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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
# https://www.apache.org/licenses/LICENSE-2.0
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"""
Adjusts the brightness of an image.
"""
from typing import Any, Dict
import cv2
import numpy as np
from peekingduck.pipeline.nodes.abstract_node import AbstractNode
from peekingduck.pipeline.nodes.base import ThresholdCheckerMixin
[docs]class Node(ThresholdCheckerMixin, AbstractNode):
"""Adjusts the brightness of an image, by adding a bias/`beta parameter
<https://docs.opencv.org/4.x/d3/dc1/tutorial_basic_
linear_transform.html>`_.
Inputs:
|img_data|
Outputs:
|img_data|
Configs:
beta (:obj:`int`): **[-100, 100], default = 0**. |br|
Increasing the value of beta increases image brightness, and vice
versa.
"""
def __init__(self, config: Dict[str, Any] = None, **kwargs: Any) -> None:
super().__init__(config, node_path=__name__, **kwargs)
self.check_bounds("beta", "[-100, 100]")
def run(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
"""Adjusts the brightness of an image frame.
Args:
inputs (Dict): Inputs dictionary with the key `img`.
Returns:
(Dict): Outputs dictionary with the key `img`.
"""
orig_shape = inputs["img"].shape
img_vector = np.reshape(inputs["img"], (1, -1))
cv2.add(img_vector, self.beta, img_vector)
img = np.reshape(img_vector, orig_shape)
return {"img": img}
def _get_config_types(self) -> Dict[str, Any]:
"""Returns dictionary mapping the node's config keys to respective types."""
return {"beta": int}