def process_frame(frame, prev_mask, carpet_mask):
if carpet_mask is None:
carpet_mask = img_util.green_carpet_mask(frame,
carpet_lowerb,
carpet_upperb)
mask = get_mask(frame, lowerb=ball_lowerb, upperb=ball_upperb,
carpet_mask=carpet_mask)
if prev_mask is None:
move_mask = np.zeros_like(mask)
else:
move_mask = cv2.bitwise_not(prev_mask, mask=mask)
prev_mask = mask
is_ball, move_mask = img_util.detect_ball(move_mask)
return is_ball, move_mask, prev_mask, frame
def test_orange_mask(input_path, out_prefix=None):
if out_prefix is None:
out_prefix = os.path.join('output', os.path.basename(input_path))
frames_orig = video_io.get_frames(input_path)
carpet_mask = img_util.green_carpet_mask(frames_orig[30],
lowerb_hls=(55, 0, 0),
upperb_hls=(70, 255, 255))
cv2.imwrite(out_prefix + '_carpet.jpg', carpet_mask)
frames_orange = [
video_util.preprocess(frame, carpet_mask=carpet_mask) for frame
in frames_orig]
write_video(out_prefix + '_orange_mask.avi', frames_orange)
return
def program(out_dir):
cap = cv2.VideoCapture(0)
cap.set(cv2.cv.CV_CAP_PROP_FPS, 30.0)
# fps = cap.get(cv2.cv.CV_CAP_PROP_FPS)
# cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 1920)
# cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 1080)
# cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 1280)
# cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 720)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 864)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 480)
perspective_matrix = get_perspective_transform(cap)
#
logger.info('matrix of perspective transform: {}'.format(
perspective_matrix))
img = read_from_capture(cap)
cv2.imwrite(os.path.join(out_dir, 'img.jpg'), img)
# Find carpet
lowerb, upperb = gui.get_hls_range(img,
winname='Choose HLS range for carpet')
logger.info('Carpet HLS range: {} - {}'.format(lowerb, upperb))
carpet_mask = img_util.green_carpet_mask(img, lowerb, upperb)
cv2.imwrite(os.path.join(out_dir, 'carpet_mask.jpg'), carpet_mask)
# Find target
img = read_from_capture(cap)
lowerb, upperb = gui.get_hls_range(img,
winname='Choose HLS range for target')
logger.info('Target HLS range: {} - {}'.format(lowerb, upperb))
ret, target_contour = img_util.target_contour(img, lowerb, upperb,
carpet_mask)
logging.debug('target contour: {}'.format(target_contour))
if not ret:
raise ValueError('Cannot find target')
target_contour_plane = perspective_transform_contour(target_contour,
perspective_matrix)
m = cv2.moments(target_contour_plane)
mass = m['m00']
# x,y coordinates on plane
if mass > 0:
target_coords = m['m10'] / mass, m['m01'] / mass
logger.info(
'target coordinates on plane: (x,y) = {}'.format(target_coords))
else:
raise ValueError('Cannot find target center')
cv2.drawContours(img, contours=[target_contour], contourIdx=-1,
color=(255, 255, 255),
thickness=2)
img_carpet = cv2.bitwise_and(img, img, mask=carpet_mask)
cv2.addWeighted(img, 0.25, img_carpet, 0.75, 0, dst=img_carpet)
cv2.imwrite(os.path.join(out_dir, 'carpet_target.jpg'), img_carpet)
# Find ball
img = read_from_capture(cap)
ball_lowerb, ball_upperb = gui.get_hls_range(img,
winname='Choose HLS range for ball')
logger.info('Ball HLS range: {} - {}'.format(ball_lowerb, ball_upperb))
conn = robot.RobotConnector(winscp_path='C:/TRIKStudio/winscp/WinSCP.com')
trik = robot.Robot(conn, angle_to_encoder=180 / np.pi)
traj = None
def get_coords():
if traj is None:
return False, (0, 0)
else:
idx, landing_point = tr.get_landing_point(traj)
if landing_point is not None:
return True, perspective_transform(landing_point,
perspective_matrix)
return False, (0, 0)
gun_params = {'x': 300, 'y': 50, 'z': 97, 'v': 300, 'g': 981,
'alpha_0': 15 * pi / 180, 'phi_0': 0.0, 'gun_length': 10}
gun_layer = GunLayer(rotate_and_shoot=trik.rotate_and_shoot,
get_coords=get_coords, target=target_coords,
gun_params=gun_params)
for i in xrange(10):
out_prefix = os.path.join(out_dir, str(i))
commands = tuple()
stdout, stderr = trik.open_and_trikRun(*commands)
logger.debug('trik: sent command = {}'.format(commands))
logger.debug('trik: stdout = {}'.format(stdout))
logger.debug('trik: stderr = {}'.format(stderr))
logger.info('ready to shoot...')
gun_layer.shoot_at_target()
logger.info('ready to capture...')
frames, mask_ball = video_util.extract_ball_from_capture(cap,
max_frames_count=30,
skip_count=0,
carpet_mask=carpet_mask,
get_mask=video_util.get_ball_mask,
ball_lowerb=ball_lowerb,
ball_upperb=ball_upperb,
ball_size=3
)
logger.debug("Frames captured: {}".format(len(frames)))
traj = tr.get_ball_trajectory(mask_ball)
if not traj:
logger.info('trajectory not found')
else:
logger.info('trajectory found')
for x, y in traj:
center = (int(round(x)), int(round(y)))
for frame in frames:
cv2.circle(frame, center, 3, (0, 0, 255), thickness=-1)
idx, landing_point = tr.get_landing_point(traj)
if landing_point is not None:
logger.info('landing point on plane: {}'.format(
perspective_transform(landing_point, perspective_matrix)))
for frame in frames:
x, y = landing_point
center = (int(round(x)), int(round(y)))
cv2.circle(frame, center, radius=10, color=(255, 255, 255),
thickness=1)
video_io.write_video(out_prefix + '_frames_ball.avi', frames)
video_io.write_video(out_prefix + '_ball_mask.avi', mask_ball)
cap.release()
def extract_ball_from_capture(cap, max_frames_count=-1, skip_count=0,
carpet_mask=None, get_mask=None,
carpet_lowerb=None,
carpet_upperb=None,
ball_lowerb=None,
ball_upperb=None,
ball_size=3):
"""
Read frames from capture until we detect motion of the ball
Return tuple of (original frames, ball mask frames)
:param carpet_lowerb:
:rtype : (list(np.ndarray), list(np.ndarray))
"""
frames = []
mask_frames = []
# mog = cv2.BackgroundSubtractorMOG(history=5, nmixtures=4,backgroundRatio=0.7)
mog = cv2.BackgroundSubtractorMOG()
motion_started = False
for _ in xrange(skip_count):
if cap.isOpened():
cap.read()
prev_mask = None
while cap.isOpened():
if 0 < max_frames_count <= len(frames):
logger.debug('max frames count reached')
break
ret, frame = cap.read()
if ret:
if get_mask is not None:
if carpet_mask is None:
carpet_mask = img_util.green_carpet_mask(frame,
carpet_lowerb,
carpet_upperb)
mask = get_mask(frame, lowerb=ball_lowerb, upperb=ball_upperb,
carpet_mask=carpet_mask)
if prev_mask is None:
move_mask = np.zeros_like(mask)
else:
move_mask = cv2.bitwise_not(prev_mask, mask=mask)
prev_mask = mask
else:
logger.debug('get_mask = None')
move_mask = mog.apply(frame)
is_ball, move_mask = img_util.detect_ball(move_mask, ball_size)
if is_ball:
if not motion_started:
logger.debug('ball appeared')
motion_started = True
frames.append(frame)
mask_frames.append(move_mask)
else:
if motion_started:
logger.debug(
'ball disappeared. Frames count: {}'.format(
len(frames)))
break
else:
continue
else:
logger.debug('Cannot read more frames')
break
return frames, mask_frames