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multiple hard coded processes

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blakeblackshear 2019-02-04 06:34:32 -06:00
parent 072997736c
commit 623a3044fb
1 changed files with 18 additions and 7 deletions
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25
detect_objects.py
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@ -114,6 +114,7 @@ def main():
# is a float. otherwise it stops updating the value in shared # is a float. otherwise it stops updating the value in shared
# memory. probably something to do with the size of the memory block # memory. probably something to do with the size of the memory block
shared_frame_time = mp.Value('d', 0.0) shared_frame_time = mp.Value('d', 0.0)
shared_frame_time2 = mp.Value('d', 0.0)
# compute the flattened array length from the array shape # compute the flattened array length from the array shape
flat_array_length = frame_shape[0] * frame_shape[1] * frame_shape[2] flat_array_length = frame_shape[0] * frame_shape[1] * frame_shape[2]
# create shared array for storing the full frame image data # create shared array for storing the full frame image data
@ -122,20 +123,28 @@ def main():
frame_arr = tonumpyarray(shared_arr).reshape(frame_shape) frame_arr = tonumpyarray(shared_arr).reshape(frame_shape)
# create shared array for storing 10 detected objects # create shared array for storing 10 detected objects
shared_output_arr = mp.Array(ctypes.c_double, 6*10) shared_output_arr = mp.Array(ctypes.c_double, 6*10)
shared_output_arr2 = mp.Array(ctypes.c_double, 6*10)
capture_process = mp.Process(target=fetch_frames, args=(shared_arr, shared_frame_time, frame_shape)) capture_process = mp.Process(target=fetch_frames, args=(shared_arr, [shared_frame_time, shared_frame_time2], frame_shape))
capture_process.daemon = True capture_process.daemon = True
detection_process = mp.Process(target=process_frames, args=(shared_arr, shared_output_arr, shared_frame_time, frame_shape, REGION_SIZE, REGION_X_OFFSET, REGION_Y_OFFSET)) detection_process = mp.Process(target=process_frames, args=(shared_arr, shared_output_arr,
shared_frame_time, frame_shape, REGION_SIZE, REGION_X_OFFSET, REGION_Y_OFFSET))
detection_process.daemon = True detection_process.daemon = True
object_parser = ObjectParser([shared_output_arr]) detection_process2 = mp.Process(target=process_frames, args=(shared_arr, shared_output_arr2,
shared_frame_time2, frame_shape, 1080, 0, 0))
detection_process.daemon = True
object_parser = ObjectParser([shared_output_arr, shared_output_arr2])
object_parser.start() object_parser.start()
capture_process.start() capture_process.start()
print("capture_process pid ", capture_process.pid) print("capture_process pid ", capture_process.pid)
detection_process.start() detection_process.start()
print("detection_process pid ", detection_process.pid) print("detection_process pid ", detection_process.pid)
detection_process2.start()
print("detection_process pid ", detection_process2.pid)
app = Flask(__name__) app = Flask(__name__)
@ -178,6 +187,7 @@ def main():
capture_process.join() capture_process.join()
detection_process.join() detection_process.join()
detection_process2.join()
object_parser.join() object_parser.join()
# convert shared memory array into numpy array # convert shared memory array into numpy array
@ -186,7 +196,7 @@ def tonumpyarray(mp_arr):
# fetch the frames as fast a possible, only decoding the frames when the # fetch the frames as fast a possible, only decoding the frames when the
# detection_process has consumed the current frame # detection_process has consumed the current frame
def fetch_frames(shared_arr, shared_frame_time, frame_shape): def fetch_frames(shared_arr, shared_frame_times, frame_shape):
# convert shared memory array into numpy and shape into image array # convert shared memory array into numpy and shape into image array
arr = tonumpyarray(shared_arr).reshape(frame_shape) arr = tonumpyarray(shared_arr).reshape(frame_shape)
@ -203,13 +213,14 @@ def fetch_frames(shared_arr, shared_frame_time, frame_shape):
if ret: if ret:
# if the detection_process is ready for the next frame decode it # if the detection_process is ready for the next frame decode it
# otherwise skip this frame and move onto the next one # otherwise skip this frame and move onto the next one
if shared_frame_time.value == 0.0: if all(shared_frame_time.value == 0.0 for shared_frame_time in shared_frame_times):
# go ahead and decode the current frame # go ahead and decode the current frame
ret, frame = video.retrieve() ret, frame = video.retrieve()
if ret: if ret:
arr[:] = frame arr[:] = frame
# signal to the detection_process by setting the shared_frame_time # signal to the detection_processes by setting the shared_frame_time
shared_frame_time.value = frame_time.timestamp() for shared_frame_time in shared_frame_times:
shared_frame_time.value = frame_time.timestamp()
else: else:
# sleep a little to reduce CPU usage # sleep a little to reduce CPU usage
time.sleep(0.01) time.sleep(0.01)