diff --git a/detect_objects.py b/detect_objects.py index afbc6f057..1c06ed619 100644 --- a/detect_objects.py +++ b/detect_objects.py @@ -15,7 +15,7 @@ import logging from flask import Flask, Response, make_response, jsonify, request import paho.mqtt.client as mqtt -from frigate.video import track_camera +from frigate.video import track_camera, get_ffmpeg_input, get_frame_shape, CameraCapture, start_or_restart_ffmpeg from frigate.object_processing import TrackedObjectProcessor from frigate.util import EventsPerSecond from frigate.edgetpu import EdgeTPUProcess @@ -83,60 +83,50 @@ class CameraWatchdog(threading.Thread): time.sleep(10) while True: # wait a bit before checking - time.sleep(30) + time.sleep(10) # check the plasma process rc = self.plasma_process.poll() if rc != None: print(f"plasma_process exited unexpectedly with {rc}") self.plasma_process = start_plasma_store() - time.sleep(10) # check the detection process if (self.tflite_process.detection_start.value > 0.0 and datetime.datetime.now().timestamp() - self.tflite_process.detection_start.value > 10): print("Detection appears to be stuck. Restarting detection process") self.tflite_process.start_or_restart() - time.sleep(30) elif not self.tflite_process.detect_process.is_alive(): print("Detection appears to have stopped. Restarting detection process") self.tflite_process.start_or_restart() - time.sleep(30) # check the camera processes for name, camera_process in self.camera_processes.items(): process = camera_process['process'] if not process.is_alive(): - print(f"Process for {name} is not alive. Starting again...") + print(f"Track process for {name} is not alive. Starting again...") camera_process['fps'].value = float(self.config[name]['fps']) camera_process['skipped_fps'].value = 0.0 camera_process['detection_fps'].value = 0.0 camera_process['read_start'].value = 0.0 - camera_process['ffmpeg_pid'].value = 0 - process = mp.Process(target=track_camera, args=(name, self.config[name], FFMPEG_DEFAULT_CONFIG, GLOBAL_OBJECT_CONFIG, - self.tflite_process.detection_queue, self.tracked_objects_queue, + process = mp.Process(target=track_camera, args=(name, self.config[name], GLOBAL_OBJECT_CONFIG, camera_process['frame_queue'], + camera_process['frame_shape'], self.tflite_process.detection_queue, self.tracked_objects_queue, camera_process['fps'], camera_process['skipped_fps'], camera_process['detection_fps'], - camera_process['read_start'], camera_process['ffmpeg_pid'])) + camera_process['read_start'])) process.daemon = True camera_process['process'] = process process.start() - print(f"Camera_process started for {name}: {process.pid}") - - if (camera_process['read_start'].value > 0.0 and - datetime.datetime.now().timestamp() - camera_process['read_start'].value > 10): - print(f"Process for {name} has been reading from ffmpeg for over 10 seconds long. Killing ffmpeg...") - ffmpeg_pid = camera_process['ffmpeg_pid'].value - if ffmpeg_pid != 0: - try: - os.kill(ffmpeg_pid, signal.SIGTERM) - except OSError: - print(f"Unable to terminate ffmpeg with pid {ffmpeg_pid}") - time.sleep(10) - try: - os.kill(ffmpeg_pid, signal.SIGKILL) - print(f"Unable to kill ffmpeg with pid {ffmpeg_pid}") - except OSError: - pass + print(f"Track process started for {name}: {process.pid}") + + if not camera_process['capture_thread'].is_alive(): + frame_shape = camera_process['frame_shape'] + frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2] + ffmpeg_process = start_or_restart_ffmpeg(camera_process['ffmpeg_cmd'], frame_size) + camera_capture = CameraCapture(name, ffmpeg_process, frame_shape, camera_process['frame_queue'], + camera_process['take_frame'], camera_process['camera_fps']) + camera_capture.start() + camera_process['ffmpeg_process'] = ffmpeg_process + camera_process['capture_thread'] = camera_capture def main(): # connect to mqtt and setup last will @@ -180,17 +170,54 @@ def main(): # start the camera processes camera_processes = {} for name, config in CONFIG['cameras'].items(): + # Merge the ffmpeg config with the global config + ffmpeg = config.get('ffmpeg', {}) + ffmpeg_input = get_ffmpeg_input(ffmpeg['input']) + ffmpeg_global_args = ffmpeg.get('global_args', FFMPEG_DEFAULT_CONFIG['global_args']) + ffmpeg_hwaccel_args = ffmpeg.get('hwaccel_args', FFMPEG_DEFAULT_CONFIG['hwaccel_args']) + ffmpeg_input_args = ffmpeg.get('input_args', FFMPEG_DEFAULT_CONFIG['input_args']) + ffmpeg_output_args = ffmpeg.get('output_args', FFMPEG_DEFAULT_CONFIG['output_args']) + ffmpeg_cmd = (['ffmpeg'] + + ffmpeg_global_args + + ffmpeg_hwaccel_args + + ffmpeg_input_args + + ['-i', ffmpeg_input] + + ffmpeg_output_args + + ['pipe:']) + + if 'width' in config and 'height' in config: + frame_shape = (config['height'], config['width'], 3) + else: + frame_shape = get_frame_shape(ffmpeg_input) + + frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2] + take_frame = config.get('take_frame', 1) + + ffmpeg_process = start_or_restart_ffmpeg(ffmpeg_cmd, frame_size) + frame_queue = mp.SimpleQueue() + camera_fps = EventsPerSecond() + camera_fps.start() + camera_capture = CameraCapture(name, ffmpeg_process, frame_shape, frame_queue, take_frame, camera_fps) + camera_capture.start() + camera_processes[name] = { + 'camera_fps': camera_fps, + 'take_frame': take_frame, 'fps': mp.Value('d', float(config['fps'])), 'skipped_fps': mp.Value('d', 0.0), 'detection_fps': mp.Value('d', 0.0), 'read_start': mp.Value('d', 0.0), - 'ffmpeg_pid': mp.Value('i', 0) + 'ffmpeg_process': ffmpeg_process, + 'ffmpeg_cmd': ffmpeg_cmd, + 'frame_queue': frame_queue, + 'frame_shape': frame_shape, + 'capture_thread': camera_capture } - camera_process = mp.Process(target=track_camera, args=(name, config, FFMPEG_DEFAULT_CONFIG, GLOBAL_OBJECT_CONFIG, + + camera_process = mp.Process(target=track_camera, args=(name, config, GLOBAL_OBJECT_CONFIG, frame_queue, frame_shape, tflite_process.detection_queue, tracked_objects_queue, camera_processes[name]['fps'], camera_processes[name]['skipped_fps'], camera_processes[name]['detection_fps'], - camera_processes[name]['read_start'], camera_processes[name]['ffmpeg_pid'])) + camera_processes[name]['read_start'])) camera_process.daemon = True camera_processes[name]['process'] = camera_process @@ -245,7 +272,7 @@ def main(): 'detection_fps': round(camera_stats['detection_fps'].value, 2), 'read_start': camera_stats['read_start'].value, 'pid': camera_stats['process'].pid, - 'ffmpeg_pid': camera_stats['ffmpeg_pid'].value + 'ffmpeg_pid': camera_stats['ffmpeg_process'].pid } stats['coral'] = { @@ -302,7 +329,7 @@ def main(): app.run(host='0.0.0.0', port=WEB_PORT, debug=False) - camera_watchdog.join() + object_processor.join() plasma_process.terminate() diff --git a/frigate/object_processing.py b/frigate/object_processing.py index a06824246..80bcbfd46 100644 --- a/frigate/object_processing.py +++ b/frigate/object_processing.py @@ -10,7 +10,7 @@ from collections import Counter, defaultdict import itertools import pyarrow.plasma as plasma import matplotlib.pyplot as plt -from frigate.util import draw_box_with_label +from frigate.util import draw_box_with_label, PlasmaManager from frigate.edgetpu import load_labels PATH_TO_LABELS = '/labelmap.txt' @@ -36,6 +36,7 @@ class TrackedObjectProcessor(threading.Thread): 'current_frame': np.zeros((720,1280,3), np.uint8), 'object_id': None }) + self.plasma_client = PlasmaManager() def get_best(self, camera, label): if label in self.camera_data[camera]['best_objects']: @@ -45,35 +46,8 @@ class TrackedObjectProcessor(threading.Thread): def get_current_frame(self, camera): return self.camera_data[camera]['current_frame'] - - def connect_plasma_client(self): - while True: - try: - self.plasma_client = plasma.connect("/tmp/plasma") - return - except: - print(f"TrackedObjectProcessor: unable to connect plasma client") - time.sleep(10) - - def get_from_plasma(self, object_id): - while True: - try: - return self.plasma_client.get(object_id, timeout_ms=0) - except: - self.connect_plasma_client() - time.sleep(1) - - def delete_from_plasma(self, object_ids): - while True: - try: - self.plasma_client.delete(object_ids) - return - except: - self.connect_plasma_client() - time.sleep(1) def run(self): - self.connect_plasma_client() while True: camera, frame_time, tracked_objects = self.tracked_objects_queue.get() @@ -85,10 +59,7 @@ class TrackedObjectProcessor(threading.Thread): ### # Draw tracked objects on the frame ### - object_id_hash = hashlib.sha1(str.encode(f"{camera}{frame_time}")) - object_id_bytes = object_id_hash.digest() - object_id = plasma.ObjectID(object_id_bytes) - current_frame = self.get_from_plasma(object_id) + current_frame = self.plasma_client.get(f"{camera}{frame_time}") if not current_frame is plasma.ObjectNotAvailable: # draw the bounding boxes on the frame @@ -117,10 +88,10 @@ class TrackedObjectProcessor(threading.Thread): self.camera_data[camera]['current_frame'] = current_frame # store the object id, so you can delete it at the next loop - previous_object_id = self.camera_data[camera]['object_id'] + previous_object_id = f"{camera}{frame_time}" if not previous_object_id is None: - self.delete_from_plasma([previous_object_id]) - self.camera_data[camera]['object_id'] = object_id + self.plasma_client.delete(f"{camera}{frame_time}") + self.camera_data[camera]['object_id'] = f"{camera}{frame_time}" ### # Maintain the highest scoring recent object and frame for each label diff --git a/frigate/util.py b/frigate/util.py index 543ce38f6..4e9a2307b 100755 --- a/frigate/util.py +++ b/frigate/util.py @@ -1,4 +1,5 @@ import datetime +import time import signal import traceback import collections @@ -6,6 +7,8 @@ import numpy as np import cv2 import threading import matplotlib.pyplot as plt +import hashlib +import pyarrow.plasma as plasma def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label, info, thickness=2, color=None, position='ul'): if color is None: @@ -134,4 +137,47 @@ def print_stack(sig, frame): traceback.print_stack(frame) def listen(): - signal.signal(signal.SIGUSR1, print_stack) \ No newline at end of file + signal.signal(signal.SIGUSR1, print_stack) + +class PlasmaManager: + def __init__(self): + self.connect() + + def connect(self): + while True: + try: + self.plasma_client = plasma.connect("/tmp/plasma") + return + except: + print(f"TrackedObjectProcessor: unable to connect plasma client") + time.sleep(10) + + def get(self, name, timeout_ms=0): + object_id = plasma.ObjectID(hashlib.sha1(str.encode(name)).digest()) + while True: + try: + return self.plasma_client.get(object_id, timeout_ms=timeout_ms) + except: + self.connect() + time.sleep(1) + + def put(self, name, obj): + object_id = plasma.ObjectID(hashlib.sha1(str.encode(name)).digest()) + while True: + try: + self.plasma_client.put(obj, object_id) + return + except Exception as e: + print(f"Failed to put in plasma: {e}") + self.connect() + time.sleep(1) + + def delete(self, name): + object_id = plasma.ObjectID(hashlib.sha1(str.encode(name)).digest()) + while True: + try: + self.plasma_client.delete([object_id]) + return + except: + self.connect() + time.sleep(1) \ No newline at end of file diff --git a/frigate/video.py b/frigate/video.py index 223a02079..958c227a3 100755 --- a/frigate/video.py +++ b/frigate/video.py @@ -5,16 +5,15 @@ import cv2 import queue import threading import ctypes +import pyarrow.plasma as plasma import multiprocessing as mp import subprocess as sp import numpy as np -import hashlib -import pyarrow.plasma as plasma import copy import itertools import json from collections import defaultdict -from frigate.util import draw_box_with_label, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond, listen +from frigate.util import draw_box_with_label, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond, listen, PlasmaManager from frigate.objects import ObjectTracker from frigate.edgetpu import RemoteObjectDetector from frigate.motion import MotionDetector @@ -97,7 +96,7 @@ def create_tensor_input(frame, region): # Expand dimensions since the model expects images to have shape: [1, 300, 300, 3] return np.expand_dims(cropped_frame, axis=0) -def start_or_restart_ffmpeg(ffmpeg_cmd, frame_size, pid, ffmpeg_process=None): +def start_or_restart_ffmpeg(ffmpeg_cmd, frame_size, ffmpeg_process=None): if not ffmpeg_process is None: print("Terminating the existing ffmpeg process...") ffmpeg_process.terminate() @@ -112,30 +111,54 @@ def start_or_restart_ffmpeg(ffmpeg_cmd, frame_size, pid, ffmpeg_process=None): print("Creating ffmpeg process...") print(" ".join(ffmpeg_cmd)) - process = sp.Popen(ffmpeg_cmd, stdout = sp.PIPE, bufsize=frame_size*10) - pid.value = process.pid + process = sp.Popen(ffmpeg_cmd, stdout = sp.PIPE, stdin = sp.DEVNULL, bufsize=frame_size*10, start_new_session=True) return process -def track_camera(name, config, ffmpeg_global_config, global_objects_config, detection_queue, detected_objects_queue, fps, skipped_fps, detection_fps, read_start, ffmpeg_pid): +class CameraCapture(threading.Thread): + def __init__(self, name, ffmpeg_process, frame_shape, frame_queue, take_frame, fps): + threading.Thread.__init__(self) + self.name = name + self.frame_shape = frame_shape + self.frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2] + self.frame_queue = frame_queue + self.take_frame = take_frame + self.fps = fps + self.plasma_client = PlasmaManager() + self.ffmpeg_process = ffmpeg_process + + def run(self): + frame_num = 0 + while True: + if self.ffmpeg_process.poll() != None: + print(f"{self.name}: ffmpeg process is not running. exiting capture thread...") + break + + frame_bytes = self.ffmpeg_process.stdout.read(self.frame_size) + frame_time = datetime.datetime.now().timestamp() + + if len(frame_bytes) == 0: + print(f"{self.name}: ffmpeg didnt return a frame. something is wrong.") + continue + + frame_num += 1 + if (frame_num % self.take_frame) != 0: + continue + + # put the frame in the plasma store + self.plasma_client.put(f"{self.name}{frame_time}", + np + .frombuffer(frame_bytes, np.uint8) + .reshape(self.frame_shape) + ) + # add to the queue + self.frame_queue.put(frame_time) + + self.fps.update() + +def track_camera(name, config, global_objects_config, frame_queue, frame_shape, detection_queue, detected_objects_queue, fps, skipped_fps, detection_fps, read_start): print(f"Starting process for {name}: {os.getpid()}") listen() - # Merge the ffmpeg config with the global config - ffmpeg = config.get('ffmpeg', {}) - ffmpeg_input = get_ffmpeg_input(ffmpeg['input']) - ffmpeg_restart_delay = ffmpeg.get('restart_delay', 0) - ffmpeg_global_args = ffmpeg.get('global_args', ffmpeg_global_config['global_args']) - ffmpeg_hwaccel_args = ffmpeg.get('hwaccel_args', ffmpeg_global_config['hwaccel_args']) - ffmpeg_input_args = ffmpeg.get('input_args', ffmpeg_global_config['input_args']) - ffmpeg_output_args = ffmpeg.get('output_args', ffmpeg_global_config['output_args']) - ffmpeg_cmd = (['ffmpeg'] + - ffmpeg_global_args + - ffmpeg_hwaccel_args + - ffmpeg_input_args + - ['-i', ffmpeg_input] + - ffmpeg_output_args + - ['pipe:']) - # Merge the tracked object config with the global config camera_objects_config = config.get('objects', {}) # combine tracked objects lists @@ -149,14 +172,6 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete object_filters[obj] = {**global_object_filters.get(obj, {}), **camera_object_filters.get(obj, {})} expected_fps = config['fps'] - take_frame = config.get('take_frame', 1) - - if 'width' in config and 'height' in config: - frame_shape = (config['height'], config['width'], 3) - else: - frame_shape = get_frame_shape(ffmpeg_input) - - frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2] frame = np.zeros(frame_shape, np.uint8) @@ -174,10 +189,8 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete object_detector = RemoteObjectDetector(name, '/labelmap.txt', detection_queue) object_tracker = ObjectTracker(10) - - ffmpeg_process = start_or_restart_ffmpeg(ffmpeg_cmd, frame_size, ffmpeg_pid) - - plasma_client = plasma.connect("/tmp/plasma") + + plasma_client = PlasmaManager() frame_num = 0 avg_wait = 0.0 fps_tracker = EventsPerSecond() @@ -186,39 +199,23 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete skipped_fps_tracker.start() object_detector.fps.start() while True: - rc = ffmpeg_process.poll() - if rc != None: - print(f"{name}: ffmpeg_process exited unexpectedly with {rc}") - print(f"Letting {name} rest for {ffmpeg_restart_delay} seconds before restarting...") - time.sleep(ffmpeg_restart_delay) - ffmpeg_process = start_or_restart_ffmpeg(ffmpeg_cmd, frame_size, ffmpeg_pid, ffmpeg_process) - time.sleep(10) - read_start.value = datetime.datetime.now().timestamp() - frame_bytes = ffmpeg_process.stdout.read(frame_size) + frame_time = frame_queue.get() duration = datetime.datetime.now().timestamp()-read_start.value read_start.value = 0.0 avg_wait = (avg_wait*99+duration)/100 - if len(frame_bytes) == 0: - print(f"{name}: ffmpeg_process didnt return any bytes") - continue - - # limit frame rate - frame_num += 1 - if (frame_num % take_frame) != 0: - continue - fps_tracker.update() fps.value = fps_tracker.eps() detection_fps.value = object_detector.fps.eps() - - frame_time = datetime.datetime.now().timestamp() - # Store frame in numpy array - frame[:] = (np - .frombuffer(frame_bytes, np.uint8) - .reshape(frame_shape)) + # Get frame from plasma store + frame = plasma_client.get(f"{name}{frame_time}") + + if frame is plasma.ObjectNotAvailable: + skipped_fps_tracker.update() + skipped_fps.value = skipped_fps_tracker.eps() + continue # look for motion motion_boxes = motion_detector.detect(frame) @@ -227,6 +224,7 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete if frame_num > 100 and fps.value < expected_fps-1 and duration < 0.5*avg_wait: skipped_fps_tracker.update() skipped_fps.value = skipped_fps_tracker.eps() + plasma_client.delete(f"{name}{frame_time}") continue skipped_fps.value = skipped_fps_tracker.eps() @@ -330,7 +328,7 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete for index in idxs: obj = group[index[0]] - if clipped(obj, frame_shape): #obj['clipped']: + if clipped(obj, frame_shape): box = obj[2] # calculate a new region that will hopefully get the entire object region = calculate_region(frame_shape, @@ -370,9 +368,6 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete # now that we have refined our detections, we need to track objects object_tracker.match_and_update(frame_time, detections) - # put the frame in the plasma store - object_id = hashlib.sha1(str.encode(f"{name}{frame_time}")).digest() - plasma_client.put(frame, plasma.ObjectID(object_id)) # add to the queue detected_objects_queue.put((name, frame_time, object_tracker.tracked_objects))