def filled_square(df_threshold, diff):
avgs = [
np.average(diff[:, :, 0]),
np.average(diff[:, :, 1]),
np.average(diff[:, :, 2])
]
max_c = np.argmax(avgs)
binary = FrameProcessing.gray_to_binary(diff[:, :, max_c], 64)
area = np.sum(binary) / binary.size
b = np.multiply(diff[:, :, 0], binary)
g = np.multiply(diff[:, :, 1], binary)
r = np.multiply(diff[:, :, 2], binary)
bin_sum = np.sum(binary)
if bin_sum == 0:
avgs = [0, 0, 0]
else:
avgs = [np.sum(b) / bin_sum, np.sum(g) / bin_sum, np.sum(r) / bin_sum]
std = np.std(avgs)
# print(area, std)
if area > df_threshold['piece_min_area'] and std > df_threshold[
'piece_min_std']:
#print(avg, area, std)
return True
else:
return False
def lock_effect(df_threshold, diff):
avgs = [
np.average(diff[:, :, 0]),
np.average(diff[:, :, 1]),
np.average(diff[:, :, 2])
]
max_c = np.argmax(avgs)
gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
binary = FrameProcessing.gray_to_binary(diff[:, :, max_c], 64)
gray = np.multiply(gray, binary)
area = np.sum(binary) / binary.size
b = np.multiply(diff[:, :, 0], binary)
g = np.multiply(diff[:, :, 1], binary)
r = np.multiply(diff[:, :, 2], binary)
bin_sum = np.sum(binary)
if bin_sum == 0:
avgs = [0, 0, 0]
else:
avgs = [np.sum(b) / bin_sum, np.sum(g) / bin_sum, np.sum(r) / bin_sum]
std = np.std(avgs)
# print(area, std)
if area > df_threshold['piece_min_area'] and std < df_threshold[
'piece_min_std']:
#print(avg, area, std)
return True
else:
return False
def draw_current_playfield(df, playfield, frame_current):
for y in range(playfield.height):
text = str(y)
text_x = playfield.frame_board[y][0].min_x-40
text_y = playfield.frame_board[y][0].max_y
cv2.putText(frame_current, text, (text_x, text_y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255), 1)
for x in range(playfield.width):
sq = playfield.frame_board[y][x]
if playfield.board[y][x] > 0:
roi = sq.current_frame
stds = np.std(roi, axis = 2)
stds = FrameProcessing.gray_to_binary(stds, df['threshold']['piece_min_std'])
roi = FrameProcessing.multiply_binary(roi, stds)
if roi is not None:
frame_current[sq.min_y: sq.max_y, sq.min_x: sq.max_x] = roi
return frame_current
def square_changed(df_threshold, diff):
avg = np.average(diff)
avgs = [
np.average(diff[:, :, 0]),
np.average(diff[:, :, 1]),
np.average(diff[:, :, 2])
]
#print(avgs)
max_c = np.argmax(avgs)
binary = FrameProcessing.gray_to_binary(diff[:, :, max_c],
df_threshold['binarize'])
area = np.sum(binary) / binary.size
#print(avg, area)
if avg > df_threshold['piece_diff'] and area > df_threshold[
'piece_min_area']:
return True
else:
return False