diff --git a/pixel_puzzle/pixel_puzzle.py b/pixel_puzzle/pixel_puzzle.py
new file mode 100644
index 0000000..43b9366
--- /dev/null
+++ b/pixel_puzzle/pixel_puzzle.py
@@ -0,0 +1,182 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+
+import os
+import platform
+from base64 import b64decode, b64encode
+from pathlib import Path
+from typing import Union
+
+import numpy as np
+from PIL import Image
+
+
+def encode_base64(image_to_encode: str,
+                  encoded_text: Union[str, Path] = Path(__file__).with_suffix(".txt")) -> None:
+    """
+    Encode the input image as a Base64 string.
+    """
+    with open(image_to_encode, "rb") as image_file:
+        encoded_string = b64encode(image_file.read()).decode("utf-8")
+        with open(encoded_text, "w", encoding="utf-8") as text_file:
+            text_file.write(encoded_string)
+
+
+def decode_base64(encoded_text: str,
+                  decoded_image: Union[str, Path] = Path(__file__).with_suffix(".png")) -> None:
+    """
+    Decode the input Base64 string into an image.
+    """
+    with open(encoded_text, "r", encoding="utf-8") as text_file:
+        decoded_output = b64decode(text_file.read())
+        with open(decoded_image, "wb") as image_file:
+            image_file.write(decoded_output)
+
+
+def shuffle_pixels(origin_image: str,
+                   shuffled_image: str,
+                   index_file: Union[str, Path] = Path(__file__).with_suffix(".npy"),
+                   dimension: int = 0,
+                   seed: Union[int, None] = None) -> None:
+    """
+    Shuffle the arrangement of pixels in a specified dimension.
+    """
+    rng = np.random.default_rng(seed)
+
+    pixel_array = np.array(
+        Image.open(origin_image)
+    )
+    indices_shuffled = rng.permutation(
+        pixel_array.shape[dimension]
+    )
+
+    np.save(index_file, indices_shuffled)
+
+    shuffled_output = Image.fromarray(
+        np.take(
+            pixel_array,
+            indices_shuffled,
+            axis=dimension
+        )
+    )
+    shuffled_output.save(shuffled_image)
+
+
+def recover_pixels(shuffled_image: str,
+                   recovered_image: str,
+                   index_file: Union[str, Path] = Path(__file__).with_suffix(".npy"),
+                   dimension: int = 0) -> None:
+    """
+    Recover the arrangement of pixels in a specified dimension.
+    """
+    pixel_array = np.array(
+        Image.open(shuffled_image)
+    )
+
+    indices_recovered = np.argsort(
+        np.load(index_file)
+    )
+
+    recovered_output = Image.fromarray(
+        np.take(
+            pixel_array,
+            indices_recovered,
+            axis=dimension
+        )
+    )
+    recovered_output.save(recovered_image)
+
+
+if __name__ == "__main__":
+
+    print(
+        "A script to encode/decode images "
+        "or shuffle/recover the pixels of images.\n"
+    )
+
+    selection_of_mode = input(
+        'Please select one mode.\n'
+        'Options are "encode", "decode", "shuffle" and "recover".\n'
+    )
+
+    match selection_of_mode:
+
+        case "encode":
+            path_of_original_image = input(
+                "Please input the path of the original image.\n"
+            )
+            path_of_output_text = input(
+                "Please input the path of the output text file.\n"
+            )
+            encode_base64(
+                path_of_original_image,
+                path_of_output_text
+            )
+
+        case "decode":
+            path_of_input_text = input(
+                "Please input the path of the input text file.\n"
+            )
+            path_of_decoded_image = input(
+                "Please input the path of the decoded image.\n"
+            )
+            decode_base64(
+                path_of_input_text,
+                path_of_decoded_image
+            )
+
+        case "shuffle":
+            path_of_original_image = input(
+                "Please input the path of the original image.\n"
+            )
+            path_of_shuffled_image = input(
+                "Please input the path of the shuffled image.\n"
+            )
+            path_of_output_array = input(
+                "Please input the path of the output array.\n"
+            )
+            dimension_to_shuffle = input(
+                "Please input the dimension to shuffle.\n"
+            )
+            random_number_seed = input(
+                'Please input the selected random number seed.\n'
+                'Type "no" for `None`.\n'
+            )
+            shuffle_pixels(
+                path_of_original_image,
+                path_of_shuffled_image,
+                path_of_output_array,
+                int(dimension_to_shuffle),
+                seed=None if random_number_seed == "no" else int(random_number_seed)
+            )
+
+        case "recover":
+            path_of_shuffled_image = input(
+                "Please input the path of the shuffled image.\n"
+            )
+            path_of_recovered_image = input(
+                "Please input the path of the recovered image.\n"
+            )
+            path_of_input_array = input(
+                "Please input the path of the input array.\n"
+            )
+            dimension_to_recover = input(
+                "Please input the dimension to recover.\n"
+            )
+            recover_pixels(
+                path_of_shuffled_image,
+                path_of_recovered_image,
+                path_of_input_array,
+                int(dimension_to_recover)
+            )
+
+        case _:
+            print("Invalid mode selection.\n")
+
+    if platform.system() == "Windows":
+        os.system("pause")
+    else:
+        os.system(
+            "/bin/bash -c 'read -s -n 1 -p \"Press any key to exit.\"'"
+        )
+        print()