hist_of_pixel_values.py

import os
import numpy as np
import cv2
import matplotlib.pyplot as plt


root_dir = os.path.join([rd for rd in os.listdir('.') if 'gconet_' in rd][0], 'CoCA/Accordion')
image_paths = [os.path.join(root_dir, p) for p in os.listdir(root_dir)]
pixel_values = []
for image_path in image_paths:
    image = cv2.imread(image_path)
    pixel_value = image.flatten().squeeze().tolist()
    pixel_values += pixel_value

pixel_values = np.array(pixel_values)

non_zero_values = pixel_values[pixel_values >= 0]
margin_values_percent = (np.sum(non_zero_values > 230) + np.sum(non_zero_values <= 0)) / non_zero_values.shape[0] * 100
print('histing...')
plt.hist(x=non_zero_values)
plt.title('(0+>230)/all, {:.1f} % are margin values'.format(margin_values_percent))
plt.savefig('hist_(0+>230)|all.png')
plt.show()

non_zero_values = pixel_values[pixel_values >= 0]
margin_values_percent = (np.sum(non_zero_values > 230) + np.sum(non_zero_values < 0)) / non_zero_values.shape[0] * 100
print('histing...')
plt.figure()
plt.hist(x=non_zero_values)
plt.title('(230)/all, {:.1f} % are margin values'.format(margin_values_percent))
plt.savefig('hist_(230)|all.png')
plt.show()

non_zero_values = pixel_values[pixel_values > 0]
margin_values_percent = (np.sum(non_zero_values > 230) + np.sum(non_zero_values <= 0)) / non_zero_values.shape[0] * 100
print('histing...')
plt.figure()
plt.hist(x=non_zero_values)
plt.title('(0+>230)/(all-0), {:.1f} % are margin values'.format(margin_values_percent))
plt.savefig('hist_(0+>230)|(all-0).png')
plt.show()