mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
90 lines
3.1 KiB
Python
90 lines
3.1 KiB
Python
import cv2
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import time
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import queue
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import yaml
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import numpy as np
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from flask import Flask, Response, make_response
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import paho.mqtt.client as mqtt
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from frigate.video import Camera
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from frigate.object_detection import PreppedQueueProcessor
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with open('/config/config.yml') as f:
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CONFIG = yaml.safe_load(f)
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MQTT_HOST = CONFIG['mqtt']['host']
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MQTT_PORT = CONFIG.get('mqtt', {}).get('port', 1883)
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MQTT_TOPIC_PREFIX = CONFIG.get('mqtt', {}).get('topic_prefix', 'frigate')
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MQTT_USER = CONFIG.get('mqtt', {}).get('user')
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MQTT_PASS = CONFIG.get('mqtt', {}).get('password')
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WEB_PORT = CONFIG.get('web_port', 5000)
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DEBUG = (CONFIG.get('debug', '0') == '1')
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def main():
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# connect to mqtt and setup last will
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def on_connect(client, userdata, flags, rc):
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print("On connect called")
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# publish a message to signal that the service is running
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client.publish(MQTT_TOPIC_PREFIX+'/available', 'online', retain=True)
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client = mqtt.Client()
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client.on_connect = on_connect
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client.will_set(MQTT_TOPIC_PREFIX+'/available', payload='offline', qos=1, retain=True)
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if not MQTT_USER is None:
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client.username_pw_set(MQTT_USER, password=MQTT_PASS)
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client.connect(MQTT_HOST, MQTT_PORT, 60)
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client.loop_start()
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# Queue for prepped frames, max size set to (number of cameras * 5)
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max_queue_size = len(CONFIG['cameras'].items())*10
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prepped_frame_queue = queue.Queue(max_queue_size)
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cameras = {}
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for name, config in CONFIG['cameras'].items():
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cameras[name] = Camera(name, config, prepped_frame_queue, client, MQTT_TOPIC_PREFIX, DEBUG)
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prepped_queue_processor = PreppedQueueProcessor(
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cameras,
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prepped_frame_queue
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)
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prepped_queue_processor.start()
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for name, camera in cameras.items():
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camera.start()
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print("Capture process for {}: {}".format(name, camera.get_capture_pid()))
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# create a flask app that encodes frames a mjpeg on demand
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app = Flask(__name__)
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@app.route('/<camera_name>/best_person.jpg')
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def best_person(camera_name):
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best_person_frame = cameras[camera_name].get_best_person()
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if best_person_frame is None:
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best_person_frame = np.zeros((720,1280,3), np.uint8)
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ret, jpg = cv2.imencode('.jpg', best_person_frame)
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response = make_response(jpg.tobytes())
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response.headers['Content-Type'] = 'image/jpg'
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return response
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@app.route('/<camera_name>')
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def mjpeg_feed(camera_name):
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# return a multipart response
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return Response(imagestream(camera_name),
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mimetype='multipart/x-mixed-replace; boundary=frame')
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def imagestream(camera_name):
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while True:
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# max out at 5 FPS
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time.sleep(0.2)
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frame = cameras[camera_name].get_current_frame_with_objects()
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# encode the image into a jpg
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ret, jpg = cv2.imencode('.jpg', frame)
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yield (b'--frame\r\n'
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b'Content-Type: image/jpeg\r\n\r\n' + jpg.tobytes() + b'\r\n\r\n')
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app.run(host='0.0.0.0', port=WEB_PORT, debug=False)
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camera.join()
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if __name__ == '__main__':
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main() |