def generate(bot, update, args):
'''
Generate random message starting from words given (/with command)
'''
argument = ' '.join(args)
B = Board(9)
B.generate_puzzle(1, to_remove=30)
draw_matrix(B.grid, name='puzzle.png')
bot.send_photo(chat_id=update.message.chat_id,
photo=open('puzzle.png', 'rb'))
def test_check_column(state, expected):
board = Board.create_empty_board([[], [], []], [[], [2], []])
for i, s in enumerate(state):
board[i, 1] = s
assert board.check_column(1) == expected
def test_check_line(state, expected):
board = Board.create_empty_board([[2], [], []], [[], [], []])
for i, s in enumerate(state):
board[0, i] = s
assert board.check_line(0) == expected
def test_check_line_complex(state, expected):
board = Board.create_empty_board([[], [], [2, 1, 2]], [[]] * 10)
for i, s in enumerate(state):
board[2, i] = s
assert board.check_line(2) == expected
def solve(bot, update):
file_id = update.message.photo[-1]
newFile = bot.getFile(file_id)
newFile.download('download.jpg')
bot.sendMessage(chat_id=update.message.chat_id, text="Processing...")
img = imread('download.jpg', IMREAD_GRAYSCALE)
json_file = open(args.model + '.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
model = model_from_json(loaded_model_json)
model.load_weights(args.model + '.h5')
grid = get_grid(img, model, method='cnn')
B = Board(9, grid)
# print(B.grid)
solution_img(B.solution().T, B.grid.T, 'solution.png')
bot.send_photo(chat_id=update.message.chat_id,
photo=open('solution.png', 'rb'))
def test_solve_simple():
board = Board.create_empty_board([[1], [1], [1]], [[1], [1], [1]])
board[0,0] = B
board.solve(depth=5)
expected = [[B, W, W], [W, B, W], [W, W, B]]
assert board_to_list(board._board) == expected
def save_generated_dataset(folder, number, randfont=True):
''' Save <number> of pictures in the given <folder>s orig subfolder and data as data.csv '''
y = np.zeros((number, 81), int)
for i in range(number):
picname = folder + 'orig/grid' + str(i).zfill(4) + '.png'
B = Board(9)
grid = B.solution()
fonts = [
'arial.ttf', 'arialbd.ttf', 'APHont-Regular_q15c.ttf',
'APHont-Bold_q15c.ttf', 'Hack.ttf', 'DejaVuSansMono-Bold.ttf',
'DroidSerif-Regular.ttf', 'OpenSans-Bold.ttf'
]
if randfont:
font = ImageFont.truetype('fonts/' + choice(fonts), size=45)
else:
font = ImageFont.truetype('fonts/APHont-Regular_q15c.ttf', size=45)
draw_matrix(grid, picname, frame=True, font=font)
y[i] = grid.reshape(81)
np.savetxt(folder + 'data.csv', y, delimiter=',', fmt='%d')
def test_change_board():
board = Board.create_empty_board([[], [], []], [[], [], [], []])
board[1,1] = W
board[2,2] = B
for i in range(3):
for j in range(3):
if (i,j) not in [(1,1), (2,2)]:
assert board[i,j] == E
assert board[1,1] == W
assert board[2,2] == B
def test_case01_empty():
b = Board([
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
])
assert repr(SudokuSolver.solve(b)) == repr([[1, 2, 3, 4, 5, 8, 9, 6, 7],
[4, 5, 8, 6, 7, 9, 1, 2, 3],
[9, 6, 7, 1, 2, 3, 8, 4, 5],
[2, 1, 9, 8, 3, 4, 5, 7, 6],
[3, 8, 4, 5, 6, 7, 2, 1, 9],
[5, 7, 6, 9, 1, 2, 3, 8, 4],
[8, 9, 1, 3, 4, 6, 7, 5, 2],
[6, 3, 2, 7, 8, 5, 4, 9, 1],
[7, 4, 5, 2, 9, 1, 6, 3,
8]]), "Wrong answer"
def test_case01_easy():
b = Board([
[1, 0, 6, 0, 0, 2, 3, 0, 0],
[0, 5, 0, 0, 0, 6, 0, 9, 1],
[0, 0, 9, 5, 0, 1, 4, 6, 2],
[0, 3, 7, 9, 0, 5, 0, 0, 0],
[5, 8, 1, 0, 2, 7, 9, 0, 0],
[0, 0, 0, 4, 0, 8, 1, 5, 7],
[0, 0, 0, 2, 6, 0, 5, 4, 0],
[0, 0, 4, 1, 5, 0, 6, 0, 9],
[9, 0, 0, 8, 7, 4, 2, 1, 0],
])
assert repr(SudokuSolver.solve(b)) == repr([[1, 4, 6, 7, 9, 2, 3, 8, 5],
[2, 5, 8, 3, 4, 6, 7, 9, 1],
[3, 7, 9, 5, 8, 1, 4, 6, 2],
[4, 3, 7, 9, 1, 5, 8, 2, 6],
[5, 8, 1, 6, 2, 7, 9, 3, 4],
[6, 9, 2, 4, 3, 8, 1, 5, 7],
[7, 1, 3, 2, 6, 9, 5, 4, 8],
[8, 2, 4, 1, 5, 3, 6, 7, 9],
[9, 6, 5, 8, 7, 4, 2, 1,
3]]), "Wrong answer"
def test_case01_hard():
b = Board([
[4, 0, 9, 3, 7, 0, 0, 0, 0],
[1, 0, 0, 4, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 9, 0, 1, 0],
[5, 0, 0, 0, 0, 6, 0, 7, 0],
[0, 6, 2, 0, 0, 0, 5, 8, 0],
[0, 1, 0, 2, 0, 0, 0, 0, 3],
[0, 2, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 5, 2, 0, 0, 8],
[0, 0, 0, 0, 9, 7, 6, 0, 5],
])
assert repr(SudokuSolver.solve(b)) == repr([[4, 8, 9, 3, 7, 1, 2, 5, 6],
[1, 5, 6, 4, 2, 8, 9, 3, 7],
[2, 7, 3, 5, 6, 9, 8, 1, 4],
[5, 4, 8, 9, 3, 6, 1, 7, 2],
[3, 6, 2, 7, 1, 4, 5, 8, 9],
[9, 1, 7, 2, 8, 5, 4, 6, 3],
[6, 2, 5, 8, 4, 3, 7, 9, 1],
[7, 9, 1, 6, 5, 2, 3, 4, 8],
[8, 3, 4, 1, 9, 7, 6, 2,
5]]), "Wrong answer"
def test_solve_problem():
b = [
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, B, B, E, E, E, E, E, E, E, B, B, E, E, E, E, E, E, E, B, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, B, B, E, E, B, E, E, E, B, B, E, E, B, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, B, E, E, E, E, B, E, E, E, E, B, E, E, E, B, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, B, B, E, E, E, E, B, B, E, E, E, E, B, E, E, E, E, B, B, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
[E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E],
]
lines = [
[7,3,1,1,7],
[1,1,2,2,1,1],
[1,3,1,3,1,1,3,1],
[1,3,1,1,6,1,3,1],
[1,3,1,5,2,1,3,1],
[1,1,2,1,1],
[7,1,1,1,1,1,7],
[3,3],
[1,2,3,1,1,3,1,1,2],
[1,1,3,2,1,1],
[4,1,4,2,1,2],
[1,1,1,1,1,4,1,3],
[2,1,1,1,2,5],
[3,2,2,6,3,1],
[1,9,1,1,2,1],
[2,1,2,2,3,1],
[3,1,1,1,1,5,1],
[1,2,2,5],
[7,1,2,1,1,1,3],
[1,1,2,1,2,2,1],
[1,3,1,4,5,1],
[1,3,1,3,10,2],
[1,3,1,1,6,6],
[1,1,2,1,1,2],
[7,2,1,2,5],
]
columns = [
[7,2,1,1,7],
[1,1,2,2,1,1],
[1,3,1,3,1,3,1,3,1],
[1,3,1,1,5,1,3,1],
[1,3,1,1,4,1,3,1],
[1,1,1,2,1,1],
[7,1,1,1,1,1,7],
[1,1,3],
[2,1,2,1,8,2,1],
[2,2,1,2,1,1,1,2],
[1,7,3,2,1],
[1,2,3,1,1,1,1,1],
[4,1,1,2,6],
[3,3,1,1,1,3,1],
[1,2,5,2,2],
[2,2,1,1,1,1,1,2,1],
[1,3,3,2,1,8,1],
[6,2,1],
[7,1,4,1,1,3],
[1,1,1,1,4],
[1,3,1,3,7,1],
[1,3,1,1,1,2,1,1,4],
[1,3,1,4,3,3],
[1,1,2,2,2,6,1],
[7,1,3,2,1,1],
]
board = Board.create_from_board(b, lines, columns)
board.solve()
print board._board
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import StandardScaler
import sys
import argparse
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('task', help='Solve or generate')
parser.add_argument('-i', help='Image to solve')
parser.add_argument('--method', help='Which ML algorithm to use - cnn or knn')
parser.add_argument(
'--model', help='Location of the model.json and model.h5 files for CNN')
args = parser.parse_args()
if args.task == 'generate':
B = Board(9)
B.generate_puzzle(1, to_remove=30)
draw_matrix(B.grid, name='puzzle.png')
# solution_img(B.solution(), B.grid, 'solution.png')
sys.exit()
elif args.task == 'solve':
img = imread(args.i, IMREAD_GRAYSCALE)
if args.method == 'knn':
scaler = StandardScaler()
model = KNeighborsClassifier(n_neighbors=3)
x_train, y_train = generate_dataset(250)
x_train = x_train.reshape(250, 784)
scaler.fit(x_train)
model.fit(x_train, y_train)
elif args.method == 'cnn':
json_file = open(args.model + '.json', 'r')
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--input",
"-i",
help=
"set input path in txt, must be rectangular n x m board, first line is 'n m' separated by space, then followed by n lines: fill the number separated by space or 0 if empty cell (must have exactly 1 empty cell)"
)
return parser.parse_args()
def get_config():
args = get_args()
filename = args.input if args.input else input("Input filename: ")
with open(filename, "r") as f:
config = f.readlines()
return config
if __name__ == "__main__":
config = get_config()
B = Board(config)
print("==== Initial matrix ====")
B.nodes[0].print()
print()
if B.solvable(output=True):
B.solve()
else:
print("Puzzle is unsolvable!")
[4,1,1,2,6],
[3,3,1,1,1,3,1],
[1,2,5,2,2],
[2,2,1,1,1,1,1,2,1],
[1,3,3,2,1,8,1],
[6,2,1],
[7,1,4,1,1,3],
[1,1,1,1,4],
[1,3,1,3,7,1],
[1,3,1,1,1,2,1,1,4],
[1,3,1,4,3,3],
[1,1,2,2,2,6,1],
[7,1,3,2,1,1],
]
board = Board.create_from_board(b, lines, columns)
#board.solve()
#print board._board
result_board = [
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0],
[ 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0],
[ 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0],
[ 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0],
[ 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0],
[ 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0],
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0],
[ 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
return initial_blocks
if __name__ == '__main__':
# initial_blocks = random_initial_blocks()
# initial_blocks = [
# [8, 1, 3],
# [4, 0, 2],
# [7, 6, 5]
# ]
initial_blocks = [[0, 1, 3], [4, 2, 5], [7, 8, 6]]
DIRECTIONS = ['UP', 'DOWN', 'LEFT', 'RIGHT']
initial = Board(initial_blocks)
initial.print_elements("Initial")
current_move = initial
while not current_move.is_goal():
possible_moves: List[Board] = []
for direction in DIRECTIONS:
if current_move.is_move_possible(direction):
new = current_move.go(direction)
possible_moves.append(new)
else:
print(f'Moving in {direction} not possible.')
current_move = min(possible_moves, key=lambda x: x.manhattan())
board[i][j] = info['shape'][0]
if info['end_points']:
board[i][j] = board[i][j].upper()
else:
board[i][j] = str(info['visits'])
return board, (x_levels[0], x_interval), (y_levels[0], y_interval)
if __name__ == '__main__':
import subprocess
import pyscreenshot as ImageGrab
from solver import Board
print("Please click on the window of the game LYNE.")
res = subprocess.getoutput('xwininfo')
num = [int(s) for s in res.split() if s.isdigit()]
while True:
input("Press enter for starting.")
img = ImageGrab.grab(bbox=(num[0], num[1], num[0] + num[4],
num[1] + num[5]))
img = cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)
board = get_board(img)[0]
from IPython import embed
embed()
board = Board(board)
paths = board.solve()
for path in paths:
board._print_path(path)
