def run(self):
with RunManager(self.name, self.run_acquirer, self.setup, self.q_sig,
self.q_comm) as rm:
print(rm)
def run(self):
''' Run continuously, waiting for input
'''
with RunManager(self.name, self.getInput, self.setup, self.q_sig,
self.q_comm) as rm:
logger.info(rm)
def run(self):
'''Run the processor continually on input frames
'''
self.fitframe_time = []
self.putAnalysis_time = []
self.procFrame_time = [] #aka t_motion
self.detect_time = []
self.shape_time = []
self.flag = False
self.total_times = []
self.timestamp = []
self.counter = 0
with RunManager(self.name, self.runProcess, self.setup, self.q_sig,
self.q_comm) as rm:
logger.info(rm)
print('Processor broke, avg time per frame: ',
np.mean(self.total_times, axis=0))
print('Processor got through ', self.frame_number, ' frames')
np.savetxt('output/timing/process_frame_time.txt',
np.array(self.total_times))
np.savetxt('output/timing/process_timestamp.txt',
np.array(self.timestamp))
self.shape_time = np.array(self.onAc.t_shapes)
self.detect_time = np.array(self.onAc.t_detect)
np.savetxt('output/timing/fitframe_time.txt',
np.array(self.fitframe_time))
np.savetxt('output/timing/shape_time.txt', self.shape_time)
np.savetxt('output/timing/detect_time.txt', self.detect_time)
np.savetxt('output/timing/putAnalysis_time.txt',
np.array(self.putAnalysis_time))
np.savetxt('output/timing/procFrame_time.txt',
np.array(self.procFrame_time))
before = self.params['init_batch']
nb = self.onAc.params.get('init', 'nb')
np.savetxt(
'output/raw_C.txt',
np.array(
self.onAc.estimates.C_on[nb:self.onAc.M,
before:self.frame_number + before]))
print('Number of times coords updated ', self.counter)
# with open('output/S.pk', 'wb') as f:
# init = self.params['init_batch']
# S = np.stack([osi.s[init:] for osi in self.onAc.estimates.OASISinstances])
# print('--------Final S shape: ', S.shape)
# pickle.dump(S, f)
with open('output/A.pk', 'wb') as f:
nb = self.onAc.params.get('init', 'nb')
A = self.onAc.estimates.Ab[:, nb:]
print(type(A))
pickle.dump(A, f)
if self.onAc.estimates.OASISinstances is not None:
try:
init = self.params['init_batch']
S = np.stack([
osi.s[init:] for osi in self.onAc.estimates.OASISinstances
])
np.savetxt('output/end_spikes.txt', S)
except Exception as e:
logger.error('Exception {}: {} during frame number {}'.format(
type(e).__name__, e, self.frame_number))
print(traceback.format_exc())
else:
print('No OASIS')
self.coords1 = [o['CoM'] for o in self.coords]
print(self.coords1[0])
print('type ', type(self.coords1[0]))
np.savetxt('output/contours.txt', np.array(self.coords1))