Program To Calculate Average and Standard Deviation of Image in Python Language Assignment Solution

Instructions

Objective

Write a python homework to calculate average and standard deviation of image in python language.

Requirements and Specifications

Source Code

import matplotlib.pyplot as mplot import numpy as np #import image #might get error so use import below from PIL import Image import matplotlib.pyplot as plt import os files=os.listdir("./data") N_images = len(files) # Load the first image and get its size img = np.array(Image.open("./data/" + files[0])).astype('float') (h,w,layers) = img.shape avg_image = np.zeros(img.shape).astype('float') print("Loading images... ", end = "") for filename in files: img_dir = "./data/" + filename img=np.array(Image.open("./data/"+filename)) avg_image += img print(f"done. A total of {N_images} images loaded.") # Calculate average image print("Calculating average image... ", end="") avg_image = avg_image / float(N_images) print("done.") # Calculate standard deviation image # Create an array with the same size of the avg image print("Calculating std image... ", end="") std_image = np.zeros(avg_image.shape).astype('float') # Now calculate the std of each pixel for all images for filename in files: img_dir = "./data/" + filename img=np.array(Image.open("./data/"+filename)) std_image += (np.square(img - avg_image) / float(N_images)) std_image = np.sqrt(std_image) print("done.") std_image2 = avg_image.std() # Ask user for treshold while True: threshold = input("Enter STD treshold: ") if threshold.isnumeric(): threshold = float(threshold) if threshold >= 0.0 and threshold <= 255.0: break else: print("Please enter a value between 0-255") else: print("Please enter a numeric treshold value.") # Now, highlight areas in avg_image avg_image_highlighted = avg_image.copy() for row in range(h): for col in range(w): if std_image[row][col].mean() > threshold: # if pixel's std is higher than treshold avg_image_highlighted[row][col] = [255.0, 0.0, 0.0] fig, axes = plt.subplots(nrows = 1, ncols = 2) axes[0].imshow(avg_image.astype(np.uint8)) axes[0].set_title('Average Image') axes[1].imshow(avg_image_highlighted.astype(np.uint8)) axes[1].set_title('Average Image Highlighted') plt.show()