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()