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main.py: creates objects and variables necessary for the another file.

#!/usr/bin/env python3
#-*- coding: utf-8 -*-
#˅
from MaskCreator import MaskCreator
from ConfigReader import ConfigReader
from MainDisplay import MainDisplay

# creating object for MainDisplay, ConfigReader classes

# change to config_left.ini or config_right.ini when necessary
CReader = ConfigReader("config_left.ini")
# CReader = ConfigReader("config_right.ini")
MDisplay = MainDisplay()

# initializing variables
mask_width = CReader.getProjectedOverlapWidth()
image_width = CReader.getProjectedImageWidth()
gamma = CReader.getGamma()
image_side = CReader.getImageSide()
image_path = CReader.getImageName()

if image_side == 0:
    image_name = 'left'
elif image_side == 1:
    image_name = 'right'
else:
    print("Invalid ImageSide value in config.ini. Use 0 for left image, 1 for right image.")

# loading image
image = MDisplay.readImage(image_path)
result_image = MDisplay.setImage(image)

if image is not None:
    # creating object for MaskCreator class
    MCreator = MaskCreator(image)

    # image modification
    MCreator.create_mask(image_side, mask_width, image_width)
    MCreator.gammaCorrection(gamma)
    MCreator.result_image = result_image
    MCreator.alpha_blending(image_side)
    MCreator.mod_intensity(image_side)

    # saving image
    MDisplay.saveImage()
else:
    print(f"Failed to read the image (ImageSide={image_side}).")

MaskCreator.py: creates objects and variables necessary for the other file.

import cv2
import numpy as np

class MaskCreator:
    """ 
    @brief The MaskCreator class performs image modification, including creating masks, gamma correction, alpha blending, and intensity modification.

    @details
    The class includes methods for:
    - Creating masks based on specified parameters.
    - Applying gamma correction to the image.
    - Performing alpha blending on the image based on the image side.
    - Modifying image intensity based on the image side.

    @note
    Ensure that the OpenCV library is installed (`pip install opencv-python`) before using this class.

    @date January 18, 2024
    """ 

    def __init__(self, image):
        """ 
        @brief Initializes a MaskCreator object.

        @param image: The input image on which modifications will be applied.
        """ 
        self.__image = image
        self.__alpha_gradient = None
        self.__gamma_corrected = None
        self.result_image = None
        self.__mask = None

    def create_mask(self, image_side, mask_width, image_width):
        """ 
        @brief Creates a mask based on specified parameters.

        @param image_side: The side of the image (0 for left, 1 for right).
        @param mask_width: The width of the mask.
        @param image_width: The width of the input image.
        """ 
        self.__mask = self.__image.shape[1] * mask_width // image_width
        if image_side == 1:
            self.__alpha_gradient = np.linspace(1, 0, self.__mask)
        elif image_side == 0:
            self.__alpha_gradient = np.linspace(0, 1, self.__mask)

    def gammaCorrection(self, gamma):
        """ 
        @brief Applies gamma correction to the image.

        @param gamma: The gamma value for correction.
        """ 
        self.__gamma_corrected = np.uint8(cv2.pow(self.__image / 255.0, gamma) * 255)

    def alpha_blending(self, image_side):
        """ 
        @brief Performs alpha blending on the image based on the image side.

        @param image_side: The side of the image (0 for left, 1 for right).
        """ 
        if image_side == 1:
            for col in range(self.__mask):
                alpha = self.__alpha_gradient[-self.__mask + col]
                self.result_image[:, col] = alpha * self.__gamma_corrected[:, col] + (1 - alpha) * self.result_image[:, col]
        elif image_side == 0:
            for col in range(self.__mask):
                alpha = self.__alpha_gradient[-self.__mask + col]
                self.result_image[:, -self.__mask + col] = alpha * self.__gamma_corrected[:, -self.__mask + col] + (1 - alpha) * self.result_image[:, -self.__mask + col]

    def mod_intensity(self, image_side):
        """ 
        @brief Modifies image intensity based on the image side.

        @param image_side: The side of the image (0 for left, 1 for right).
        """ 
        if image_side == 1:
            for col in range(self.__mask):
                intensity_factor = 1.0 - (self.__mask - col) / self.__mask
                self.result_image[:, col] = (self.result_image[:, col] * intensity_factor).astype(np.uint8)
        elif image_side == 0:
            for col in range(self.__mask):
                intensity_factor = 1.0 - col / self.__mask
                self.result_image[:, -self.__mask + col] = (self.result_image[:, -self.__mask + col] * intensity_factor).astype(np.uint8)

ConfigReader.py: For reading file's configuration parameters¶

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
""" 
@file
@brief This script defines the MainDisplay class, which handles reading, setting, and displaying images using the OpenCV library.

@date January 18, 2024
""" 

import cv2

class MainDisplay:
    """ 
    @brief The MainDisplay class provides functionalities for image handling and display.

    @details
    The class includes methods for:
    - Reading an image from a specified path.
    - Setting the result image.
    - Displaying the result image using the OpenCV library.

    @note
    Ensure that the OpenCV library is installed (`pip install opencv-python`) before using this class.

    @date January 18, 2024
    """ 

    def __init__(self):
        """ 
        @brief Initializes a MainDisplay object.

        @details
        The result_image attribute is initialized to None.
        """ 
        self.result_image = None

    def readImage(self, image_path):
        """ 
        @brief Reads an image from the specified path.

        @param image_path: The path to the image file.

        @return The read image.
        """ 
        image = cv2.imread(image_path)
        return image

    def setImage(self, image):
        """ 
        @brief Sets the result image.

        @param image: The image to set as the result image.

        @return The set result image.
        """ 
        self.result_image = image
        return self.result_image

    def saveImage(self):
        """ 
        @brief Displays and saves the result image.

        @details
        The result image is displayed in a window with the window name indicating the displayed image.
        The window remains open until a key is pressed. Then, it is closed, and the program continues.

        @note
        Ensure that the OpenCV window is closed before proceeding with the execution of other code.

        @warning
        This method uses blocking code (cv2.waitKey(0)) that might lead to issues in certain scenarios.
        """ 
        # display image. (window name, image to display)
        cv2.imshow(f"Displaying {self.result_image}", self.result_image)
        cv2.waitKey(0)
        cv2.destroyAllWindows()

mainDisplay.py: Displays the result¶

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
""" 
@file
@brief This script defines the MainDisplay class, which handles reading, setting, and displaying images using the OpenCV library.

@date January 18, 2024
""" 

import cv2

class MainDisplay:
    """ 
    @brief The MainDisplay class provides functionalities for image handling and display.

    @details
    The class includes methods for:
    - Reading an image from a specified path.
    - Setting the result image.
    - Displaying the result image using the OpenCV library.

    @note
    Ensure that the OpenCV library is installed (`pip install opencv-python`) before using this class.

    @date January 18, 2024
    """ 

    def __init__(self):
        """ 
        @brief Initializes a MainDisplay object.

        @details
        The result_image attribute is initialized to None.
        """ 
        self.result_image = None

    def readImage(self, image_path):
        """ 
        @brief Reads an image from the specified path.

        @param image_path: The path to the image file.

        @return The read image.
        """ 
        image = cv2.imread(image_path)
        return image

    def setImage(self, image):
        """ 
        @brief Sets the result image.

        @param image: The image to set as the result image.

        @return The set result image.
        """ 
        self.result_image = image
        return self.result_image

    def saveImage(self):
        """ 
        @brief Displays and saves the result image.

        @details
        The result image is displayed in a window with the window name indicating the displayed image.
        The window remains open until a key is pressed. Then, it is closed, and the program continues.

        @note
        Ensure that the OpenCV window is closed before proceeding with the execution of other code.

        @warning
        This method uses blocking code (cv2.waitKey(0)) that might lead to issues in certain scenarios.
        """ 
        # display image. (window name, image to display)
        cv2.imshow(f"Displaying {self.result_image}", self.result_image)
        cv2.waitKey(0)
        cv2.destroyAllWindows()