def thread_func(start, end):
try:
local_maxima = mlsl.maxima(img, img_type, col_offset, start,
col_stride, row_stride, col_total,
row_total, cols, end-start, distance)
lock.acquire()
try:
output.extend(local_maxima)
finally:
lock.release()
finally:
done.release()
def maxima(img, img_type, col_offset, row_offset,
col_stride, row_stride, col_total, row_total,
cols, rows, distance, threads=2):
if threads < 1:
raise Error('the argument threads must be positive')
if threads < 2:
return mlsl.maxima(img, img_type, col_offset, row_offset,
col_stride, row_stride, col_total,
row_total, cols, rows, distance)
output = []
lock = threading.RLock()
done = threading.Semaphore(0)
if threads > rows:
threads = rows;
def thread_func(start, end):
try:
local_maxima = mlsl.maxima(img, img_type, col_offset, start,
col_stride, row_stride, col_total,
row_total, cols, end-start, distance)
lock.acquire()
try:
output.extend(local_maxima)
finally:
lock.release()
finally:
done.release()
for j in range(threads):
start = row_offset + int(round(1.0*j*rows/threads))
end = row_offset + int(round(1.0*(j+1)*rows/threads))
thread.start_new_thread(thread_func, (start,end))
for j in range(threads):
done.acquire()
return output