur_kernel_size, self.blur_kernel_size)
)
image[y_1:y_2, x_1:x_2, :] = blur_bbox_image
return image
def _get_config_types(self) -> Dict[str, Any]:
"""Returns dictionary mapping the node's config keys to respective types."""
return {"blue_kernel_size": int}