Add Python reference implementation

reference.py

@@ -0,0 +1,67 @@
+from PIL import Image
+from pathlib import Path
+from io import BytesIO
+from collections import namedtuple
+from enum import Enum
+import requests
+
+Dimensions = namedtuple('Dimensions', ['width', 'height'])
+
+
+def import_from_path(path: Path) -> Image:
+    return Image.open(path)
+
+
+def import_from_url(url: str) -> Image:
+    r = requests.get(url)
+    return Image.open(BytesIO(r.content))
+
+
+def convert_to_black_white(im: Image) -> Image:
+    return im.convert('1')
+
+
+def convert_to_grayscale(im: Image) -> Image:
+    return im.convert('L')
+
+
+def resize(im: Image, size: Dimensions) -> Image:
+    return im.resize(size)
+
+
+def align_horizontal(images: list[Image]) -> Image:
+    largeur_totale = sum(im.width for im in images)
+    hauteur_max = max(images, key=lambda im: im.height).height
+    dst = Image.new(images[0].mode, (largeur_totale, hauteur_max))
+
+    largeur = 0
+    for img in images:
+        dst.paste(img, (largeur, 0))
+        largeur += img.width
+    return dst
+
+
+def align_vertical(images: list[Image]) -> Image:
+    hauteur_totale = sum(im.height for im in images)
+    largeur_max = max(images, key=lambda im: im.width).width
+    dst = Image.new(images[0].mode, (largeur_max, hauteur_totale))
+
+    hauteur = 0
+    for img in images:
+        dst.paste(img, (0, hauteur))
+        hauteur += img.height
+    return dst
+
+
+def fusion_image(im1: Image, im2: Image, opacity: float = 0.5) -> Image:
+    assert im1.mode == im2.mode, f'Image mode must be the same {im1.mode} != {im2.mode}'
+    return Image.blend(im1, im2, opacity)
+
+
+def create_gif(images: list[Image], duration: int = 40):
+    images[0].save('animated.gif', save_all=True, append_images=images[1:], duration=duration, loop=0)
+    return import_from_path(Path('animated.gif'))
+
+
+if __name__ == '__main__':
+    import_from_url('https://codefirst.iut.uca.fr/git/assets/img/avatar_default.png')