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main.py
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from PIL import Image
from PIL import ImageGrab
import numpy as np
from sklearn_decoder import ImgRecognizer
import win32api, win32con
import time
import debug_utils as dbg
import simple_solver
import cProfile
import pstats
# excelent hardcoded values :)
board_box = (366, 166, 1008, 738)
img_size = (board_box[2]-board_box[0], board_box[3]-board_box[1])
cell_size = (img_size[0]/9, img_size[1]/9)
board_size = 9
game_board = np.zeros((board_size, board_size), dtype=np.int32)
recognizer = ImgRecognizer()
'''
candy values:
- 0 blue
- 1 green
- 2 orange
- 3 purple
- 4 red
- 5 yellow
- 6 chocolate'''
match_list = [(0, 1, 13, 19), (2, 3, 14, 20), (4, 5, 15, 21), (6, 7, 18, 22), (8, 9, 16, 23), (10, 11, 17, 24)]
special_candies = [1, 3, 5, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]
simple_candies = [0, 2, 4, 6, 8, 10]
striped_candies_h = [1, 3, 5, 7, 9, 11]
striped_candies_v = range(13, 19)
striped_candies = striped_candies_h[:]
striped_candies.extend(striped_candies_v)
wrapped_candies = range(19, 25)
chocolate = [12]
board_dict = {0: 'blue ', 1: 's_h_blue ', 2: 'green ', 3: 's_h_green ', 4: 'orange ', 5: 's_h_orange ',
6: 'purple ', 7: 's_h_purple ', 8: 'red ', 9: 's_h_red ', 10: 'yellow ', 11: 's_h_yellow ',
12: 'chocolate', 13: 's_v_blue ', 14: 's_v_green ', 15: 's_v_orange ', 16: 's_v_red ',
17: 's_v_yellow ', 18: 's_v_purple ', 19: 'blue_wrapped', 20: 'green_wrapped', 21: 'orange_wrapped',
22: 'purple_wrapped', 23: 'red_wrapped', 24: 'yellow_wrapped', -1: 'empty '}
# 3 candies explode for 60 points
# 4 candies exploder for 120 create striped candy - striped candy explodes the whole vertical line
# 5 in a line create a chocolate sprinkle. swipe it with a candy and it explodes candies of that color from the board
# windows coords
def win32_click(x, y):
win32api.SetCursorPos((x, y))
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTDOWN, x, y, 0, 0)
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTUP, x, y, 0, 0)
def get_desktop_coords(cell):
x = board_box[0] + cell[1] * cell_size[0] + cell_size[0]/2
y = board_box[1] + cell[0] * cell_size[1] + cell_size[1]/2
return x, y
def do_move(move):
start = move[0]
end = move[1]
start_w = get_desktop_coords(start)
end_w = get_desktop_coords(end)
win32api.SetCursorPos(start_w)
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTDOWN, start_w[0], start_w[1], 0, 0)
time.sleep(0.3)
win32api.SetCursorPos(end_w)
time.sleep(0.3)
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTUP, end_w[0], end_w[1], 0, 0)
win32api.SetCursorPos((1100, 1100))
def grab_board():
global game_board
img = ImageGrab.grab()
#img = Image.open('board.bmp')
img = img.crop(board_box)
#img.save('board.bmp')
for y in range(0, 9):
for x in range(0, 9):
cell_box = (x*cell_size[0], y*cell_size[1], (x+1)*cell_size[0], (y+1)*cell_size[1])
cell = img.crop(cell_box)
#cell.save('Cells/{0}_{1}.bmp'.format(y, x))
game_board[y][x] = recognizer.predict(cell)
dbg.print_board(game_board)
return img
ref_img = None
def board_is_moving():
global ref_img
img = ImageGrab.grab()
img = img.crop(board_box)
img = img.resize((img.size[0]/4, img.size[1]/4), Image.NEAREST)
has_movement = True
if ref_img:
has_movement = compare_images(img, ref_img, threshold=100) > 100
ref_img = img
return has_movement
def are_pixels_equal(p1, p2, threshold):
diff = 0
for i in range(3):
diff += abs(p1[i]-p2[i])
return diff < threshold
def compare_images(current, reference, threshold):
current_data = np.array(current.getdata())
ref_data = np.array(reference.getdata())
diff_pixels = 0
total_size = current.size[0]*current.size[1]
for i in range(0, total_size-3, 3):
if not are_pixels_equal(current_data[i], ref_data[i], threshold):
diff_pixels += 1
print diff_pixels
return diff_pixels
background_img = Image.open('background.bmp')
background_img = background_img.resize((background_img.size[0]/4, background_img.size[1]/4), Image.NEAREST)
def main():
recognizer.train()
solver = simple_solver.SimpleSolver()
img_end_game = Image.open('end_screen.bmp')
img_end_game = img_end_game.resize((img_end_game.size[0]/4, img_end_game.size[1]/4), Image.NEAREST)
total_moves = 0
while True:
if not board_is_moving():
board_img = grab_board()
board_img = board_img.resize((board_img.size[0]/4, board_img.size[1]/4), Image.NEAREST)
if compare_images(board_img, img_end_game, 10) < 3000:
break
score, move = solver.solve_board(game_board)
print '\nBest move found. Score = {0}, Move = {1}'.format(score, move)
do_move(move)
total_moves += 1
time.sleep(0.4)
print 'Total moves done: ' + str(total_moves)
if __name__ == '__main__':
main()
#cProfile.run('main()', filename='stats.txt')
#stats = pstats.Stats('stats.txt').sort_stats('cumulative')
#stats.print_stats()
#recognizer.train()