def __init__(self, B, A):
"""Create an IIR filter, given the B and A coefficient vectors"""
self.B = B
self.A = A
if len(A) > 2:
self.prev_outputs = Ringbuffer(len(A) - 1)
else:
self.prev_outputs = Ringbuffer(3)
self.prev_inputs = Ringbuffer(len(B))
def __init__(self, window):
if have_numpy:
self.window = numpy.array(window)
else:
self.window = list(window)
self.buffer = Ringbuffer(len(window))
def __init__(self, taps):
self.taps = taps
max_t = 0
for time, scale in taps:
if time > max_t:
max_t = time
self.buffer = Ringbuffer(max_t)
def __init__(self,
bp_filter,
lp_filter,
centre_freq,
sr,
loop_gain=1.0,
in_gain=1.0):
self.sr = sr
self.base_rate = (centre_freq * 2 * math.pi) / sr
self.int = 0
self.bp_filter = bp_filter
self.lp_filter = lp_filter
self.phase_buffer = Ringbuffer(int(sr / centre_freq))
self.loop_gain = loop_gain
self.in_gain = in_gain
def __init__(self, len):
self.buffer = Ringbuffer(len)
self.differentiator = Differentiator()
def __init__(self, window_len):
self.window_len = window_len
self.buffer = Ringbuffer(window_len)
def __init__(self, delay):
self.delay = delay
self.buffer = Ringbuffer(delay)
def __init__(self, window):
self.window = window
self.buffer = Ringbuffer(window)
def __init__(self, binop, window):
self.state = None
self.window = window
self.buffer = Ringbuffer(window)
self.binop = binop
def load_reID(self):
logging.basicConfig(filename='feature_extractor_wrapper.log',
level=logging.DEBUG)
self.feature_extractor = feature_extraction('0', self.model, '1',
self.batch_size)
self.ringbuffer = Ringbuffer(200, 10000)
def main():
'''
detect and print the detected goals
'''
buf = Ringbuffer(4 * FPS)
replay_it = None
gd = GoalDetector()
classifier = Classifier('trainingdata')
videopath = './match2.h264'
camera = cv2.VideoCapture(videopath)
print(np.shape(camera))
cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty(
"window",
cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
(grabbed, frame) = camera.read()
for i in range(100): # TODO delete
camera.read()
# TODO make read() wait for a frame to be ready
t0 = time.time()
while grabbed:
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
t1 = time.time()
if replay_it:
try:
cv2.imshow('window', next(replay_it))
except StopIteration:
replay_it = None
else:
obs, _ = gd.step(hsv)
t2 = time.time()
# resized = cv2.resize(hsv, (960, 540))
cv2.imshow('window', hsv)
t3 = time.time()
for i, obstacles in enumerate(obs):
for obstacle in obstacles:
# if classifier.predict(obstacle, hsv, gd.goal_rects[i]):
if False:
replay_it = iter(buf)
break
if replay_it:
break
t4 = time.time()
cv2.waitKey(1) # need to wait for event loop and displaying...
t5 = time.time()
(grabbed, frame) = camera.read()
t6 = time.time()
# TODO speed up JPEG saving
if not replay_it:
buf.store_next_frame((frame))
t7 = time.time()
# print('{} grabbing, {} hsvconv, {} compute, {} displaying'
# .format(t4 - t3, t1 - t0, t2 - t1, t3 - t2))
t = (t0, t1, t2, t3, t4, t5, t6, t7)
print([t[i] - t[i-1] for i in range(1, len(t))])
t0 = time.time()
cv2.destroyAllWindows()
