create typed config classes

frigate/__main__.py

@@ -7,100 +7,31 @@ import multiprocessing as mp
 from playhouse.sqlite_ext import SqliteExtDatabase
 from typing import Dict, List
 
-from frigate.config import FRIGATE_CONFIG_SCHEMA
+from frigate.config import FrigateConfig
 from frigate.edgetpu import EdgeTPUProcess
 from frigate.events import EventProcessor
 from frigate.http import create_app
 from frigate.models import Event
 from frigate.mqtt import create_mqtt_client
 from frigate.object_processing import TrackedObjectProcessor
-from frigate.video import get_frame_shape, track_camera, get_ffmpeg_input, capture_camera
+from frigate.video import track_camera, capture_camera
 from frigate.watchdog import FrigateWatchdog
 
 class FrigateApp():
     def __init__(self):
         self.stop_event = mp.Event()
-        self.config: dict = None
+        self.config: FrigateConfig = None
         self.detection_queue = mp.Queue()
-        self.detectors: Dict[str: EdgeTPUProcess] = {}
-        self.detection_out_events: Dict[str: mp.Event] = {}
+        self.detectors: Dict[str, EdgeTPUProcess] = {}
+        self.detection_out_events: Dict[str, mp.Event] = {}
         self.detection_shms: List[mp.shared_memory.SharedMemory] = []
         self.camera_metrics = {}
     
     def init_config(self):
-        # TODO: sub in FRIGATE_ENV vars
-        frigate_env_vars = {k: v for k, v in os.environ.items() if k.startswith('FRIGATE_')}
         config_file = os.environ.get('CONFIG_FILE', '/config/config.yml')
+        self.config = FrigateConfig(config_file=config_file)
 
-        with open(config_file) as f:
-            raw_config = f.read()
-        
-        if config_file.endswith(".yml"):    
-            config = yaml.safe_load(raw_config)
-        elif config_file.endswith(".json"):
-            config = json.loads(raw_config)
-        
-        self.config = FRIGATE_CONFIG_SCHEMA(config)
-
-        if 'password' in self.config['mqtt']:
-            self.config['mqtt']['password'] = self.config['mqtt']['password'].format(**frigate_env_vars)
-
-        cache_dir = self.config['save_clips']['cache_dir']
-        clips_dir = self.config['save_clips']['clips_dir']
-
-        if not os.path.exists(cache_dir) and not os.path.islink(cache_dir):
-            os.makedirs(cache_dir)
-        if not os.path.exists(clips_dir) and not os.path.islink(clips_dir):
-            os.makedirs(clips_dir)
-
-        for camera_name, camera_config in self.config['cameras'].items():
-
-            # set shape
-            if 'width' in camera_config and 'height' in camera_config:
-                frame_shape = (camera_config['height'], camera_config['width'], 3)
-            else:
-                frame_shape = get_frame_shape(camera_config['ffmpeg']['input'])
-        
-            camera_config['frame_shape'] = frame_shape
-
-            # build ffmpeg command
-            ffmpeg = camera_config['ffmpeg']
-            ffmpeg_input = ffmpeg['input'].format(**frigate_env_vars)
-            ffmpeg_global_args = ffmpeg.get('global_args', self.config['ffmpeg']['global_args'])
-            ffmpeg_hwaccel_args = ffmpeg.get('hwaccel_args', self.config['ffmpeg']['hwaccel_args'])
-            ffmpeg_input_args = ffmpeg.get('input_args', self.config['ffmpeg']['input_args'])
-            ffmpeg_output_args = ffmpeg.get('output_args', self.config['ffmpeg']['output_args'])
-            if not camera_config.get('fps') is None:
-                ffmpeg_output_args = ["-r", str(camera_config['fps'])] + ffmpeg_output_args
-            if camera_config['save_clips']['enabled']:
-                ffmpeg_output_args = [
-                    "-f",
-                    "segment",
-                    "-segment_time",
-                    "10",
-                    "-segment_format",
-                    "mp4",
-                    "-reset_timestamps",
-                    "1",
-                    "-strftime",
-                    "1",
-                    "-c",
-                    "copy",
-                    "-an",
-                    "-map",
-                    "0",
-                    f"{os.path.join(self.config['save_clips']['cache_dir'], camera_name)}-%Y%m%d%H%M%S.mp4"
-                ] + ffmpeg_output_args
-            ffmpeg_cmd = (['ffmpeg'] +
-                    ffmpeg_global_args +
-                    ffmpeg_hwaccel_args +
-                    ffmpeg_input_args +
-                    ['-i', ffmpeg_input] +
-                    ffmpeg_output_args +
-                    ['pipe:'])
-            
-            camera_config['ffmpeg_cmd'] = ffmpeg_cmd
-
+        for camera_name in self.config.cameras.keys():
             # create camera_metrics
             self.camera_metrics[camera_name] = {
                 'camera_fps': mp.Value('d', 0.0),
@@ -118,10 +49,10 @@ class FrigateApp():
         self.event_queue = mp.Queue()
 
         # Queue for cameras to push tracked objects to
-        self.detected_frames_queue = mp.Queue(maxsize=len(self.config['cameras'].keys())*2)
+        self.detected_frames_queue = mp.Queue(maxsize=len(self.config.cameras.keys())*2)
 
     def init_database(self):
-        self.db = SqliteExtDatabase(f"/{os.path.join(self.config['save_clips']['clips_dir'], 'frigate.db')}")
+        self.db = SqliteExtDatabase(f"/{os.path.join(self.config.save_clips.clips_dir, 'frigate.db')}")
         models = [Event]
         self.db.bind(models)
         self.db.create_tables(models, safe=True)
@@ -130,38 +61,29 @@ class FrigateApp():
         self.flask_app = create_app(self.config, self.db, self.camera_metrics, self.detectors, self.detected_frames_processor)
 
     def init_mqtt(self):
-        # TODO: create config class
-        mqtt_config = self.config['mqtt']
-        self.mqtt_client = create_mqtt_client(
-            mqtt_config['host'],
-            mqtt_config['port'],
-            mqtt_config['topic_prefix'],
-            mqtt_config['client_id'],
-            mqtt_config.get('user'),
-            mqtt_config.get('password')
-        )
+        self.mqtt_client = create_mqtt_client(self.config.mqtt)
 
     def start_detectors(self):
-        for name in self.config['cameras'].keys():
+        for name in self.config.cameras.keys():
             self.detection_out_events[name] = mp.Event()
             shm_in = mp.shared_memory.SharedMemory(name=name, create=True, size=300*300*3)
             shm_out = mp.shared_memory.SharedMemory(name=f"out-{name}", create=True, size=20*6*4)
             self.detection_shms.append(shm_in)
             self.detection_shms.append(shm_out)
 
-        for name, detector in self.config['detectors'].items():
-            if detector['type'] == 'cpu':
+        for name, detector in self.config.detectors.items():
+            if detector.type == 'cpu':
                 self.detectors[name] = EdgeTPUProcess(self.detection_queue, out_events=self.detection_out_events, tf_device='cpu')
-            if detector['type'] == 'edgetpu':
-                self.detectors[name] = EdgeTPUProcess(self.detection_queue, out_events=self.detection_out_events, tf_device=detector['device'])
+            if detector.type == 'edgetpu':
+                self.detectors[name] = EdgeTPUProcess(self.detection_queue, out_events=self.detection_out_events, tf_device=detector.device)
 
     def start_detected_frames_processor(self):
-        self.detected_frames_processor = TrackedObjectProcessor(self.config['cameras'], self.mqtt_client, self.config['mqtt']['topic_prefix'], 
+        self.detected_frames_processor = TrackedObjectProcessor(self.config.cameras, self.mqtt_client, self.config.mqtt.topic_prefix, 
             self.detected_frames_queue, self.event_queue, self.stop_event)
         self.detected_frames_processor.start()
 
     def start_camera_processors(self):
-        for name, config in self.config['cameras'].items():
+        for name, config in self.config.cameras.items():
             camera_process = mp.Process(target=track_camera, args=(name, config,
                 self.detection_queue, self.detection_out_events[name], self.detected_frames_queue, 
                 self.camera_metrics[name]))
@@ -171,7 +93,7 @@ class FrigateApp():
             print(f"Camera processor started for {name}: {camera_process.pid}")
 
     def start_camera_capture_processes(self):
-        for name, config in self.config['cameras'].items():
+        for name, config in self.config.cameras.items():
             capture_process = mp.Process(target=capture_camera, args=(name, config,
                 self.camera_metrics[name]))
             capture_process.daemon = True
@@ -199,7 +121,7 @@ class FrigateApp():
         self.init_web_server()
         self.start_event_processor()
         self.start_watchdog()
-        self.flask_app.run(host='0.0.0.0', port=self.config['web_port'], debug=False)
+        self.flask_app.run(host='0.0.0.0', port=self.config.web_port, debug=False)
         self.stop()
     
     def stop(self):

frigate/config.py

@@ -1,5 +1,17 @@
+import base64
+import json
+import os
+import yaml
+
+from typing import Dict
+
+import cv2
+import matplotlib.pyplot as plt
+import numpy as np
 import voluptuous as vol
 
+from frigate.util import get_frame_shape
+
 DETECTORS_SCHEMA = vol.Schema(
     {
         vol.Required(str): {
@@ -66,12 +78,21 @@ FILTER_SCHEMA = vol.Schema(
     }
 )
 
-OBJECTS_SCHEMA = vol.Schema(
+def filters_for_all_tracked_objects(object_config):
+    for tracked_object in object_config.get('track', ['person']):
+        if not 'filters' in object_config:
+            object_config['filters'] = {}
+        if not tracked_object in object_config['filters']:
+            object_config['filters'][tracked_object] = {}
+    return object_config
+
+OBJECTS_SCHEMA = vol.Schema(vol.All(filters_for_all_tracked_objects,
     {
         vol.Optional('track', default=['person']): [str],
-        'filters': FILTER_SCHEMA.extend({vol.Optional('min_score', default=0.5): float})
+        # TODO: this should populate filters for all tracked objects
+        vol.Optional('filters', default = {}): FILTER_SCHEMA.extend({ str: {vol.Optional('min_score', default=0.5): float}})
     }
-)
+))
 
 DEFAULT_CAMERA_MQTT = {
     'crop_to_region': True
@@ -99,8 +120,8 @@ CAMERAS_SCHEMA = vol.Schema(
     {
         str: {
             vol.Required('ffmpeg'): CAMERA_FFMPEG_SCHEMA,
-            'height': int,
-            'width': int,
+            vol.Required('height'): int,
+            vol.Required('width'): int,
             'fps': int,
             'mask': str,
             vol.Optional('best_image_timeout', default=60): int,
@@ -140,3 +161,438 @@ FRIGATE_CONFIG_SCHEMA = vol.Schema(
         vol.Required('cameras', default={}): CAMERAS_SCHEMA
     }
 )
+
+class DetectorConfig():
+    def __init__(self, config):
+        self._type = config['type']
+        self._device = config['device']
+    
+    @property
+    def type(self):
+        return self._type
+    
+    @property
+    def device(self):
+        return self._device
+
+
+class MqttConfig():
+    def __init__(self, config):
+        self._host = config['host']
+        self._port = config['port']
+        self._topic_prefix = config['topic_prefix']
+        self._client_id = config['client_id']
+        self._user = config.get('user')
+        self._password = config.get('password')
+    
+    @property
+    def host(self):
+        return self._host
+    
+    @property
+    def port(self):
+        return self._port
+    
+    @property
+    def topic_prefix(self):
+        return self._topic_prefix
+    
+    @property
+    def client_id(self):
+        return self._client_id
+    
+    @property
+    def user(self):
+        return self._user
+    
+    @property
+    def password(self):
+        return self._password
+
+class SaveClipsConfig():
+    def __init__(self, config):
+        self._max_seconds = config['max_seconds']
+        self._clips_dir = config['clips_dir']
+        self._cache_dir = config['cache_dir']
+    
+    @property
+    def max_seconds(self):
+        return self._max_seconds
+    
+    @property
+    def clips_dir(self):
+        return self._clips_dir
+    
+    @property
+    def cache_dir(self):
+        return self._cache_dir
+
+class FfmpegConfig():
+    def __init__(self, global_config, config):
+        self._input = config.get('input')
+        self._global_args = config.get('global_args', global_config['global_args'])
+        self._hwaccel_args = config.get('hwaccel_args', global_config['hwaccel_args'])
+        self._input_args = config.get('input_args', global_config['input_args'])
+        self._output_args = config.get('output_args', global_config['output_args'])
+    
+    @property
+    def input(self):
+        return self._input
+    
+    @property
+    def global_args(self):
+        return self._global_args
+    
+    @property
+    def hwaccel_args(self):
+        return self._hwaccel_args
+
+    @property
+    def input_args(self):
+        return self._input_args
+    
+    @property
+    def output_args(self):
+        return self._output_args
+
+class FilterConfig():
+    def __init__(self, config):
+        self._min_area = config['min_area']
+        self._max_area = config['max_area']
+        self._threshold = config['threshold']
+        self._min_score = config.get('min_score')
+    
+    @property
+    def min_area(self):
+        return self._min_area
+
+    @property
+    def max_area(self):
+        return self._max_area
+
+    @property
+    def threshold(self):
+        return self._threshold
+    
+    @property
+    def min_score(self):
+        return self._min_score
+
+class ObjectConfig():
+    def __init__(self, global_config, config):
+        self._track = config.get('track', global_config['track'])
+        if 'filters' in config:
+            self._filters = { name: FilterConfig(c) for name, c in config['filters'].items() }
+        else:
+            self._filters = { name: FilterConfig(c) for name, c in global_config['filters'].items() }
+    
+    @property
+    def track(self):
+        return self._track
+    
+    @property
+    def filters(self) -> Dict[str, FilterConfig]:
+        return self._filters
+
+class CameraSnapshotsConfig():
+    def __init__(self, config):
+        self._show_timestamp = config['show_timestamp']
+        self._draw_zones = config['draw_zones']
+        self._draw_bounding_boxes = config['draw_bounding_boxes']
+    
+    @property
+    def show_timestamp(self):
+        return self._show_timestamp
+    
+    @property
+    def draw_zones(self):
+        return self._draw_zones
+
+    @property
+    def draw_bounding_boxes(self):
+        return self._draw_bounding_boxes
+
+class CameraSaveClipsConfig():
+    def __init__(self, config):
+        self._enabled = config['enabled']
+        self._pre_capture = config['pre_capture']
+        self._objects = config.get('objects')
+    
+    @property
+    def enabled(self):
+        return self._enabled
+    
+    @property
+    def pre_capture(self):
+        return self._pre_capture
+
+    @property
+    def objects(self):
+        return self._objects
+
+class CameraMqttConfig():
+    def __init__(self, config):
+        self._crop_to_region = config['crop_to_region']
+        self._snapshot_height = config.get('snapshot_height')
+    
+    @property
+    def crop_to_region(self):
+        return self._crop_to_region
+    
+    @property
+    def snapshot_height(self):
+        return self._snapshot_height
+
+class ZoneConfig():
+    def __init__(self, name, config):
+        self._coordinates = config['coordinates']
+        self._filters = { name: FilterConfig(c) for name, c in config['filters'].items() }
+
+        if isinstance(self._coordinates, list):
+            self._contour =  np.array([[int(p.split(',')[0]), int(p.split(',')[1])] for p in self._coordinates])
+        elif isinstance(self._coordinates, str):
+            points = self._coordinates.split(',')
+            self._contour =  np.array([[int(points[i]), int(points[i+1])] for i in range(0, len(points), 2)])
+        else:
+            print(f"Unable to parse zone coordinates for {name}")
+            self._contour = np.array([])
+        
+        self._color = (0,0,0)
+    
+    @property
+    def coordinates(self):
+        return self._coordinates
+    
+    @property
+    def contour(self):
+        return self._contour
+    
+    @contour.setter
+    def contour(self, val):
+        self._contour = val
+    
+    @property
+    def color(self):
+        return self._color
+    
+    @color.setter
+    def color(self, val):
+        self._color = val
+    
+    @property
+    def filters(self):
+        return self._filters
+
+class CameraConfig():
+    def __init__(self, name, config, cache_dir, global_ffmpeg, global_objects):
+        self._name = name
+        self._ffmpeg = FfmpegConfig(global_ffmpeg, config['ffmpeg'])
+        self._height = config.get('height')
+        self._width = config.get('width')
+        self._frame_shape = (self._height, self._width)
+        self._frame_shape_yuv = (self._frame_shape[0]*3//2, self._frame_shape[1])
+        self._fps = config.get('fps')
+        self._mask = self._create_mask(config.get('mask'))
+        self._best_image_timeout = config['best_image_timeout']
+        self._mqtt = CameraMqttConfig(config['mqtt'])
+        self._zones = { name: ZoneConfig(name, z) for name, z in config['zones'].items() }
+        self._save_clips = CameraSaveClipsConfig(config['save_clips'])
+        self._snapshots = CameraSnapshotsConfig(config['snapshots'])
+        self._objects = ObjectConfig(global_objects, config.get('objects', {}))
+
+        self._ffmpeg_cmd = self._get_ffmpeg_cmd(cache_dir)
+
+        self._set_zone_colors(self._zones)
+
+    def _create_mask(self, mask):
+        if mask:
+            if mask.startswith('base64,'):
+                img = base64.b64decode(mask[7:]) 
+                np_img = np.fromstring(img, dtype=np.uint8)
+                mask_img = cv2.imdecode(np_img, cv2.IMREAD_GRAYSCALE)
+            elif mask.startswith('poly,'):
+                points = mask.split(',')[1:]
+                contour =  np.array([[int(points[i]), int(points[i+1])] for i in range(0, len(points), 2)])
+                mask_img = np.zeros(self.frame_shape, np.uint8)
+                mask_img[:] = 255
+                cv2.fillPoly(mask_img, pts=[contour], color=(0))
+            else:
+                mask_img = cv2.imread(f"/config/{mask}", cv2.IMREAD_GRAYSCALE)
+        else:
+            mask_img = None
+
+        if mask_img is None or mask_img.size == 0:
+            mask_img = np.zeros(self.frame_shape, np.uint8)
+            mask_img[:] = 255
+        
+        return mask_img
+
+    def _get_ffmpeg_cmd(self, cache_dir):
+        ffmpeg_output_args = self.ffmpeg.output_args
+        if self.fps:
+            ffmpeg_output_args = ["-r", str(self.fps)] + ffmpeg_output_args
+        if self.save_clips.enabled:
+            ffmpeg_output_args = [
+                "-f",
+                "segment",
+                "-segment_time",
+                "10",
+                "-segment_format",
+                "mp4",
+                "-reset_timestamps",
+                "1",
+                "-strftime",
+                "1",
+                "-c",
+                "copy",
+                "-an",
+                f"{os.path.join(cache_dir, self.name)}-%Y%m%d%H%M%S.mp4"
+            ] + ffmpeg_output_args
+        return (['ffmpeg'] +
+                self.ffmpeg.global_args +
+                self.ffmpeg.hwaccel_args +
+                self.ffmpeg.input_args +
+                ['-i', self.ffmpeg.input] +
+                ffmpeg_output_args +
+                ['pipe:'])
+    
+    def _set_zone_colors(self, zones: Dict[str, ZoneConfig]):
+        # set colors for zones
+        all_zone_names = zones.keys()
+        zone_colors = {}
+        colors = plt.cm.get_cmap('tab10', len(all_zone_names))
+        for i, zone in enumerate(all_zone_names):
+            zone_colors[zone] = tuple(int(round(255 * c)) for c in colors(i)[:3])
+        
+        for name, zone in zones.items():
+            zone.color = zone_colors[name]
+    
+    @property
+    def name(self):
+        return self._name
+
+    @property
+    def ffmpeg(self):
+        return self._ffmpeg
+    
+    @property
+    def height(self):
+        return self._height
+    
+    @property
+    def width(self):
+        return self._width
+    
+    @property
+    def fps(self):
+        return self._fps
+    
+    @property
+    def mask(self):
+        return self._mask
+    
+    @property
+    def best_image_timeout(self):
+        return self._best_image_timeout
+    
+    @property
+    def mqtt(self):
+        return self._mqtt
+    
+    @property
+    def zones(self)-> Dict[str, ZoneConfig]:
+        return self._zones
+    
+    @property
+    def save_clips(self):
+        return self._save_clips
+    
+    @property
+    def snapshots(self):
+        return self._snapshots
+    
+    @property
+    def objects(self):
+        return self._objects
+
+    @property
+    def frame_shape(self):
+        return self._frame_shape
+
+    @property
+    def frame_shape_yuv(self):
+        return self._frame_shape_yuv
+
+    @property
+    def ffmpeg_cmd(self):
+        return self._ffmpeg_cmd
+
+class FrigateConfig():
+    def __init__(self, config_file=None, config=None):
+        if config is None and config_file is None:
+            raise ValueError('config or config_file must be defined')
+        elif not config_file is None:
+            config = self._load_file(config_file)
+        
+        config = FRIGATE_CONFIG_SCHEMA(config)
+
+        config = self._sub_env_vars(config)
+
+        self._web_port = config['web_port']
+        self._detectors = { name: DetectorConfig(d) for name, d in config['detectors'].items() }
+        self._mqtt = MqttConfig(config['mqtt'])
+        self._save_clips = SaveClipsConfig(config['save_clips'])
+        self._cameras = { name: CameraConfig(name, c, self._save_clips.cache_dir, config['ffmpeg'], config['objects']) for name, c in config['cameras'].items() }
+
+        self._ensure_dirs()
+
+    def _sub_env_vars(self, config):
+        frigate_env_vars = {k: v for k, v in os.environ.items() if k.startswith('FRIGATE_')}
+
+        if 'password' in config['mqtt']:
+            config['mqtt']['password'] = config['mqtt']['password'].format(**frigate_env_vars) 
+        
+        for camera in config['cameras'].values():
+            camera['ffmpeg']['input'] = camera['ffmpeg']['input'].format(**frigate_env_vars)
+        
+        return config
+    
+    def _ensure_dirs(self):
+        cache_dir = self.save_clips.cache_dir
+        clips_dir = self.save_clips.clips_dir
+
+        if not os.path.exists(cache_dir) and not os.path.islink(cache_dir):
+            os.makedirs(cache_dir)
+        if not os.path.exists(clips_dir) and not os.path.islink(clips_dir):
+            os.makedirs(clips_dir)
+
+    def _load_file(self, config_file):
+        with open(config_file) as f:
+            raw_config = f.read()
+        
+        if config_file.endswith(".yml"):    
+            config = yaml.safe_load(raw_config)
+        elif config_file.endswith(".json"):
+            config = json.loads(raw_config)
+        
+        return config
+    
+    @property
+    def web_port(self):
+        return self._web_port
+    
+    @property
+    def detectors(self) -> Dict[str, DetectorConfig]:
+        return self._detectors
+    
+    @property
+    def mqtt(self):
+        return self._mqtt
+    
+    @property
+    def save_clips(self):
+        return self._save_clips
+
+    @property
+    def cameras(self) -> Dict[str, CameraConfig]:
+        return self._cameras

frigate/events.py

@@ -14,8 +14,8 @@ class EventProcessor(threading.Thread):
     def __init__(self, config, camera_processes, event_queue, stop_event):
         threading.Thread.__init__(self)
         self.config = config
-        self.cache_dir = self.config['save_clips']['cache_dir']
-        self.clips_dir = self.config['save_clips']['clips_dir']
+        self.cache_dir = self.config.save_clips.cache_dir
+        self.clips_dir = self.config.save_clips.clips_dir
         self.camera_processes = camera_processes
         self.cached_clips = {}
         self.event_queue = event_queue
@@ -77,7 +77,7 @@ class EventProcessor(threading.Thread):
             earliest_event = datetime.datetime.now().timestamp()
 
         # if the earliest event exceeds the max seconds, cap it
-        max_seconds = self.config['save_clips']['max_seconds']
+        max_seconds = self.config.save_clips.max_seconds
         if datetime.datetime.now().timestamp()-earliest_event > max_seconds:
             earliest_event = datetime.datetime.now().timestamp()-max_seconds
         
@@ -163,15 +163,16 @@ class EventProcessor(threading.Thread):
 
             self.refresh_cache()
 
-            save_clips_config = self.config['cameras'][camera].get('save_clips', {})
+            save_clips_config = self.config.cameras[camera].save_clips
 
             # if save clips is not enabled for this camera, just continue
-            if not save_clips_config.get('enabled', False):
+            if not save_clips_config.enabled:
                 continue
 
             # if specific objects are listed for this camera, only save clips for them
-            if 'objects' in save_clips_config:
-                if not event_data['label'] in save_clips_config['objects']:
+            # TODO: default to all tracked objects rather than checking for None
+            if save_clips_config.objects:
+                if not event_data['label'] in save_clips_config.objects:
                     continue
 
             if event_type == 'start':
@@ -190,7 +191,7 @@ class EventProcessor(threading.Thread):
                 )
 
                 if len(self.cached_clips) > 0 and not event_data['false_positive']:
-                    self.create_clip(camera, event_data, save_clips_config.get('pre_capture', 30))
+                    self.create_clip(camera, event_data, save_clips_config.pre_capture)
                 del self.events_in_process[event_data['id']]
 
                 

frigate/http.py

@@ -75,7 +75,7 @@ def stats():
 
 @bp.route('/<camera_name>/<label>/best.jpg')
 def best(camera_name, label):
-    if camera_name in current_app.frigate_config['cameras']:
+    if camera_name in current_app.frigate_config.cameras:
         best_object = current_app.detected_frames_processor.get_best(camera_name, label)
         best_frame = best_object.get('frame')
         if best_frame is None:
@@ -103,7 +103,7 @@ def best(camera_name, label):
 def mjpeg_feed(camera_name):
     fps = int(request.args.get('fps', '3'))
     height = int(request.args.get('h', '360'))
-    if camera_name in current_app.frigate_config['cameras']:
+    if camera_name in current_app.frigate_config.cameras:
         # return a multipart response
         return Response(imagestream(current_app.detected_frames_processor, camera_name, fps, height),
                         mimetype='multipart/x-mixed-replace; boundary=frame')
@@ -112,7 +112,7 @@ def mjpeg_feed(camera_name):
 
 @bp.route('/<camera_name>/latest.jpg')
 def latest_frame(camera_name):
-    if camera_name in current_app.frigate_config['cameras']:
+    if camera_name in current_app.frigate_config.cameras:
         # max out at specified FPS
         frame = current_app.detected_frames_processor.get_current_frame(camera_name)
         if frame is None:

frigate/mqtt.py

@@ -1,7 +1,9 @@
 import paho.mqtt.client as mqtt
 
-def create_mqtt_client(host: str, port: int, client_id: str, topic_prefix: str, user: str, password: str):
-    client = mqtt.Client(client_id=client_id)
+from frigate.config import MqttConfig
+
+def create_mqtt_client(config: MqttConfig):
+    client = mqtt.Client(client_id=config.client_id)
     def on_connect(client, userdata, flags, rc):
         # TODO: use logging library
         print("On connect called")
@@ -14,11 +16,11 @@ def create_mqtt_client(host: str, port: int, client_id: str, topic_prefix: str,
                 print ("MQTT Not authorized")
             else:
                 print ("Unable to connect to MQTT: Connection refused. Error code: " + str(rc))
-        client.publish(topic_prefix+'/available', 'online', retain=True)       
+        client.publish(config.topic_prefix+'/available', 'online', retain=True)       
     client.on_connect = on_connect
-    client.will_set(topic_prefix+'/available', payload='offline', qos=1, retain=True)
-    if not user is None:
-        client.username_pw_set(user, password=password)
-    client.connect(host, port, 60)
+    client.will_set(config.topic_prefix+'/available', payload='offline', qos=1, retain=True)
+    if not config.user is None:
+        client.username_pw_set(config.user, password=config.password)
+    client.connect(config.host, config.port, 60)
     client.loop_start()
     return client

frigate/object_processing.py

@@ -13,6 +13,7 @@ import itertools
 import matplotlib.pyplot as plt
 from frigate.util import draw_box_with_label, SharedMemoryFrameManager
 from frigate.edgetpu import load_labels
+from frigate.config import CameraConfig
 from typing import Callable, Dict
 from statistics import mean, median
 
@@ -33,16 +34,16 @@ def zone_filtered(obj, object_config):
 
         # if the min area is larger than the
         # detected object, don't add it to detected objects
-        if obj_settings.get('min_area',-1) > obj['area']:
+        if obj_settings.min_area > obj['area']:
             return True
         
         # if the detected object is larger than the
         # max area, don't add it to detected objects
-        if obj_settings.get('max_area', 24000000) < obj['area']:
+        if obj_settings.max_area < obj['area']:
             return True
 
         # if the score is lower than the threshold, skip
-        if obj_settings.get('threshold', 0) > obj['computed_score']:
+        if obj_settings.threshold > obj['computed_score']:
             return True
         
     return False
@@ -58,7 +59,7 @@ class CameraState():
         self.object_status = defaultdict(lambda: 'OFF')
         self.tracked_objects = {}
         self.zone_objects = defaultdict(lambda: [])
-        self._current_frame = np.zeros((self.config['frame_shape'][0]*3//2, self.config['frame_shape'][1]), np.uint8)
+        self._current_frame = np.zeros(self.config.frame_shape_yuv, np.uint8)
         self.current_frame_lock = threading.Lock()
         self.current_frame_time = 0.0
         self.previous_frame_id = None
@@ -89,14 +90,14 @@ class CameraState():
                 region = obj['region']
                 cv2.rectangle(frame_copy, (region[0], region[1]), (region[2], region[3]), (0,255,0), 1)
             
-            if self.config['snapshots']['show_timestamp']:
+            if self.config.snapshots.show_timestamp:
                 time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
                 cv2.putText(frame_copy, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
 
-            if self.config['snapshots']['draw_zones']:
-                for name, zone in self.config['zones'].items():
+            if self.config.snapshots.draw_zones:
+                for name, zone in self.config.zones.items():
                     thickness = 8 if any([name in obj['zones'] for obj in tracked_objects.values()]) else 2
-                    cv2.drawContours(frame_copy, [zone['contour']], -1, zone['color'], thickness)
+                    cv2.drawContours(frame_copy, [zone.contour], -1, zone.color, thickness)
         
         return frame_copy
 
@@ -105,7 +106,7 @@ class CameraState():
         if not obj.get('false_positive', True):
             return False
 
-        threshold = self.config['objects'].get('filters', {}).get(obj['label'], {}).get('threshold', 0.85)
+        threshold = self.config.objects.filters[obj['label']].threshold
         if obj['computed_score'] < threshold:
             return True
         return False
@@ -124,7 +125,7 @@ class CameraState():
         self.current_frame_time = frame_time
         # get the new frame and delete the old frame
         frame_id = f"{self.name}{frame_time}"
-        current_frame = self.frame_manager.get(frame_id, (self.config['frame_shape'][0]*3//2, self.config['frame_shape'][1]))
+        current_frame = self.frame_manager.get(frame_id, self.config.frame_shape_yuv)
 
         current_ids = tracked_objects.keys()
         previous_ids = self.tracked_objects.keys()
@@ -184,12 +185,12 @@ class CameraState():
             current_zones = []
             bottom_center = (obj['centroid'][0], obj['box'][3])
             # check each zone
-            for name, zone in self.config['zones'].items():
-                contour = zone['contour']
+            for name, zone in self.config.zones.items():
+                contour = zone.contour
                 # check if the object is in the zone
                 if (cv2.pointPolygonTest(contour, bottom_center, False) >= 0):
                     # if the object passed the filters once, dont apply again
-                    if name in obj.get('zones', []) or not zone_filtered(obj, zone.get('filters', {})):
+                    if name in obj.get('zones', []) or not zone_filtered(obj, zone.filters):
                         current_zones.append(name)
                         obj['entered_zones'].add(name)
 
@@ -208,7 +209,7 @@ class CameraState():
                 now = datetime.datetime.now().timestamp()
                 # if the object is a higher score than the current best score 
                 # or the current object is older than desired, use the new object
-                if obj_copy['score'] > current_best['score'] or (now - current_best['frame_time']) > self.config.get('best_image_timeout', 60):
+                if obj_copy['score'] > current_best['score'] or (now - current_best['frame_time']) > self.config.best_image_timeout:
                     obj_copy['frame'] = np.copy(current_frame)
                     self.best_objects[object_type] = obj_copy
                     for c in self.callbacks['snapshot']:
@@ -249,7 +250,7 @@ class CameraState():
             self.previous_frame_id = frame_id
 
 class TrackedObjectProcessor(threading.Thread):
-    def __init__(self, camera_config, client, topic_prefix, tracked_objects_queue, event_queue, stop_event):
+    def __init__(self, camera_config: Dict[str, CameraConfig], client, topic_prefix, tracked_objects_queue, event_queue, stop_event):
         threading.Thread.__init__(self)
         self.camera_config = camera_config
         self.client = client
@@ -296,22 +297,22 @@ class TrackedObjectProcessor(threading.Thread):
                 return
             
             best_frame = cv2.cvtColor(obj['frame'], cv2.COLOR_YUV2BGR_I420)
-            if self.camera_config[camera]['snapshots']['draw_bounding_boxes']:
+            if self.camera_config[camera].snapshots.draw_bounding_boxes:
                 thickness = 2
                 color = COLOR_MAP[obj['label']]
                 box = obj['box']
                 draw_box_with_label(best_frame, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}", thickness=thickness, color=color)
                 
-            mqtt_config = self.camera_config[camera].get('mqtt', {'crop_to_region': False})
-            if mqtt_config.get('crop_to_region'):
+            mqtt_config = self.camera_config[camera].mqtt
+            if mqtt_config.crop_to_region:
                 region = obj['region']
                 best_frame = best_frame[region[1]:region[3], region[0]:region[2]]
-            if 'snapshot_height' in mqtt_config: 
-                height = int(mqtt_config['snapshot_height'])
+            if mqtt_config.snapshot_height: 
+                height = mqtt_config.snapshot_height
                 width = int(height*best_frame.shape[1]/best_frame.shape[0])
                 best_frame = cv2.resize(best_frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
             
-            if self.camera_config[camera]['snapshots']['show_timestamp']:
+            if self.camera_config[camera].snapshots.show_timestamp:
                 time_to_show = datetime.datetime.fromtimestamp(obj['frame_time']).strftime("%m/%d/%Y %H:%M:%S")
                 size = cv2.getTextSize(time_to_show, cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, thickness=2)
                 text_width = size[0][0]
@@ -351,26 +352,6 @@ class TrackedObjectProcessor(threading.Thread):
         #   }
         # }
         self.zone_data = defaultdict(lambda: defaultdict(lambda: set()))
-
-        # set colors for zones
-        all_zone_names = set([zone for config in self.camera_config.values() for zone in config['zones'].keys()])
-        zone_colors = {}
-        colors = plt.cm.get_cmap('tab10', len(all_zone_names))
-        for i, zone in enumerate(all_zone_names):
-            zone_colors[zone] = tuple(int(round(255 * c)) for c in colors(i)[:3])
-
-        # create zone contours
-        for camera_config in self.camera_config.values():
-            for zone_name, zone_config in camera_config['zones'].items():
-                zone_config['color'] = zone_colors[zone_name]
-                coordinates = zone_config['coordinates']
-                if isinstance(coordinates, list):
-                    zone_config['contour'] =  np.array([[int(p.split(',')[0]), int(p.split(',')[1])] for p in coordinates])
-                elif isinstance(coordinates, str):
-                    points = coordinates.split(',')
-                    zone_config['contour'] =  np.array([[int(points[i]), int(points[i+1])] for i in range(0, len(points), 2)])
-                else:
-                    print(f"Unable to parse zone coordinates for {zone_name} - {camera}")
         
     def get_best(self, camera, label):
         best_objects = self.camera_states[camera].best_objects
@@ -398,7 +379,7 @@ class TrackedObjectProcessor(threading.Thread):
             camera_state.update(frame_time, current_tracked_objects)
 
             # update zone status for each label
-            for zone in camera_state.config['zones'].keys():
+            for zone in camera_state.config.zones.keys():
                 # get labels for current camera and all labels in current zone
                 labels_for_camera = set([obj['label'] for obj in camera_state.tracked_objects.values() if zone in obj['zones'] and not obj['false_positive']])
                 labels_to_check = labels_for_camera | set(self.zone_data[zone].keys())

frigate/test/test_config.py

@@ -1,14 +1,11 @@
 import json
 from unittest import TestCase, main
 import voluptuous as vol
-from frigate.config import FRIGATE_CONFIG_SCHEMA
+from frigate.config import FRIGATE_CONFIG_SCHEMA, FrigateConfig
 
 class TestConfig(TestCase):
-    def test_empty(self):
-        FRIGATE_CONFIG_SCHEMA({})
-
-    def test_minimal(self):
-        minimal = {
+    def setUp(self):
+        self.minimal = {
             'mqtt': {
                 'host': 'mqtt'
             },
@@ -16,11 +13,169 @@ class TestConfig(TestCase):
                 'back': {
                     'ffmpeg': {
                         'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920
+                }
+            }
+        }
+    def test_empty(self):
+        FRIGATE_CONFIG_SCHEMA({})
+
+    def test_minimal(self):
+        FRIGATE_CONFIG_SCHEMA(self.minimal)
+    
+    def test_config_class(self):
+        FrigateConfig(config=self.minimal)
+    
+    def test_inherit_tracked_objects(self):
+        config = {
+            'mqtt': {
+                'host': 'mqtt'
+            },
+            'objects': {
+                'track': ['person', 'dog']
+            },
+            'cameras': {
+                'back': {
+                    'ffmpeg': {
+                        'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920
+                }
+            }
+        }
+        frigate_config = FrigateConfig(config=config)
+        assert('dog' in frigate_config.cameras['back'].objects.track)
+    
+    def test_override_tracked_objects(self):
+        config = {
+            'mqtt': {
+                'host': 'mqtt'
+            },
+            'objects': {
+                'track': ['person', 'dog']
+            },
+            'cameras': {
+                'back': {
+                    'ffmpeg': {
+                        'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920,
+                    'objects': {
+                        'track': ['cat']
                     }
                 }
             }
         }
-        FRIGATE_CONFIG_SCHEMA(minimal)
+        frigate_config = FrigateConfig(config=config)
+        assert('cat' in frigate_config.cameras['back'].objects.track)
+    
+    def test_default_object_filters(self):
+        config = {
+            'mqtt': {
+                'host': 'mqtt'
+            },
+            'objects': {
+                'track': ['person', 'dog']
+            },
+            'cameras': {
+                'back': {
+                    'ffmpeg': {
+                        'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920
+                }
+            }
+        }
+        frigate_config = FrigateConfig(config=config)
+        assert('dog' in frigate_config.cameras['back'].objects.filters)
+    
+    def test_inherit_object_filters(self):
+        config = {
+            'mqtt': {
+                'host': 'mqtt'
+            },
+            'objects': {
+                'track': ['person', 'dog'],
+                'filters': {
+                    'dog': {
+                        'threshold': 0.7
+                    }
+                }
+            },
+            'cameras': {
+                'back': {
+                    'ffmpeg': {
+                        'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920
+                }
+            }
+        }
+        frigate_config = FrigateConfig(config=config)
+        assert('dog' in frigate_config.cameras['back'].objects.filters)
+        assert(frigate_config.cameras['back'].objects.filters['dog'].threshold == 0.7)
+    
+    def test_override_object_filters(self):
+        config = {
+            'mqtt': {
+                'host': 'mqtt'
+            },
+            'cameras': {
+                'back': {
+                    'ffmpeg': {
+                        'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920,
+                    'objects': {
+                        'track': ['person', 'dog'],
+                        'filters': {
+                            'dog': {
+                                'threshold': 0.7
+                            }
+                        }
+                    }
+                }
+            }
+        }
+        frigate_config = FrigateConfig(config=config)
+        assert('dog' in frigate_config.cameras['back'].objects.filters)
+        assert(frigate_config.cameras['back'].objects.filters['dog'].threshold == 0.7)
+    
+    def test_ffmpeg_params(self):
+        config = {
+            'ffmpeg': {
+                'input_args': ['-re']
+            },
+            'mqtt': {
+                'host': 'mqtt'
+            },
+            'cameras': {
+                'back': {
+                    'ffmpeg': {
+                        'input': 'rtsp://10.0.0.1:554/video'
+                    },
+                    'height': 1080,
+                    'width': 1920,
+                    'objects': {
+                        'track': ['person', 'dog'],
+                        'filters': {
+                            'dog': {
+                                'threshold': 0.7
+                            }
+                        }
+                    }
+                }
+            }
+        }
+        frigate_config = FrigateConfig(config=config)
+        assert('-re' in frigate_config.cameras['back'].ffmpeg_cmd)
 
 if __name__ == '__main__':
     main(verbosity=2)

frigate/util.py

@@ -4,7 +4,9 @@ import time
 import signal
 import traceback
 import collections
+import json
 import numpy as np
+import subprocess as sp
 import cv2
 import threading
 import matplotlib.pyplot as plt
@@ -12,6 +14,36 @@ import hashlib
 from multiprocessing import shared_memory
 from typing import AnyStr
 
+def get_frame_shape(source):
+    ffprobe_cmd = " ".join([
+        'ffprobe',
+        '-v',
+        'panic',
+        '-show_error',
+        '-show_streams',
+        '-of',
+        'json',
+        '"'+source+'"'
+    ])
+    print(ffprobe_cmd)
+    p = sp.Popen(ffprobe_cmd, stdout=sp.PIPE, shell=True)
+    (output, err) = p.communicate()
+    p_status = p.wait()
+    info = json.loads(output)
+    print(info)
+
+    video_info = [s for s in info['streams'] if s['codec_type'] == 'video'][0]
+
+    if video_info['height'] != 0 and video_info['width'] != 0:
+        return (video_info['height'], video_info['width'], 3)
+    
+    # fallback to using opencv if ffprobe didnt succeed
+    video = cv2.VideoCapture(source)
+    ret, frame = video.read()
+    frame_shape = frame.shape
+    video.release()
+    return frame_shape
+
 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:
         color = (0,0,255)

frigate/video.py

@@ -14,45 +14,12 @@ import json
 import base64
 from typing import Dict, List
 from collections import defaultdict
+from frigate.config import CameraConfig
 from frigate.util import draw_box_with_label, yuv_region_2_rgb, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond, listen, FrameManager, SharedMemoryFrameManager
 from frigate.objects import ObjectTracker
 from frigate.edgetpu import RemoteObjectDetector
 from frigate.motion import MotionDetector
 
-def get_frame_shape(source):
-    ffprobe_cmd = " ".join([
-        'ffprobe',
-        '-v',
-        'panic',
-        '-show_error',
-        '-show_streams',
-        '-of',
-        'json',
-        '"'+source+'"'
-    ])
-    print(ffprobe_cmd)
-    p = sp.Popen(ffprobe_cmd, stdout=sp.PIPE, shell=True)
-    (output, err) = p.communicate()
-    p_status = p.wait()
-    info = json.loads(output)
-    print(info)
-
-    video_info = [s for s in info['streams'] if s['codec_type'] == 'video'][0]
-
-    if video_info['height'] != 0 and video_info['width'] != 0:
-        return (video_info['height'], video_info['width'], 3)
-    
-    # fallback to using opencv if ffprobe didnt succeed
-    video = cv2.VideoCapture(source)
-    ret, frame = video.read()
-    frame_shape = frame.shape
-    video.release()
-    return frame_shape
-
-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)
-
 def filtered(obj, objects_to_track, object_filters, mask=None):
     object_name = obj[0]
 
@@ -64,16 +31,16 @@ def filtered(obj, objects_to_track, object_filters, mask=None):
 
         # if the min area is larger than the
         # detected object, don't add it to detected objects
-        if obj_settings.get('min_area',-1) > obj[3]:
+        if obj_settings.min_area > obj[3]:
             return True
         
         # if the detected object is larger than the
         # max area, don't add it to detected objects
-        if obj_settings.get('max_area', 24000000) < obj[3]:
+        if obj_settings.max_area < obj[3]:
             return True
 
         # if the score is lower than the min_score, skip
-        if obj_settings.get('min_score', 0) > obj[1]:
+        if obj_settings.min_score > obj[1]:
             return True
     
         # compute the coordinates of the object and make sure
@@ -118,7 +85,7 @@ def start_or_restart_ffmpeg(ffmpeg_cmd, frame_size, ffmpeg_process=None):
 def capture_frames(ffmpeg_process, camera_name, frame_shape, frame_manager: FrameManager, 
     frame_queue, fps:mp.Value, skipped_fps: mp.Value, current_frame: mp.Value):
 
-    frame_size = frame_shape[0] * frame_shape[1] * 3 // 2
+    frame_size = frame_shape[0] * frame_shape[1]
     frame_rate = EventsPerSecond()
     frame_rate.start()
     skipped_eps = EventsPerSecond()
@@ -166,8 +133,8 @@ class CameraWatchdog(threading.Thread):
         self.camera_fps = camera_fps
         self.ffmpeg_pid = ffmpeg_pid
         self.frame_queue = frame_queue
-        self.frame_shape = self.config['frame_shape']
-        self.frame_size = self.frame_shape[0] * self.frame_shape[1] * 3 // 2
+        self.frame_shape = self.config.frame_shape_yuv
+        self.frame_size = self.frame_shape[0] * self.frame_shape[1]
 
     def run(self):
         self.start_ffmpeg()
@@ -192,7 +159,7 @@ class CameraWatchdog(threading.Thread):
             time.sleep(10)
     
     def start_ffmpeg(self):
-        self.ffmpeg_process = start_or_restart_ffmpeg(self.config['ffmpeg_cmd'], self.frame_size)
+        self.ffmpeg_process = start_or_restart_ffmpeg(self.config.ffmpeg_cmd, self.frame_size)
         self.ffmpeg_pid.value = self.ffmpeg_process.pid
         self.capture_thread = CameraCapture(self.name, self.ffmpeg_process, self.frame_shape, self.frame_queue, 
             self.camera_fps)
@@ -203,7 +170,6 @@ class CameraCapture(threading.Thread):
         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.fps = fps
         self.skipped_fps = EventsPerSecond()
@@ -217,44 +183,21 @@ class CameraCapture(threading.Thread):
         capture_frames(self.ffmpeg_process, self.name, self.frame_shape, self.frame_manager, self.frame_queue,
             self.fps, self.skipped_fps, self.current_frame)
 
-def capture_camera(name, config, process_info):
+def capture_camera(name, config: CameraConfig, process_info):
     frame_queue = process_info['frame_queue']
     camera_watchdog = CameraWatchdog(name, config, frame_queue, process_info['camera_fps'], process_info['ffmpeg_pid'])
     camera_watchdog.start()
     camera_watchdog.join()
 
-def track_camera(name, config, detection_queue, result_connection, detected_objects_queue, process_info):
+def track_camera(name, config: CameraConfig, detection_queue, result_connection, detected_objects_queue, process_info):
     listen()
 
     frame_queue = process_info['frame_queue']
 
-    frame_shape = config['frame_shape']
-
-    # Merge the tracked object config with the global config
-    camera_objects_config = config.get('objects', {})
-    objects_to_track = camera_objects_config.get('track', [])
-    object_filters = camera_objects_config.get('filters', {})
-
-    # load in the mask for object detection
-    if 'mask' in config:
-        if config['mask'].startswith('base64,'):
-            img = base64.b64decode(config['mask'][7:]) 
-            npimg = np.fromstring(img, dtype=np.uint8)
-            mask = cv2.imdecode(npimg, cv2.IMREAD_GRAYSCALE)
-        elif config['mask'].startswith('poly,'):
-            points = config['mask'].split(',')[1:]
-            contour =  np.array([[int(points[i]), int(points[i+1])] for i in range(0, len(points), 2)])
-            mask = np.zeros((frame_shape[0], frame_shape[1]), np.uint8)
-            mask[:] = 255
-            cv2.fillPoly(mask, pts=[contour], color=(0))
-        else:
-            mask = cv2.imread("/config/{}".format(config['mask']), cv2.IMREAD_GRAYSCALE)
-    else:
-        mask = None
-
-    if mask is None or mask.size == 0:
-        mask = np.zeros((frame_shape[0], frame_shape[1]), np.uint8)
-        mask[:] = 255
+    frame_shape = config.frame_shape
+    objects_to_track = config.objects.track
+    object_filters = config.objects.filters
+    mask = config.mask
 
     motion_detector = MotionDetector(frame_shape, mask, resize_factor=6)
     object_detector = RemoteObjectDetector(name, '/labelmap.txt', detection_queue, result_connection)
@@ -301,7 +244,7 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape,
     frame_manager: FrameManager, motion_detector: MotionDetector, 
     object_detector: RemoteObjectDetector, object_tracker: ObjectTracker,
     detected_objects_queue: mp.Queue, process_info: Dict,
-    objects_to_track: List[str], object_filters: Dict, mask,
+    objects_to_track: List[str], object_filters, mask,
     exit_on_empty: bool = False):
     
     fps = process_info['process_fps']