# num_packet_before_disable = 1000
with open('Position_and_Speed_31_01_2020.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
#Open Event Data Real Time Discarded CSV file
with open('Events_31_01_2020.csv', 'w', newline='') as csvfile:
writerevents = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
#Open Event Data Real Time Discarded CSV file
with open('Noise_Events_31_01_2020.csv', 'w', newline='') as csvfile:
writernoise = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
while True:
try:
data = device.get_event("events")
if data is not None:
(pol_events, num_pol_event, special_events, num_special_event, frame_ts, frames, imu_events, num_imu_event) = data
if pol_events is not None:
for event in pol_events:
(t, x, y, p, noise) = event
if(noise == 1):
if (Collection_Period_1 == False) and (Positive_n_events == 0) and (Negative_n_events == 0):
t1 = t
t2 = t + 1000
t3 = t + 11000
t4 = t + 12000
event_batch_size = 0
event_batch_size_max = 10000
iterations = 0
with Timer("Processing entire dataset"):
while True:
event_batch = np.empty((1, 5))
while True:
if event_batch_size >= event_batch_size_max:
break
try:
iterations += 1
data = dvs_device.get_event()
if data is not None:
(
pol_events,
num_pol_event,
special_events,
num_special_event,
frames_ts,
frames,
imu_events,
num_imu_event,
) = data
if pol_events is not None:
event_batch = np.concatenate(
(event_batch, pol_events))