Mirrors/blakeblackshear.frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2025-08-13 13:47:36 +02:00
Code Issues Projects Releases Wiki Activity

add support for a camera 'label' to allow for tags other than 'person'. put 'label: cat' in a camera spec to make a good cat cam detector!

Browse Source
This commit is contained in:
alan 2019-12-23 18:56:58 -08:00
parent 5c01720567
commit 49ee0e0ee2
3 changed files with 10 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
frigate/mqtt.py
View File

@ -3,13 +3,14 @@ import cv2
import threading
class MqttObjectPublisher(threading.Thread):
def __init__(self, client, topic_prefix, objects_parsed, detected_objects, best_person_frame):
def __init__(self, client, topic_prefix, objects_parsed, detected_objects, best_person_frame, label):
threading.Thread.__init__(self)
self.client = client
self.topic_prefix = topic_prefix
self.objects_parsed = objects_parsed
self._detected_objects = detected_objects
self.best_person_frame = best_person_frame
self.label = label
def run(self):
last_sent_payload = ""
@ -24,7 +25,7 @@ class MqttObjectPublisher(threading.Thread):
# add all the person scores in detected objects
detected_objects = self._detected_objects.copy()
person_score = sum([obj['score'] for obj in detected_objects if obj['name'] == 'person'])
person_score = sum([obj['score'] for obj in detected_objects if obj['name'] == self.label])
# if the person score is more than 100, set person to ON
payload['person'] = 'ON' if int(person_score*100) > 100 else 'OFF'

5
frigate/objects.py
View File

@ -38,11 +38,12 @@ class ObjectCleaner(threading.Thread):
# Maintains the frame and person with the highest score from the most recent
# motion event
class BestPersonFrame(threading.Thread):
def __init__(self, objects_parsed, recent_frames, detected_objects):
def __init__(self, objects_parsed, recent_frames, detected_objects, label):
threading.Thread.__init__(self)
self.objects_parsed = objects_parsed
self.recent_frames = recent_frames
self.detected_objects = detected_objects
self.label = label
self.best_person = None
self.best_frame = None
@ -55,7 +56,7 @@ class BestPersonFrame(threading.Thread):
# make a copy of detected objects
detected_objects = self.detected_objects.copy()
detected_people = [obj for obj in detected_objects if obj['name'] == 'person']
detected_people = [obj for obj in detected_objects if obj['name'] == self.label]
# get the highest scoring person
new_best_person = max(detected_people, key=lambda x:x['score'], default=self.best_person)

7
frigate/video.py
View File

@ -130,6 +130,7 @@ class Camera:
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)
self.label = config.get('label', 'person')
# create a numpy array for the current frame in initialize to zeros
self.current_frame = np.zeros(self.frame_shape, np.uint8)
@ -170,7 +171,7 @@ class Camera:
self.frame_tracker.start()
# start a thread to store the highest scoring recent person frame
self.best_person_frame = BestPersonFrame(self.objects_parsed, self.recent_frames, self.detected_objects)
self.best_person_frame = BestPersonFrame(self.objects_parsed, self.recent_frames, self.detected_objects, self.label)
self.best_person_frame.start()
# start a thread to expire objects from the detected objects list
@ -178,7 +179,7 @@ class Camera:
self.object_cleaner.start()
# start a thread to publish object scores (currently only person)
mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self.objects_parsed, self.detected_objects, self.best_person_frame)
mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self.objects_parsed, self.detected_objects, self.best_person_frame, self.label)
mqtt_publisher.start()
# create a watchdog thread for capture process
@ -255,7 +256,7 @@ class Camera:
# Store object area to use in bounding box labels
obj['area'] = (obj['xmax']-obj['xmin'])*(obj['ymax']-obj['ymin'])
if obj['name'] == 'person':
if obj['name'] == self.label:
# find the matching region
region = None
for r in self.regions: