import os
from PIL import Image, ImageChops, ImageStat

def get_gimp_export_path():
    # Path to GIMP's configuration file. This example assumes GIMP version 2.10.
    # You need to adjust the path according to the GIMP version and user's file system.
    gimp_config_file = os.path.expanduser("~/.config/GIMP/2.10/gimprc")

    try:
        # Open and read the configuration file
        with open(gimp_config_file, 'r') as file:
            for line in file:
                # Search for the default export path setting
                if "default-export-path" in line:
                    # Extract the current path from the line (assuming it's enclosed in quotes)
                    current_path = line.split('"')[1]
                    # Compare the current path with the expected path
                    return current_path
    except FileNotFoundError:
        # Handle the case where the configuration file is not found
        print("GIMP configuration file not found")
        return False
    
def check_file_exists(directory, filename):
    file_path = os.path.join(directory, filename)
    return 1 if os.path.isfile(file_path) else 0

def increase_saturation(image1_path: str, image2_path: str) -> float:
    def calculate_saturation(image):
        # convert the image to HSV mode
        hsv_image = image.convert("HSV")

        saturation_channel = hsv_image.split()[1]

        # calculate the mean saturation level
        stat = ImageStat.Stat(saturation_channel)
        mean_saturation = stat.mean[0]

        return mean_saturation

    image1 = Image.open(image1_path)
    image2 = Image.open(image2_path)

    # calculate the saturation level of each image
    saturation1 = calculate_saturation(image1)
    saturation2 = calculate_saturation(image2)

    return 1 if saturation1 < saturation2 else 0

def decrease_brightness(image1_path: str, image2_path: str) -> float:
    def calculate_brightness(image):
        # Convert the image to grayscale mode
        grayscale_image = image.convert("L")

        # Get the image data
        pixels = list(grayscale_image.getdata())

        brightness = sum(pixels) / len(pixels)
        return brightness

    image1 = Image.open(image1_path)
    image2 = Image.open(image2_path)

    brightness1 = calculate_brightness(image1)
    brightness2 = calculate_brightness(image2)

    return 1 if brightness1 > brightness2 else 0
import cv2
import numpy as np

def find_yellow_triangle(image):
    # Convert the image to RGBA
    rgba = cv2.cvtColor(image, cv2.COLOR_BGR2RGBA)

    # define range of yellow color in HSV
    lower_yellow = np.array([0, 0, 0], dtype=np.uint8)
    upper_yellow = np.array([255, 255, 255], dtype=np.uint8)

    # expand the dimensions of lower and upper yellow to match the image dimensions
    lower_yellow = np.reshape(lower_yellow, (1, 1, 3))
    upper_yellow = np.reshape(upper_yellow, (1, 1, 3))
    # build a mask for the yellow color
    mask = cv2.inRange(rgba, lower_yellow, upper_yellow)

    # search for contours in the mask
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # choose the largest contour
    max_contour = max(contours, key=cv2.contourArea)

    # calculate the center of the contour
    M = cv2.moments(max_contour)
    cx = int(M['m10'] / M['m00'])
    cy = int(M['m01'] / M['m00'])

    return cx, cy

def compare_triangle_positions(image1, image2):
    image1 = cv2.imread(image1, cv2.IMREAD_COLOR)
    image2 = cv2.imread(image2, cv2.IMREAD_COLOR)
    # find the center of the yellow triangle in each image
    cx1, cy1 = find_yellow_triangle(image1)
    cx2, cy2 = find_yellow_triangle(image2)

    # calculate the distance between the center of the triangle and the center of the image
    center_distance1 = np.sqrt((cx1 - image1.shape[1] // 2)**2 + (cy1 - image1.shape[0] // 2)**2)
    center_distance2 = np.sqrt((cx2 - image2.shape[1] // 2)**2 + (cy2 - image2.shape[0] // 2)**2)

    return 1 if center_distance1 > center_distance2 else 0


if __name__ == "__main__":
    image1_path = "../Downloads/1.png"
    image2_path = "../Downloads/edited_darker.png"

    decrease_brightness(image1_path, image2_path)

    increase_saturation(image1_path, image2_path)