update config example

Dockerfile

@@ -1,4 +1,4 @@
-FROM ubuntu:18.04
+FROM debian:stretch-slim
 LABEL maintainer "blakeb@blakeshome.com"
 
 ENV DEBIAN_FRONTEND=noninteractive
@@ -16,7 +16,7 @@ RUN apt -qq update && apt -qq install --no-install-recommends -y \
     # pillow-simd
     # zlib1g-dev libjpeg-dev \
     # VAAPI drivers for Intel hardware accel
-    libva-drm2 libva2 i965-va-driver vainfo \
+    i965-va-driver vainfo \
     && echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" > /etc/apt/sources.list.d/coral-edgetpu.list \
     && wget -q -O - https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - \
     && apt -qq update \

config/config.example.yml

@@ -81,12 +81,6 @@ cameras:
       # hwaccel_args: []
       # input_args: []
       # output_args: []
-    
-    ################
-    ## Optionally specify the resolution of the video feed. Frigate will try to auto detect if not specified
-    ################
-    # height: 1280
-    # width: 720
 
     ################
     ## Optional mask. Must be the same dimensions as your video feed.
@@ -106,19 +100,7 @@ cameras:
     take_frame: 1
 
     ################
-    # The number of seconds frigate will allow a camera to go without sending a frame before
-    # assuming the ffmpeg process has a problem and restarting.
-    ################
-    # watchdog_timeout: 300
-
-    ################
-    # Configuration for the snapshot sent over mqtt
-    ################
-    snapshots:
-      show_timestamp: True
-
-    ################
-    # Camera level object config. This config is merged with the global config above.
+    # Overrides for global object config
     ################
     objects:
       track:

frigate/objects.py

@@ -88,30 +88,21 @@ class DetectedObjectsProcessor(threading.Thread):
                     obj['clipped'] = True
                 
                 # Compute the area
-                # TODO: +1 right?
                 obj['area'] = (obj['box']['xmax']-obj['box']['xmin'])*(obj['box']['ymax']-obj['box']['ymin'])
 
                 self.camera.detected_objects[frame['frame_time']].append(obj)
             
-            # TODO: use in_process and processed counts instead to avoid lock 
             with self.camera.regions_in_process_lock:
-                if frame['frame_time'] in self.camera.regions_in_process:
-                    self.camera.regions_in_process[frame['frame_time']] -= 1
+                self.camera.regions_in_process[frame['frame_time']] -= 1
                 # print(f"{frame['frame_time']} remaining regions {self.camera.regions_in_process[frame['frame_time']]}")
 
-                    if self.camera.regions_in_process[frame['frame_time']] == 0:
-                        del self.camera.regions_in_process[frame['frame_time']]
-                        # print(f"{frame['frame_time']} no remaining regions")
-                        self.camera.finished_frame_queue.put(frame['frame_time'])
-                else:
+                if self.camera.regions_in_process[frame['frame_time']] == 0:
+                    del self.camera.regions_in_process[frame['frame_time']]
+                    # print(f"{frame['frame_time']} no remaining regions")
                     self.camera.finished_frame_queue.put(frame['frame_time'])
 
 # Thread that checks finished frames for clipped objects and sends back
 # for processing if needed
-# TODO: evaluate whether or not i really need separate threads/queues for each step
-#       given that only 1 thread will really be able to run at a time. you need a 
-#       separate process to actually do things in parallel for when you are CPU bound. 
-#       threads are good when you are waiting and could be processing while you wait
 class RegionRefiner(threading.Thread):
     def __init__(self, camera):
         threading.Thread.__init__(self)
@@ -369,9 +360,6 @@ class ObjectTracker(threading.Thread):
             # than the number of existing object centroids we need to
             # register each new input centroid as a trackable object
             # if D.shape[0] < D.shape[1]:
-            # TODO: rather than assuming these are new objects, we could
-            # look to see if any of the remaining boxes have a large amount
-            # of overlap...
             for col in unusedCols:
                 self.register(col, group[col])
 
@@ -411,8 +399,7 @@ class BestFrames(threading.Thread):
                         obj['box']['xmax'], obj['box']['ymax'], obj['name'], "{}% {}".format(int(obj['score']*100), obj['area']))
                     
                     # print a timestamp
-                    if self.camera.snapshot_config['show_timestamp']:
-                        time_to_show = datetime.datetime.fromtimestamp(obj['frame_time']).strftime("%m/%d/%Y %H:%M:%S")
-                        cv2.putText(best_frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
+                    time_to_show = datetime.datetime.fromtimestamp(obj['frame_time']).strftime("%m/%d/%Y %H:%M:%S")
+                    cv2.putText(best_frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
                     
                     self.best_frames[name] = best_frame

frigate/video.py

@@ -11,7 +11,6 @@ import numpy as np
 import prctl
 import copy
 import itertools
-import json
 from collections import defaultdict
 from frigate.util import tonumpyarray, LABELS, draw_box_with_label, calculate_region, EventsPerSecond
 from frigate.object_detection import RegionPrepper, RegionRequester
@@ -43,29 +42,8 @@ class FrameTracker(threading.Thread):
                     del self.recent_frames[k]
 
 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
+    # capture a single frame and check the frame shape so the correct array
+    # size can be allocated in memory
     video = cv2.VideoCapture(source)
     ret, frame = video.read()
     frame_shape = frame.shape
@@ -87,7 +65,7 @@ class CameraWatchdog(threading.Thread):
             # 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:
+            if self.camera.frame_time.value != 0.0 and (datetime.datetime.now().timestamp() - self.camera.frame_time.value) > 300:
                 print(self.camera.name + ": last frame is more than 5 minutes old, restarting camera capture...")
                 self.camera.start_or_restart_capture()
                 time.sleep(5)
@@ -173,15 +151,8 @@ class Camera:
         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_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)