def test_image_and_solve():
file_path = FILE_PATH.parent / "img/lvl_725.jpg"
with open(file_path, 'rb') as f:
file_bytes = np.asarray(bytearray(f.read()), dtype=np.uint8)
image_parser = ImageParser(file_bytes)
colors = image_parser.to_colors()
puzzle = BallSortPuzzle(colors)
result = puzzle.solve()
assert result is True
assert (
str(puzzle.moves)
== "[Ball(0 -> 12), Ball(1 -> 13), Ball(7 -> 12), Ball(11 -> 1), Ball(13 -> 11), Ball(3 -> 13), "
"Ball(4 -> 13), Ball(9 -> 4), Ball(3 -> 9), Ball(12 -> 3), Ball(12 -> 3), Ball(4 -> 12), "
"Ball(4 -> 12), Ball(0 -> 4), Ball(6 -> 0), Ball(11 -> 12), Ball(11 -> 12), Ball(7 -> 11), "
"Ball(4 -> 7), Ball(4 -> 7), Ball(4 -> 11), Ball(1 -> 4), Ball(1 -> 4), Ball(5 -> 4), Ball(2 -> "
"5), Ball(8 -> 4), Ball(5 -> 2), Ball(9 -> 8), Ball(2 -> 5), Ball(10 -> 9), Ball(1 -> 10), "
"Ball(5 -> 2), Ball(10 -> 1), Ball(10 -> 1), Ball(2 -> 5), Ball(10 -> 6), Ball(5 -> 2), "
"Ball(10 -> 13), Ball(2 -> 5), Ball(3 -> 10), Ball(3 -> 10), Ball(3 -> 10), Ball(2 -> 3), "
"Ball(2 -> 10), Ball(5 -> 3), Ball(5 -> 3), Ball(2 -> 5), Ball(6 -> 2), Ball(6 -> 2), Ball(5 -> "
"6), Ball(5 -> 6), Ball(5 -> 1), Ball(2 -> 5), Ball(2 -> 5), Ball(6 -> 2), Ball(6 -> 2), "
"Ball(6 -> 2), Ball(6 -> 13), Ball(5 -> 6), Ball(5 -> 6), Ball(7 -> 5), Ball(7 -> 5), Ball(7 -> "
"5), Ball(7 -> 2), Ball(6 -> 7), Ball(6 -> 7), Ball(8 -> 6), Ball(8 -> 6), Ball(7 -> 8), "
"Ball(7 -> 8), Ball(6 -> 7), Ball(6 -> 7), Ball(8 -> 6), Ball(8 -> 6), Ball(8 -> 6), Ball(8 -> "
"5), Ball(7 -> 8), Ball(7 -> 8), Ball(9 -> 7), Ball(7 -> 8), Ball(9 -> 7), Ball(7 -> 8), "
"Ball(9 -> 7), Ball(9 -> 0), Ball(7 -> 9), Ball(11 -> 7), Ball(7 -> 9), Ball(11 -> 7), "
"Ball(7 -> 9), Ball(11 -> 7), Ball(7 -> 9), Ball(11 -> 6)]"
)
def handler(event: Optional[dict], context: Optional[dict]):
body = json.loads(event['body']) # type: ignore
print(body)
message = body['message']
chat_id = message['chat']['id']
if photos := message.get('photo'):
# here photos is an array with same photo of different sizes
hd_photo = max(photos, key=lambda x: x['file_size']
) # get one with the highest resolution
try:
file = telegram_client.download_file(hd_photo['file_id'])
except TelegramClientError:
text = "Cant download the image from TG :("
else:
file_bytes = np.asarray(bytearray(file.read()), dtype=np.uint8)
try:
image_parser = ImageParser(file_bytes)
colors = image_parser.to_colors()
except ImageParserError as exp:
text = f"Cant parse image: {exp}"
else:
puzzle = BallSortPuzzle(colors)
solved = puzzle.solve()
if solved:
text = get_telegram_repr(puzzle)
else:
text = "This lvl don't have a solution"
def test_no_solution(filename):
file_path = FILE_PATH.parent / filename
with open(file_path, 'rb') as f:
file_bytes = np.asarray(bytearray(f.read()), dtype=np.uint8)
image_parser = ImageParser(file_bytes, debug=False)
colors = image_parser.to_colors()
assert colors
puzzle = BallSortPuzzle(colors)
result = puzzle.solve()
assert result is False
def test_image3():
file_path = FILE_PATH.parent / "img/lvl_1051.jpg"
with open(file_path, 'rb') as f:
file_bytes = np.asarray(bytearray(f.read()), dtype=np.uint8)
image_parser = ImageParser(file_bytes)
colors = image_parser.to_colors()
assert colors
puzzle = BallSortPuzzle(colors)
result = puzzle.solve()
assert result is True
def test_image1():
file_path = FILE_PATH.parent / "img/lvl_725.jpg"
with open(file_path, 'rb') as f:
file_bytes = np.asarray(bytearray(f.read()), dtype=np.uint8)
image_parser = ImageParser(file_bytes, debug=False)
colors = image_parser.to_colors()
assert colors == [
[color.L_BLUE, color.L_BLUE, color.GREEN, color.L_GREEN],
[color.PINK, color.PINK, color.BLUE, color.BROWN],
[color.LIME, color.L_GREEN, color.VIOLET, color.VIOLET],
[color.VIOLET, color.L_GREEN, color.GRAY, color.ORANGE],
[color.RED, color.GREEN, color.BROWN, color.ORANGE],
[color.PINK, color.LIME, color.VIOLET, color.BLUE],
[color.ORANGE, color.LIME, color.YELLOW, color.L_BLUE],
[color.LIME, color.GREEN, color.RED, color.L_GREEN],
[color.GREEN, color.YELLOW, color.GRAY, color.BLUE],
[color.L_BLUE, color.RED, color.GRAY, color.BROWN],
[color.ORANGE, color.YELLOW, color.PINK, color.GRAY],
[color.YELLOW, color.RED, color.BROWN, color.BLUE],
[],
[],
]
def imgs_for_pred(
df: pd.DataFrame,
path_col: str,
img_dims: tuple,
batch_size: int,
):
image_set = (tf.data.Dataset.from_tensor_slices((
df[path_col],
tuple([]),
)).map(ImageParser.ImageParser(),
num_parallel_calls=tf.data.experimental.AUTOTUNE).map(
ImageResizer.ImageResizer(img_dims, "stretch"),
num_parallel_calls=tf.data.experimental.AUTOTUNE).batch(
batch_size).prefetch(tf.data.experimental.AUTOTUNE))
return image_set