def py_median_3x3(image, iterations=10, num_threads=1):
''' repeatedly filter with a 3x3 median '''
tmpA = image.copy()
tmpB = np.empty_like(tmpA)
if iterations == 0:
return tmpA
n = tmpA.shape[0]
# iterations x num_threads matrix
logging.debug('num_threads = %d', num_threads)
logging.debug('iterations = %d', iterations)
events = [[threading.Event()] * num_threads] * iterations
# iterate once first
filtering.median_3x3(tmpA, tmpB, 0, 1)
tmpA, tmpB = tmpB, tmpA
for k in range(len(events[0])):
e = events[0][k]
e.set()
logging.debug('thread %d->itr %d: finish swap; set event', k, 0)
for i in range(num_threads):
t = threading.Thread(target=worker_from_second_itr, args=(i, n, num_threads, iterations, tmpA, tmpB, events))
logging.debug('start thread %d', i)
t.start()
# for i in range(iterations):
# filtering.median_3x3(tmpA, tmpB, 0, 1)
# # swap direction of filtering
# tmpA, tmpB = tmpB, tmpA
main_thread = threading.currentThread()
for t in threading.enumerate():
if t is main_thread:
continue
logging.debug('joining %s', t.getName())
t.join()
return tmpA
def py_median_3x3(image, iterations=10, num_threads=1):
""" repeatedly filter with a 3x3 median """
tmpA = image.copy()
tmpB = np.empty_like(tmpA)
for i in range(iterations):
filtering.median_3x3(tmpA, tmpB, 0, 1)
# swap direction of filtering
tmpA, tmpB = tmpB, tmpA
return tmpA
def worker_from_second_itr(i, n, num_threads, iterations, tmpA, tmpB, events):
for itr in range(1, iterations):
# wait for neighboring events to finish
prec_i = i - 1 if i > 0 else ( num_threads - 1 )
succ_i = i + 1 if i < ( num_threads - 1 ) else 0
# @x: wait for neighbors
logging.debug('thread %d->itr %d: waiting for neighbors', i, itr)
events[itr - 1][prec_i].wait()
events[itr - 1][i].wait()
events[itr - 1][succ_i].wait()
# @x: filter
logging.debug('thread %d->itr %d: get event signal; filters', i, itr)
filtering.median_3x3(tmpA, tmpB, i, num_threads)
# @x: swap i th
logging.debug('thread %d->itr %d: finish filtering; swap', i, itr)
for k in range(0, n, num_threads):
tmpA[k], tmpB[k] = tmpB[k], tmpA[k]
# @x: signal waiting threads
logging.debug('thread %d->itr %d: finish swap; set event', i, itr)
events[itr][i].set()
def run(self):
filtering.median_3x3(self.tmpA, self.tmpB, self.offset, self.step)
