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| import numpy as np | |
| import pandas as pd | |
| from scipy.ndimage.interpolation import shift | |
| import cv2 | |
| from matplotlib import pyplot as plt | |
| input_photo_path = "/kaggle/input/84474892_2612930752149692_1911641796866211840_o.jpg" | |
| image = cv2.imread(input_photo_path) | |
| # Fix color expression. Plt uses RGB, cv2 reads BGR | |
| image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) | |
| image = image.astype(np.uint8) | |
| plt.imshow(image) | |
| # Split into r, g, b channels | |
| r, g, b = cv2.split(image) | |
| # Move a random amount of distance from center of image | |
| MAX_GLITCH_OFFSET = int(0.05 * min(image.shape[0], image.shape[1])) | |
| dr = random.randint(0, MAX_GLITCH_OFFSET) | |
| dg = random.randint(0, MAX_GLITCH_OFFSET) | |
| db = random.randint(0, MAX_GLITCH_OFFSET) | |
| # Move the image. | |
| r = shift(r, dr, cval = 0) | |
| g = shift(g, dg, cval = 0) | |
| b = shift(b, db, cval = 0) | |
| glitched = cv2.merge([r, g, b]) | |
| plt.imshow(glitched) | |
| # Let's encode a secret message for our birthday boy! | |
| # How many characters do I get per layer? I'll just use the horizontal space for now, not vertical :) | |
| charLimitR = dr * image.shape[0] | |
| charLimitG = dg * image.shape[0] | |
| charLimitB = db * image.shape[0] | |
| messageR = "FIND THIS YOURSELF" | |
| messageG = "THIS ONE TOO" | |
| messageB = "AND FINALLY THIS" | |
| # Let's create a matrix to hold all our bytes! | |
| mat = np.zeros_like(glitched) | |
| messages = [messageR, messageG, messageB] | |
| layers = cv2.split(glitched) # Maybe we can do better. in a hurry right now tho :P | |
| package = zip(messages, layers) | |
| final_with_message = [] | |
| for message, layer in package: | |
| message_to_add = [ord(ch) for ch in message] | |
| paddings = [0] * (image.shape[0] * image.shape[1] - len(message_to_add)) | |
| message_to_add += paddings | |
| print(message_to_add[:200]) | |
| # Reshape our message. | |
| reshaped_message = np.array(message_to_add).reshape(layer.shape) | |
| reshaped_message = reshaped_message.astype(np.uint8) | |
| # Add this to the channel!! | |
| layer += reshaped_message | |
| final_with_message.append(layer) | |
| print(layer.size) | |
| # Recombine the glitched image. | |
| final_with_message = cv2.merge(final_with_message) | |
| final_with_message.shape | |
| plt.imshow(final_with_message) | |
| cv2.imwrite('pranjal_glitched.png', final_with_message) | |
| plt.imshow(final_with_message) | |
| # Check if we get the same bytes from the image back! | |
| r, g, b = cv2.split(final_with_message) | |
| r = r.reshape(r.shape[0] * r.shape[1]) | |
| print(r[:200]) | |
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