# for fname in images:
# frame = cv2.imread(fname)
# for m in data:
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(
gray, (3, 3),
None,
flags=cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_NORMALIZE_IMAGE +
cv2.CALIB_CB_FAST_CHECK)
destx = s0x
desty = s0y
# if True:
if ret == True:
m = cv2.mean(corners)
xhistory.extend(np.array([m[0]]))
yhistory.extend(np.array([m[1]]))
count += 1
if count < 12:
continue
dx = xhistory.get()
dispx = np.mean(dx[-3:]) - np.mean(dx[-6:-3])
last_dispx = np.mean(dx[-9:-6]) - np.mean(dx[-6:-3])
changed_directionx = np.sign(dispx) != np.sign(last_dispx)
if changed_directionx:
tmp = dx[-2:]
xhistory = RingBuffer(ringlen)
xhistory.extend(np.array(tmp))
dx = xhistory.get()
dispx = dx[-1] - dx[-2]
