import time import numpy as np from PIL import Image import concurrent.futures # Estimates the absolute area by using the composite trapezoidal rule. # https://numpy.org/doc/stable/reference/generated/numpy.trapz.html def calculate_area(f, a, b, num_points=10000): x = np.linspace(a, b, num_points) y = f(x) area = np.trapz(np.abs(y), x) return area # Estimates the integral by using the composite trapezoidal rule. # https://numpy.org/doc/stable/reference/generated/numpy.trapz.html def calculate_integral(f, a, b, num_points=10000): x = np.linspace(a, b, num_points) y = f(x) integral = np.trapz(y, x) return integral def mysterious_transformation(data): y_pixel, x_pixel, _ = data.shape data_new = np.zeros([y_pixel, x_pixel, 3], dtype=np.uint8) for i in range(1, y_pixel - 1): for j in range(1, x_pixel - 1): for k in range(3): new_value = 5 * data[i, j, k] - data[i, j - 1, k] - data[i, j + 1, k] - data[i - 1, j, k] - data[ i + 1, j, k] data_new[i, j, k] = max(0, min(new_value, 255)) return data_new def mysterious_transformation_parallel(data, stripes=16): # Divide and conquer! y_pixel, x_pixel, _ = data.shape stripe_height = y_pixel // stripes stripe_width = x_pixel stripe_arrays = [data[i * stripe_height:(i + 1) * stripe_height, :] for i in range(stripes)] def calculate(stripe, i): y_stripe_pixel, x_stripe_pixel, _ = stripe.shape data_new = np.zeros([y_stripe_pixel, x_stripe_pixel, 3], dtype=np.uint8) height = i * stripe_height width = i * stripe_width for i in range(height, y_stripe_pixel - 1): for j in range(width, x_stripe_pixel - 1): for k in range(3): # No data race is to be expected (old image is only read) new_value = 5 * data[i, j, k] - data[i, j - 1, k] - data[i, j + 1, k] - data[i - 1, j, k] - data[i + 1, j, k] data_new[i, j, k] = max(0, min(new_value, 255)) return data_new i = 0 with concurrent.futures.ThreadPoolExecutor(stripes) as executor: # Compute for each slide and resample afterward data_new_stripes = list(executor.map(calculate, stripe_arrays, [i])) i += 1 return np.concatenate(data_new_stripes) 3 img = Image.open("lokomotive.png") pixels = np.asarray(img, dtype=np.uint8) # Measure execution time for mysterious_transformation # AMD Ryzen 7 5800X: 4.976848363876343 seconds start_time_normal = time.time() data_new_normal = mysterious_transformation(pixels) end_time_normal = time.time() execution_time_normal = end_time_normal - start_time_normal print("Execution time for normal method:", execution_time_normal, "seconds") # Measure execution time for mysterious_transformation_parallel # Execution time for parallel method: 0.0123138427734375 seconds start_time_parallel = time.time() data_new_parallel = mysterious_transformation_parallel(pixels, 256) end_time_parallel = time.time() execution_time_parallel = end_time_parallel - start_time_parallel print("Execution time for parallel method:", execution_time_parallel, "seconds") img_new_normal = Image.fromarray(data_new_normal, 'RGB') img_new_normal.save("new_normal_lokomotive.png") img_new_parallel = Image.fromarray(data_new_normal, 'RGB') img_new_parallel.save("new_parallel_lokomotive.png") img1 = Image.open("new_normal_lokomotive.png") img2 = Image.open("new_parallel_lokomotive.png") diff_count = 0 for x in range(img1.width): for y in range(img1.height): if img1.getpixel((x, y)) != img2.getpixel((x, y)): diff_count += 1 print(diff_count)