1133.md

An Old Image

Python script:

import cv2 as cv
import pandas as pd
import itertools
import numpy as np

imgfile = "old_image.png"
image = cv.imread(imgfile)

# Convert the image from BGR (OpenCV's default) to RGB
image = cv.cvtColor(image, cv.COLOR_BGR2RGB)

height, width, _ = image.shape
pixel_data = []

for y in range(height):
    for x in range(width):
        r, g, b = image[y, x]
        pixel_data.append((x, y, r, g, b))

df = pd.DataFrame(pixel_data, columns=["x", "y", "red", "green", "blue"])
# print(df)
columns_to_mix = ["x", "y", "red", "green"]

# Generate all permutations
permutations = list(itertools.permutations(columns_to_mix))
print(permutations)
images = []

for perm in permutations:
    permuted_df = df[list(perm) + ["blue"]]
    permuted_df.columns = ["x", "y", "red", "green", "blue"]
    print(permuted_df)

    # Reconstruct the image
    permuted_image = np.zeros((height, width, 3), dtype=np.uint8)
    for _, row in permuted_df.iterrows():
        x, y, r, g, b = int(row["x"]), int(row["y"]), int(row["red"]), int(row["green"]), int(row["blue"])
        permuted_image[y, x] = [r, g, b]

    images.append(permuted_image)    

# Navigation loop to display images
current_index = 0
threshold = 90 # Tweak this if QR code is not detected
while True:
    # Convert the image to black and white
    gray_image = cv.cvtColor(images[current_index], cv.COLOR_RGB2GRAY)
    _, binary_image = cv.threshold(gray_image, threshold, 255, cv.THRESH_BINARY)

    cv.imshow("Permuted Image - B/W", binary_image)
    print(f"Showing image {current_index + 1} of {len(images)}")

    key = cv.waitKey(0) & 0xFF

    if key == 27:  # ESC key to exit
        break
    elif key == 81:  # Left arrow key
        current_index = (current_index - 1) % len(images)
    elif key == 83:  # Right arrow key
        current_index = (current_index + 1) % len(images)

cv.destroyAllWindows()