implementing a config file for a single camera

This commit is contained in:
blakeblackshear 2019-03-28 07:30:58 -05:00
parent 0514eeac03
commit 8774e537dc
3 changed files with 50 additions and 28 deletions

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@ -47,7 +47,8 @@ RUN pip install -U pip \
notebook \
Flask \
imutils \
paho-mqtt
paho-mqtt \
PyYAML
# Install tensorflow models object detection
RUN GIT_SSL_NO_VERIFY=true git clone -q https://github.com/tensorflow/models /usr/local/lib/python3.5/dist-packages/tensorflow/models

27
config/config.yml Normal file
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@ -0,0 +1,27 @@
web_port: 5000
mqtt:
host: mqtt.blakeshome.com
topic_prefix: cameras
cameras:
back:
rtsp:
user: viewer
host: 10.0.10.10
port: 554
password: $RTSP_PASSWORD
path: /cam/realmonitor?channel=1&subtype=2
regions:
- size: 350
x_offset: 0
y_offset: 300
min_person_size: 5000
- size: 400
x_offset: 350
y_offset: 250
min_person_size: 2000
- size: 400
x_offset: 750
y_offset: 250
min_person_size: 2000

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@ -9,6 +9,7 @@ import multiprocessing as mp
import queue
import threading
import json
import yaml
from contextlib import closing
import numpy as np
from object_detection.utils import visualization_utils as vis_util
@ -20,40 +21,33 @@ from frigate.mqtt import MqttMotionPublisher, MqttObjectPublisher
from frigate.objects import ObjectParser, ObjectCleaner, BestPersonFrame
from frigate.motion import detect_motion
from frigate.video import fetch_frames, FrameTracker
from frigate.object_detection import FramePrepper, PreppedQueueProcessor, detect_objects
from frigate.object_detection import FramePrepper, PreppedQueueProcessor
RTSP_URL = os.getenv('RTSP_URL')
with open('/config/config.yml') as f:
# use safe_load instead load
CONFIG = yaml.safe_load(f)
MQTT_HOST = os.getenv('MQTT_HOST')
MQTT_USER = os.getenv('MQTT_USER')
MQTT_PASS = os.getenv('MQTT_PASS')
MQTT_TOPIC_PREFIX = os.getenv('MQTT_TOPIC_PREFIX')
rtsp_camera = CONFIG['cameras']['back']['rtsp']
if (rtsp_camera['password'].startswith('$')):
rtsp_camera['password'] = os.getenv(rtsp_camera['password'][1:])
RTSP_URL = 'rtsp://{}:{}@{}:{}{}'.format(rtsp_camera['user'],
rtsp_camera['password'], rtsp_camera['host'], rtsp_camera['port'],
rtsp_camera['path'])
# REGIONS = "300,0,0,2000,200,no-mask-300.bmp:300,300,0,2000,200,no-mask-300.bmp:300,600,0,2000,200,no-mask-300.bmp:300,900,0,2000,200,no-mask-300.bmp:300,0,300,2000,200,no-mask-300.bmp:300,300,300,2000,200,no-mask-300.bmp:300,600,300,2000,200,no-mask-300.bmp:300,900,300,2000,200,no-mask-300.bmp"
# REGIONS = "400,350,250,50"
REGIONS = os.getenv('REGIONS')
MQTT_HOST = CONFIG['mqtt']['host']
MQTT_PORT = CONFIG.get('mqtt', {}).get('port', 1883)
MQTT_TOPIC_PREFIX = CONFIG['mqtt']['topic_prefix'] + '/back'
MQTT_USER = CONFIG.get('mqtt', {}).get('user')
MQTT_PASS = CONFIG.get('mqtt', {}).get('password')
DEBUG = (os.getenv('DEBUG') == '1')
WEB_PORT = CONFIG.get('web_port', 5000)
DEBUG = (CONFIG.get('debug', '0') == '1')
def main():
DETECTED_OBJECTS = []
recent_frames = {}
# Parse selected regions
regions = []
for region_string in REGIONS.split(':'):
region_parts = region_string.split(',')
regions.append({
'size': int(region_parts[0]),
'x_offset': int(region_parts[1]),
'y_offset': int(region_parts[2]),
'min_person_area': int(region_parts[3]),
# array for prepped frame with shape (1, 300, 300, 3)
'prepped_frame_array': mp.Array(ctypes.c_uint8, 300*300*3),
# shared value for storing the prepped_frame_time
'prepped_frame_time': mp.Value('d', 0.0),
# Lock to control access to the prepped frame
'prepped_frame_lock': mp.Lock()
})
regions = CONFIG['cameras']['back']['regions']
# capture a single frame and check the frame shape so the correct array
# size can be allocated in memory
video = cv2.VideoCapture(RTSP_URL)
@ -135,7 +129,7 @@ def main():
if not MQTT_USER is None:
client.username_pw_set(MQTT_USER, password=MQTT_PASS)
client.connect(MQTT_HOST, 1883, 60)
client.connect(MQTT_HOST, MQTT_PORT, 60)
client.loop_start()
# start a thread to publish object scores (currently only person)
@ -202,7 +196,7 @@ def main():
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + jpg.tobytes() + b'\r\n\r\n')
app.run(host='0.0.0.0', debug=False)
app.run(host='0.0.0.0', port=WEB_PORT, debug=False)
capture_process.join()
for detection_prep_thread in detection_prep_threads: