diff --git a/detect_objects.py b/detect_objects.py
index ba1bc24b7..2c700f2a3 100644
--- a/detect_objects.py
+++ b/detect_objects.py
@@ -2,6 +2,7 @@ import cv2
 import time
 import queue
 import yaml
+import threading
 import multiprocessing as mp
 import subprocess as sp
 import numpy as np
@@ -50,10 +51,40 @@ GLOBAL_OBJECT_CONFIG = CONFIG.get('objects', {})
 WEB_PORT = CONFIG.get('web_port', 5000)
 DEBUG = (CONFIG.get('debug', '0') == '1')
 
+# TODO: make CPU/Coral switching more seamless
 # MODEL_PATH = CONFIG.get('tflite_model', '/lab/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite')
 MODEL_PATH = CONFIG.get('tflite_model', '/lab/detect.tflite')
 LABEL_MAP = CONFIG.get('label_map', '/lab/labelmap.txt')
 
+
+class CameraWatchdog(threading.Thread):
+    def __init__(self, camera_processes, config, tflite_process, tracked_objects_queue):
+        threading.Thread.__init__(self)
+        self.camera_processes = camera_processes
+        self.config = config
+        self.tflite_process = tflite_process
+        self.tracked_objects_queue = tracked_objects_queue
+
+    def run(self):
+        time.sleep(10)
+        while True:
+            # wait a bit before checking
+            time.sleep(10)
+
+            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...")
+                    camera_process['fps'].value = 10.0
+                    camera_process['skipped_fps'].value = 0.0
+                    process = mp.Process(target=track_camera, args=(name, self.config[name], FFMPEG_DEFAULT_CONFIG, GLOBAL_OBJECT_CONFIG, 
+                        self.tflite_process.detect_lock, self.tflite_process.detect_ready, self.tflite_process.frame_ready, self.tracked_objects_queue, 
+                        camera_process['fps'], camera_process['skipped_fps']))
+                    process.daemon = True
+                    camera_process['process'] = process
+                    process.start()
+                    print(f"Camera_process started for {name}: {process.pid}")
+
 def main():
     # connect to mqtt and setup last will
     def on_connect(client, userdata, flags, rc):
@@ -101,22 +132,24 @@ def main():
     tflite_process = EdgeTPUProcess(MODEL_PATH)
 
     # start the camera processes
-    camera_processes = []
-    camera_stats_values = {}
+    camera_processes = {}
     for name, config in CONFIG['cameras'].items():
-        camera_stats_values[name] = {
+        camera_processes[name] = {
             'fps': mp.Value('d', 10.0),
             'skipped_fps': mp.Value('d', 0.0)
         }
         camera_process = mp.Process(target=track_camera, args=(name, config, FFMPEG_DEFAULT_CONFIG, GLOBAL_OBJECT_CONFIG, 
             tflite_process.detect_lock, tflite_process.detect_ready, tflite_process.frame_ready, tracked_objects_queue, 
-            camera_stats_values[name]['fps'], camera_stats_values[name]['skipped_fps']))
+            camera_processes[name]['fps'], camera_processes[name]['skipped_fps']))
         camera_process.daemon = True
-        camera_processes.append(camera_process)
+        camera_processes[name]['process'] = camera_process
 
-    for camera_process in camera_processes:
-        camera_process.start()
-        print(f"Camera_process started {camera_process.pid}")
+    for name, camera_process in camera_processes.items():
+        camera_process['process'].start()
+        print(f"Camera_process started for {name}: {camera_process['process'].pid}")
+    
+    camera_watchdog = CameraWatchdog(camera_processes, CONFIG['cameras'], tflite_process, tracked_objects_queue)
+    camera_watchdog.start()
     
     object_processor = TrackedObjectProcessor(CONFIG['cameras'], client, MQTT_TOPIC_PREFIX, tracked_objects_queue)
     object_processor.start()
@@ -138,7 +171,7 @@ def main():
             }
         }
 
-        for name, camera_stats in camera_stats_values.items():
+        for name, camera_stats in camera_processes.items():
             stats[name] = {
                 'fps': camera_stats['fps'].value,
                 'skipped_fps': camera_stats['skipped_fps'].value
@@ -183,8 +216,7 @@ def main():
 
     app.run(host='0.0.0.0', port=WEB_PORT, debug=False)
 
-    for camera_process in camera_processes:
-        camera_process.join()
+    camera_watchdog.join()
     
     plasma_process.terminate()
 
diff --git a/frigate/video.py b/frigate/video.py
index f06e2a9f4..b67b0172d 100755
--- a/frigate/video.py
+++ b/frigate/video.py
@@ -55,534 +55,6 @@ def get_ffmpeg_input(ffmpeg_input):
     frigate_vars = {k: v for k, v in os.environ.items() if k.startswith('FRIGATE_')}
     return ffmpeg_input.format(**frigate_vars)
 
-<<<<<<< HEAD
-class CameraWatchdog(threading.Thread):
-    def __init__(self, camera):
-        threading.Thread.__init__(self)
-        self.camera = camera
-
-    def run(self):
-        prctl.set_name(self.__class__.__name__)
-        while True:
-            # wait a bit before checking
-            time.sleep(10)
-
-            if self.camera.frame_time.value != 0.0 and (datetime.datetime.now().timestamp() - self.camera.frame_time.value) > self.camera.watchdog_timeout:
-                print(self.camera.name + ": last frame is more than 5 minutes old, restarting camera capture...")
-                self.camera.start_or_restart_capture()
-                time.sleep(5)
-
-# Thread to read the stdout of the ffmpeg process and update the current frame
-class CameraCapture(threading.Thread):
-    def __init__(self, camera):
-        threading.Thread.__init__(self)
-        self.camera = camera
-
-    def run(self):
-        prctl.set_name(self.__class__.__name__)
-        frame_num = 0
-        while True:
-            if self.camera.ffmpeg_process.poll() != None:
-                print(self.camera.name + ": ffmpeg process is not running. exiting capture thread...")
-                break
-
-            raw_image = self.camera.ffmpeg_process.stdout.read(self.camera.frame_size)
-
-            if len(raw_image) == 0:
-                print(self.camera.name + ": ffmpeg didnt return a frame. something is wrong. exiting capture thread...")
-                break
-
-            frame_num += 1
-            if (frame_num % self.camera.take_frame) != 0:
-                continue
-
-            with self.camera.frame_lock:
-                # TODO: use frame_queue instead
-                self.camera.frame_time.value = datetime.datetime.now().timestamp()
-                self.camera.frame_cache[self.camera.frame_time.value] = (
-                    np
-                    .frombuffer(raw_image, np.uint8)
-                    .reshape(self.camera.frame_shape)
-                )
-                self.camera.frame_queue.put(self.camera.frame_time.value)
-            # Notify with the condition that a new frame is ready
-            with self.camera.frame_ready:
-                self.camera.frame_ready.notify_all()
-
-            self.camera.fps.update()
-
-class VideoWriter(threading.Thread):
-    def __init__(self, camera):
-        threading.Thread.__init__(self)
-        self.camera = camera
-
-    def run(self):
-        prctl.set_name(self.__class__.__name__)
-        while True:
-            (frame_time, tracked_objects) = self.camera.frame_output_queue.get()
-            # if len(tracked_objects) == 0:
-            #     continue
-            # f = open(f"/debug/output/{self.camera.name}-{str(format(frame_time, '.8f'))}.jpg", 'wb')
-            # f.write(self.camera.frame_with_objects(frame_time, tracked_objects))
-            # f.close()
-
-class Camera:
-    def __init__(self, name, ffmpeg_config, global_objects_config, config, prepped_frame_queue, mqtt_client, mqtt_prefix):
-        self.name = name
-        self.config = config
-        self.detected_objects = defaultdict(lambda: [])
-        self.frame_cache = {}
-        self.last_processed_frame = None
-        # queue for re-assembling frames in order
-        self.frame_queue = queue.Queue()
-        # track how many regions have been requested for a frame so we know when a frame is complete
-        self.regions_in_process = {}
-        # Lock to control access
-        self.regions_in_process_lock = mp.Lock()
-        self.finished_frame_queue = queue.Queue()
-        self.refined_frame_queue = queue.Queue()
-        self.frame_output_queue = queue.Queue()
-
-        self.ffmpeg = config.get('ffmpeg', {})
-        self.ffmpeg_input = get_ffmpeg_input(self.ffmpeg['input'])
-        self.ffmpeg_global_args = self.ffmpeg.get('global_args', ffmpeg_config['global_args'])
-        self.ffmpeg_hwaccel_args = self.ffmpeg.get('hwaccel_args', ffmpeg_config['hwaccel_args'])
-        self.ffmpeg_input_args = self.ffmpeg.get('input_args', ffmpeg_config['input_args'])
-        self.ffmpeg_output_args = self.ffmpeg.get('output_args', ffmpeg_config['output_args'])
-
-        camera_objects_config = config.get('objects', {})
-
-        self.take_frame = self.config.get('take_frame', 1)
-        self.watchdog_timeout = self.config.get('watchdog_timeout', 300)
-        self.snapshot_config = {
-            'show_timestamp': self.config.get('snapshots', {}).get('show_timestamp', True)
-        }
-        self.regions = self.config['regions']
-        if 'width' in self.config and 'height' in self.config:
-            self.frame_shape = (self.config['height'], self.config['width'], 3)
-        else:
-            self.frame_shape = get_frame_shape(self.ffmpeg_input)
-        self.frame_size = self.frame_shape[0] * self.frame_shape[1] * self.frame_shape[2]
-        self.mqtt_client = mqtt_client
-        self.mqtt_topic_prefix = '{}/{}'.format(mqtt_prefix, self.name)
-
-        # create shared value for storing the frame_time
-        self.frame_time = mp.Value('d', 0.0)
-        # Lock to control access to the frame
-        self.frame_lock = mp.Lock()
-        # Condition for notifying that a new frame is ready
-        self.frame_ready = mp.Condition()
-        # Condition for notifying that objects were tracked
-        self.objects_tracked = mp.Condition()
-
-        # Queue for prepped frames, max size set to (number of regions * 5)
-        self.resize_queue = queue.Queue()
-
-        # Queue for raw detected objects
-        self.detected_objects_queue = queue.Queue()
-        self.detected_objects_processor = DetectedObjectsProcessor(self)
-        self.detected_objects_processor.start()
-
-        # initialize the frame cache
-        self.cached_frame_with_objects = {
-            'frame_bytes': [],
-            'frame_time': 0
-        }
-
-        self.ffmpeg_process = None
-        self.capture_thread = None
-        self.fps = EventsPerSecond()
-        self.skipped_region_tracker = EventsPerSecond()
-
-        # combine tracked objects lists
-        self.objects_to_track = set().union(global_objects_config.get('track', ['person', 'car', 'truck']), camera_objects_config.get('track', []))
-
-        # merge object filters
-        global_object_filters = global_objects_config.get('filters', {})
-        camera_object_filters = camera_objects_config.get('filters', {})
-        objects_with_config = set().union(global_object_filters.keys(), camera_object_filters.keys())
-        self.object_filters = {}
-        for obj in objects_with_config:
-            self.object_filters[obj] = {**global_object_filters.get(obj, {}), **camera_object_filters.get(obj, {})}
-
-        # start a thread to track objects
-        self.object_tracker = ObjectTracker(self, 10)
-        self.object_tracker.start()
-
-        # start a thread to write tracked frames to disk
-        self.video_writer = VideoWriter(self)
-        self.video_writer.start()
-
-        # start a thread to queue resize requests for regions
-        self.region_requester = RegionRequester(self)
-        self.region_requester.start()
-
-        # start a thread to cache recent frames for processing
-        self.frame_tracker = FrameTracker(self.frame_time, 
-            self.frame_ready, self.frame_lock, self.frame_cache)
-        self.frame_tracker.start()
-
-        # start a thread to resize regions
-        self.region_prepper = RegionPrepper(self, self.frame_cache, self.resize_queue, prepped_frame_queue)
-        self.region_prepper.start()
-
-        # start a thread to store the highest scoring recent frames for monitored object types
-        self.best_frames = BestFrames(self)
-        self.best_frames.start()
-
-        # start a thread to expire objects from the detected objects list
-        self.object_cleaner = ObjectCleaner(self)
-        self.object_cleaner.start()
-
-        # start a thread to refine regions when objects are clipped
-        self.dynamic_region_fps = EventsPerSecond()
-        self.region_refiner = RegionRefiner(self)
-        self.region_refiner.start()
-        self.dynamic_region_fps.start()
-
-        # start a thread to publish object scores
-        mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self)
-        mqtt_publisher.start()
-
-        # create a watchdog thread for capture process
-        self.watchdog = CameraWatchdog(self)
-
-        # load in the mask for object detection
-        if 'mask' in self.config:
-            self.mask = cv2.imread("/config/{}".format(self.config['mask']), cv2.IMREAD_GRAYSCALE)
-        else:
-            self.mask = None
-
-        if self.mask is None:
-            self.mask = np.zeros((self.frame_shape[0], self.frame_shape[1], 1), np.uint8)
-            self.mask[:] = 255
-
-
-    def start_or_restart_capture(self):
-        if not self.ffmpeg_process is None:
-            print("Terminating the existing ffmpeg process...")
-            self.ffmpeg_process.terminate()
-            try:
-                print("Waiting for ffmpeg to exit gracefully...")
-                self.ffmpeg_process.wait(timeout=30)
-            except sp.TimeoutExpired:
-                print("FFmpeg didnt exit. Force killing...")
-                self.ffmpeg_process.kill()
-                self.ffmpeg_process.wait()
-
-            print("Waiting for the capture thread to exit...")
-            self.capture_thread.join()
-            self.ffmpeg_process = None
-            self.capture_thread = None
-        
-# # Thread to read the stdout of the ffmpeg process and update the current frame
-# class CameraCapture(threading.Thread):
-#     def __init__(self, camera):
-#         threading.Thread.__init__(self)
-#         self.camera = camera
-
-#     def run(self):
-#         prctl.set_name(self.__class__.__name__)
-#         frame_num = 0
-#         while True:
-#             if self.camera.ffmpeg_process.poll() != None:
-#                 print(self.camera.name + ": ffmpeg process is not running. exiting capture thread...")
-#                 break
-
-#             raw_image = self.camera.ffmpeg_process.stdout.read(self.camera.frame_size)
-
-#             if len(raw_image) == 0:
-#                 print(self.camera.name + ": ffmpeg didnt return a frame. something is wrong. exiting capture thread...")
-#                 break
-
-#             frame_num += 1
-#             if (frame_num % self.camera.take_frame) != 0:
-#                 continue
-
-#             with self.camera.frame_lock:
-#                 # TODO: use frame_queue instead
-#                 self.camera.frame_time.value = datetime.datetime.now().timestamp()
-#                 self.camera.frame_cache[self.camera.frame_time.value] = (
-#                     np
-#                     .frombuffer(raw_image, np.uint8)
-#                     .reshape(self.camera.frame_shape)
-#                 )
-#                 self.camera.frame_queue.put(self.camera.frame_time.value)
-#             # Notify with the condition that a new frame is ready
-#             with self.camera.frame_ready:
-#                 self.camera.frame_ready.notify_all()
-
-#             self.camera.fps.update()
-
-# class VideoWriter(threading.Thread):
-#     def __init__(self, camera):
-#         threading.Thread.__init__(self)
-#         self.camera = camera
-
-#     def run(self):
-#         prctl.set_name(self.__class__.__name__)
-#         while True:
-#             (frame_time, tracked_objects) = self.camera.frame_output_queue.get()
-#             # if len(tracked_objects) == 0:
-#             #     continue
-#             # f = open(f"/debug/output/{self.camera.name}-{str(format(frame_time, '.8f'))}.jpg", 'wb')
-#             # f.write(self.camera.frame_with_objects(frame_time, tracked_objects))
-#             # f.close()
-
-# class Camera:
-#     def __init__(self, name, ffmpeg_config, global_objects_config, config, tflite_process, mqtt_client, mqtt_prefix):
-#         self.name = name
-#         self.config = config
-#         self.detected_objects = defaultdict(lambda: [])
-#         self.frame_cache = {}
-#         self.last_processed_frame = None
-#         # queue for re-assembling frames in order
-#         self.frame_queue = queue.Queue()
-#         # track how many regions have been requested for a frame so we know when a frame is complete
-#         self.regions_in_process = {}
-#         # Lock to control access
-#         self.regions_in_process_lock = mp.Lock()
-#         self.finished_frame_queue = queue.Queue()
-#         self.refined_frame_queue = queue.Queue()
-#         self.frame_output_queue = queue.Queue()
-
-#         self.ffmpeg = config.get('ffmpeg', {})
-#         self.ffmpeg_input = get_ffmpeg_input(self.ffmpeg['input'])
-#         self.ffmpeg_global_args = self.ffmpeg.get('global_args', ffmpeg_config['global_args'])
-#         self.ffmpeg_hwaccel_args = self.ffmpeg.get('hwaccel_args', ffmpeg_config['hwaccel_args'])
-#         self.ffmpeg_input_args = self.ffmpeg.get('input_args', ffmpeg_config['input_args'])
-#         self.ffmpeg_output_args = self.ffmpeg.get('output_args', ffmpeg_config['output_args'])
-
-#         camera_objects_config = config.get('objects', {})
-
-#         self.take_frame = self.config.get('take_frame', 1)
-#         self.watchdog_timeout = self.config.get('watchdog_timeout', 300)
-#         self.snapshot_config = {
-#             'show_timestamp': self.config.get('snapshots', {}).get('show_timestamp', True)
-#         }
-#         self.regions = self.config['regions']
-#         self.frame_shape = get_frame_shape(self.ffmpeg_input)
-#         self.frame_size = self.frame_shape[0] * self.frame_shape[1] * self.frame_shape[2]
-#         self.mqtt_client = mqtt_client
-#         self.mqtt_topic_prefix = '{}/{}'.format(mqtt_prefix, self.name)
-
-#         # create shared value for storing the frame_time
-#         self.frame_time = mp.Value('d', 0.0)
-#         # Lock to control access to the frame
-#         self.frame_lock = mp.Lock()
-#         # Condition for notifying that a new frame is ready
-#         self.frame_ready = mp.Condition()
-#         # Condition for notifying that objects were tracked
-#         self.objects_tracked = mp.Condition()
-
-#         # Queue for prepped frames, max size set to (number of regions * 5)
-#         self.resize_queue = queue.Queue()
-
-#         # Queue for raw detected objects
-#         self.detected_objects_queue = queue.Queue()
-#         self.detected_objects_processor = DetectedObjectsProcessor(self)
-#         self.detected_objects_processor.start()
-
-#         # initialize the frame cache
-#         self.cached_frame_with_objects = {
-#             'frame_bytes': [],
-#             'frame_time': 0
-#         }
-
-#         self.ffmpeg_process = None
-#         self.capture_thread = None
-#         self.fps = EventsPerSecond()
-#         self.skipped_region_tracker = EventsPerSecond()
-
-#         # combine tracked objects lists
-#         self.objects_to_track = set().union(global_objects_config.get('track', ['person', 'car', 'truck']), camera_objects_config.get('track', []))
-
-#         # merge object filters
-#         global_object_filters = global_objects_config.get('filters', {})
-#         camera_object_filters = camera_objects_config.get('filters', {})
-#         objects_with_config = set().union(global_object_filters.keys(), camera_object_filters.keys())
-#         self.object_filters = {}
-#         for obj in objects_with_config:
-#             self.object_filters[obj] = {**global_object_filters.get(obj, {}), **camera_object_filters.get(obj, {})}
-
-#         # start a thread to track objects
-#         self.object_tracker = ObjectTracker(self, 10)
-#         self.object_tracker.start()
-
-#         # start a thread to write tracked frames to disk
-#         self.video_writer = VideoWriter(self)
-#         self.video_writer.start()
-
-#         # start a thread to queue resize requests for regions
-#         self.region_requester = RegionRequester(self)
-#         self.region_requester.start()
-
-#         # start a thread to cache recent frames for processing
-#         self.frame_tracker = FrameTracker(self.frame_time, 
-#             self.frame_ready, self.frame_lock, self.frame_cache)
-#         self.frame_tracker.start()
-
-#         # start a thread to resize regions
-#         self.region_prepper = RegionPrepper(self, self.frame_cache, self.resize_queue, prepped_frame_queue)
-#         self.region_prepper.start()
-
-#         # start a thread to store the highest scoring recent frames for monitored object types
-#         self.best_frames = BestFrames(self)
-#         self.best_frames.start()
-
-#         # start a thread to expire objects from the detected objects list
-#         self.object_cleaner = ObjectCleaner(self)
-#         self.object_cleaner.start()
-
-#         # start a thread to refine regions when objects are clipped
-#         self.dynamic_region_fps = EventsPerSecond()
-#         self.region_refiner = RegionRefiner(self)
-#         self.region_refiner.start()
-#         self.dynamic_region_fps.start()
-
-#         # start a thread to publish object scores
-#         mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self)
-#         mqtt_publisher.start()
-
-#         # create a watchdog thread for capture process
-#         self.watchdog = CameraWatchdog(self)
-
-#         # load in the mask for object detection
-#         if 'mask' in self.config:
-#             self.mask = cv2.imread("/config/{}".format(self.config['mask']), cv2.IMREAD_GRAYSCALE)
-#         else:
-#             self.mask = None
-
-#         if self.mask is None:
-#             self.mask = np.zeros((self.frame_shape[0], self.frame_shape[1], 1), np.uint8)
-#             self.mask[:] = 255
-
-
-#     def start_or_restart_capture(self):
-#         if not self.ffmpeg_process is None:
-#             print("Terminating the existing ffmpeg process...")
-#             self.ffmpeg_process.terminate()
-#             try:
-#                 print("Waiting for ffmpeg to exit gracefully...")
-#                 self.ffmpeg_process.wait(timeout=30)
-#             except sp.TimeoutExpired:
-#                 print("FFmpeg didnt exit. Force killing...")
-#                 self.ffmpeg_process.kill()
-#                 self.ffmpeg_process.wait()
-
-#             print("Waiting for the capture thread to exit...")
-#             self.capture_thread.join()
-#             self.ffmpeg_process = None
-#             self.capture_thread = None
-            
-#         # create the process to capture frames from the input stream and store in a shared array
-#         print("Creating a new ffmpeg process...")
-#         self.start_ffmpeg()
-        
-#         print("Creating a new capture thread...")
-#         self.capture_thread = CameraCapture(self)
-#         print("Starting a new capture thread...")
-#         self.capture_thread.start()
-#         self.fps.start()
-#         self.skipped_region_tracker.start()
-    
-#     def start_ffmpeg(self):
-#         ffmpeg_cmd = (['ffmpeg'] +
-#             self.ffmpeg_global_args +
-#             self.ffmpeg_hwaccel_args +
-#             self.ffmpeg_input_args +
-#             ['-i', self.ffmpeg_input] +
-#             self.ffmpeg_output_args +
-#             ['pipe:'])
-
-#         print(" ".join(ffmpeg_cmd))
-        
-#         self.ffmpeg_process = sp.Popen(ffmpeg_cmd, stdout = sp.PIPE, bufsize=self.frame_size)
-    
-#     def start(self):
-#         self.start_or_restart_capture()
-#         self.watchdog.start()
-    
-#     def join(self):
-#         self.capture_thread.join()
-    
-#     def get_capture_pid(self):
-#         return self.ffmpeg_process.pid
-    
-#     def get_best(self, label):
-#         return self.best_frames.best_frames.get(label)
-
-#     def stats(self):
-#         # TODO: anything else?
-#         return {
-#             'camera_fps': self.fps.eps(60),
-#             'resize_queue': self.resize_queue.qsize(),
-#             'frame_queue': self.frame_queue.qsize(),
-#             'finished_frame_queue': self.finished_frame_queue.qsize(),
-#             'refined_frame_queue': self.refined_frame_queue.qsize(),
-#             'regions_in_process': self.regions_in_process,
-#             'dynamic_regions_per_sec': self.dynamic_region_fps.eps(),
-#             'skipped_regions_per_sec': self.skipped_region_tracker.eps(60)
-#         }
-    
-#     def frame_with_objects(self, frame_time, tracked_objects=None):
-#         if not frame_time in self.frame_cache:
-#             frame = np.zeros(self.frame_shape, np.uint8)
-#         else:
-#             frame = self.frame_cache[frame_time].copy()
-            
-#         detected_objects = self.detected_objects[frame_time].copy()
-
-#         for region in self.regions:
-#             color = (255,255,255)
-#             cv2.rectangle(frame, (region['x_offset'], region['y_offset']), 
-#                 (region['x_offset']+region['size'], region['y_offset']+region['size']), 
-#                 color, 2)
-
-#         # draw the bounding boxes on the screen
-
-#         if tracked_objects is None:
-#             with self.object_tracker.tracked_objects_lock:
-#                 tracked_objects = copy.deepcopy(self.object_tracker.tracked_objects)
-
-#         for obj in detected_objects:
-#             draw_box_with_label(frame, obj['box']['xmin'], obj['box']['ymin'], obj['box']['xmax'], obj['box']['ymax'], obj['name'], "{}% {}".format(int(obj['score']*100), obj['area']), thickness=3)
-        
-#         for id, obj in tracked_objects.items():
-#             color = (0, 255,0) if obj['frame_time'] == frame_time else (255, 0, 0)
-#             draw_box_with_label(frame, obj['box']['xmin'], obj['box']['ymin'], obj['box']['xmax'], obj['box']['ymax'], obj['name'], id, color=color, thickness=1, position='bl')
-
-#         # print a timestamp
-#         time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
-#         cv2.putText(frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
-        
-#         # print fps
-#         cv2.putText(frame, str(self.fps.eps())+'FPS', (10, 60), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
-
-#         # convert to BGR
-#         frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
-
-#         # encode the image into a jpg
-#         ret, jpg = cv2.imencode('.jpg', frame)
-
-#         return jpg.tobytes()
-
-#     def get_current_frame_with_objects(self):
-#         frame_time = self.last_processed_frame
-#         if frame_time == self.cached_frame_with_objects['frame_time']:
-#             return self.cached_frame_with_objects['frame_bytes']
-
-#         frame_bytes = self.frame_with_objects(frame_time)
-
-#         self.cached_frame_with_objects = {
-#             'frame_bytes': frame_bytes,
-#             'frame_time': frame_time
-#         }
-
-#         return frame_bytes
-
-=======
->>>>>>> 2a2fbe7... cleanup old code
 def filtered(obj, objects_to_track, object_filters, mask):
     object_name = obj[0]