zishuo/frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2025-09-27 03:46:15 +08:00
Code Issues Packages Projects Releases Wiki Activity

prep frames for object detection in a separate process

Browse Source
This commit is contained in:
blakeblackshear
2019-03-18 07:24:24 -05:00
parent 862aa2d3f0
commit f2c205be99
2 changed files with 83 additions and 58 deletions
Download Patch File Download Diff File Expand all files Collapse all files

36
detect_objects.py
View File

@@ -19,7 +19,7 @@ from frigate.mqtt import MqttMotionPublisher, MqttObjectPublisher
from frigate.objects import ObjectParser, ObjectCleaner, BestPersonFrame
from frigate.motion import detect_motion
from frigate.video import fetch_frames, FrameTracker
from frigate.object_detection import detect_objects
from frigate.object_detection import prep_for_detection, detect_objects
RTSP_URL = os.getenv('RTSP_URL')
@@ -85,6 +85,16 @@ def main():
objects_parsed = mp.Condition()
# Queue for detected objects
object_queue = mp.Queue()
# array for prepped frame with shape (1, 300, 300, 3)
prepped_frame_array = mp.Array(ctypes.c_uint8, 300*300*3)
# shared value for storing the prepped_frame_time
prepped_frame_time = mp.Value('d', 0.0)
# Condition for notifying that a new prepped frame is ready
prepped_frame_ready = mp.Condition()
# Lock to control access to the prepped frame
prepped_frame_lock = mp.Lock()
# array for prepped frame box [x1, y1, x2, y2]
prepped_frame_box = mp.Array(ctypes.c_uint16, 4)
# shape current frame so it can be treated as an image
frame_arr = tonumpyarray(shared_arr).reshape(frame_shape)
@@ -95,20 +105,19 @@ def main():
capture_process.daemon = True
# for each region, start a separate process for motion detection and object detection
detection_processes = []
detection_prep_processes = []
motion_processes = []
for region in regions:
detection_process = mp.Process(target=detect_objects, args=(shared_arr,
object_queue,
detection_prep_process = mp.Process(target=prep_for_detection, args=(shared_arr,
shared_frame_time,
frame_lock, frame_ready,
region['motion_detected'],
frame_shape,
region['size'], region['x_offset'], region['y_offset'],
region['min_person_area'],
DEBUG))
detection_process.daemon = True
detection_processes.append(detection_process)
prepped_frame_array, prepped_frame_time, prepped_frame_ready,
prepped_frame_lock, prepped_frame_box))
detection_prep_process.daemon = True
detection_prep_processes.append(detection_prep_process)
motion_process = mp.Process(target=detect_motion, args=(shared_arr,
shared_frame_time,
@@ -168,15 +177,16 @@ def main():
print("capture_process pid ", capture_process.pid)
# start the object detection processes
for detection_process in detection_processes:
detection_process.start()
print("detection_process pid ", detection_process.pid)
for detection_prep_process in detection_prep_processes:
detection_prep_process.start()
print("detection_prep_process pid ", detection_prep_process.pid)
# start the motion detection processes
# for motion_process in motion_processes:
# motion_process.start()
# print("motion_process pid ", motion_process.pid)
# TEMP: short circuit the motion detection
for region in regions:
region['motion_detected'].set()
with motion_changed:
@@ -239,8 +249,8 @@ def main():
app.run(host='0.0.0.0', debug=False)
capture_process.join()
for detection_process in detection_processes:
detection_process.join()
for detection_prep_process in detection_prep_processes:
detection_prep_process.join()
for motion_process in motion_processes:
motion_process.join()
frame_tracker.join()