Ошибка: qt.qpa.plugin. Во время компиляции проекта на Python в macOC

Приложение для конвертирования изображения в полутоновые в нём я нигде не использую qt, но ошибка каким-то образом с этим связана введите сюда описание изображения

import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats



def MSE(img1, img2):
    squared_diff = (img1 - img2) ** 2
    summed = np.sum(squared_diff)
    num_pix = img1.shape[0] * img1.shape[1]  # img1 and 2 should have same shape
    err = summed / num_pix
    return err


def show_pic_and_wait_key(pic1,pic2):
   cv2.imshow('1', pic1)
   cv2.imshow('2', pic2)

   cv2.waitKey(0)
   cv2.destroyAllWindows()


pug = cv2.imread('/Users/daniilnaumenko/Desktop/r.jpg')
gray_pug = cv2.cvtColor(pug, cv2.COLOR_BGR2GRAY) #0.299R 0.587G 0.114B
show_pic_and_wait_key(pug,gray_pug)

colors = cv2.imread('/Users/daniilnaumenko/Desktop/d.jpg')
gray_colors = cv2.cvtColor(colors , cv2.COLOR_BGR2GRAY) #0.299R 0.587G 0.114B
show_pic_and_wait_key(colors, gray_colors)


histr_pug = cv2.calcHist([gray_pug],[0],None,[25],[0,256])
plt.plot(histr_pug)
plt.show()

histr_colors = cv2.calcHist([gray_colors],[0],None,[25],[0,256])
plt.plot(histr_colors)
plt.show()

im_mean_pug, im_std_pug = cv2.meanStdDev(histr_pug)
im_mean_colors, im_std_colors = cv2.meanStdDev(histr_colors)

pug_hist_median = np.median(histr_pug)
colors_hist_median = np.median(histr_colors)

mode_hist_pug = stats.mode(histr_pug)
mode_hist_colrs = stats.mode(histr_colors)


corr_of_hist = cv2.compareHist(histr_pug, histr_colors, method = cv2.HISTCMP_CORREL)

hist_comp = cv2.compareHist(histr_colors,histr_pug,method=cv2.HISTCMP_CORREL)

img_corr_coef = cv2.matchTemplate(pug,colors,cv2.TM_CCOEFF_NORMED)

ignore, p_val_pug_hist = stats.normaltest(histr_pug)
if p_val_pug_hist < 0.05:
 print("distribution cannot be considered normal")
else:
   print("distribution can be considered normal")
 ignore, p_val_colors_hist = stats.normaltest(histr_colors)
if p_val_colors_hist < 0.05:
  print("distribution cannot be considered normal")
else:
   print("distribution can be considered normal")

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