本文整理汇总了Python中algorithm.Algorithm.solve方法的典型用法代码示例。如果您正苦于以下问题：Python Algorithm.solve方法的具体用法？Python Algorithm.solve怎么用？Python Algorithm.solve使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类algorithm.Algorithm的用法示例。
在下文中一共展示了Algorithm.solve方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: WebSudoku
# 需要导入模块: from algorithm import Algorithm [as 别名]
# 或者: from algorithm.Algorithm import solve [as 别名]
class WebSudoku(object):
def __init__(self, verbose):
self._verbose = verbose
self._values, self._centroids = self._grab_board()
self._algo = Algorithm(self, self._values)
def solve(self):
self._algo.solve()
if self._verbose:
return
for row in range(9):
for col in range(9):
if (row, col) in self._algo.board_default:
continue
y, x = self._centroids[(row, col)]
pyautogui.moveTo(x, y)
pyautogui.click()
pyautogui.press(str(self._algo.value(row, col)))
def fill_cell(self, row, col, default=False):
if not self._verbose and not default:
return
if random.random() < 0.2 and not default:
#time.sleep(5)
pass
y, x = self._centroids[(row, col)]
pyautogui.moveTo(x, y)
pyautogui.click()
value = self._algo.value(row, col)
pyautogui.press('backspace')
pyautogui.press('delete')
pyautogui.press(str(value))
def _grab_board(self):
time.sleep(3)
samples = np.float32(np.loadtxt('vectors.data'))
responses = np.float32(np.loadtxt('samples.data'))
model = cv2.KNearest()
model.train(samples, responses)
window = gtk.gdk.get_default_root_window()
x, y, width, height, _ = window.get_geometry()
ss = gtk.gdk.Pixbuf.get_from_drawable(gtk.gdk.Pixbuf(gtk.gdk.COLORSPACE_RGB, True, 8, width, height),
gtk.gdk.get_default_root_window(),
gtk.gdk.colormap_get_system(),
0, 0, x, y, width, height)
ss.save(TMP_FILE, 'png')
raw = cv2.imread(TMP_FILE)
gray = cv2.cvtColor(raw, cv2.COLOR_BGR2GRAY)
threshold = cv2.adaptiveThreshold(gray, 255, 1, 1, 11, 15)
cache = threshold.copy()
contours, _ = cv2.findContours(threshold,
cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE)
squares = []
for c in contours:
c = cv2.approxPolyDP(c, 4, True)
if len(c) != 4:
continue
if not cv2.isContourConvex(c):
continue
squares.append(c)
board_size = max(cv2.contourArea(s) for s in squares)
board = [s for s in squares if cv2.contourArea(s) == board_size][0]
min_x = min(s[0][0] for s in board)
max_x = max(s[0][0] for s in board)
min_y = min(s[0][1] for s in board)
max_y = max(s[0][1] for s in board)
step_x = (max_x - min_x) / 9.0
step_y = (max_y - min_y) / 9.0
values = {}
centroids = {}
for y in range(9):
values[y] = {}
for x in range(9):
local_min_y = min_y + (y * step_y) + 5
local_max_y = min_y + ((y+1) * step_y) - 5
local_min_x = min_x + (x * step_x) + 5
local_max_x = min_x + ((x+1) * step_x) - 5
roi = cache[
local_min_y:local_max_y,
local_min_x:local_max_x]
centroids[(y, x)] = (
int((local_min_y + local_max_y) / 2.0),
int((local_min_x + local_max_x) / 2.0))
#.........这里部分代码省略.........