import numpy as np
import numpy.typing as npt
from matplotlib import pyplot as plt
import random
import cv2
import uz_framework.image as uz_image

#################################################################
# EXCERCISE 1: Exercise 1: Global approach to image description #
#################################################################
def ex1():
    one_a()
    #one_b()

def one_a() -> npt.NDArray[np.float64]:
    """
     Firstly, you will implement the function myhist3 that computes a 3-D histogram
    from a three channel image. The images you will use are RGB, but the function
    should also work on other color spaces. The resulting histogram is stored in a 3-D
    matrix. The size of the resulting histogram is determined by the parameter n_bins.
    The bin range calculation is exactly the same as in the previous assignment, except
    now you will get one index for each image channel. Iterate through the image pixels
    and increment the appropriate histogram cells. You can create an empty 3-D numpy
    array with H = np.zeros((n_bins,n_bins,n_bins)). Take care that you normalize
    the resulting histogram.
    """
    test_image = uz_image.imread('./data/images/museum.jpg', uz_image.ImageType.float64)
    bins = uz_image.get_image_bins_ND(test_image, 10)
    return bins

def one_b():
    """
     In order to perform image comparison using histograms, we need to implement
     some distance measures. These are defined for two input histograms and return a
     single scalar value that represents the similarity (or distance) between the two histograms.
     Implement a function compare_histograms that accepts two histograms
     and a string that identifies the distance measure you wish to calculate
     Implement L2 metric, chi-square distance, intersection and Hellinger distance.
    """ 
    test_image = uz_image.imread('./data/images/museum.jpg', uz_image.ImageType.float64)
    bins = uz_image.get_image_bins_ND(test_image, 10)

    uz_image.compare_two_histograms(bins[0], bins[1], uz_image.DistanceMeasure.chi_square_distance)

# ######## #
# SOLUTION #
# ######## #

def main():
    ex1()

if __name__ == '__main__':
    main()