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	prevent unnecessary early exit from loop
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				@ -13,7 +13,7 @@ This results in a MJPEG stream with objects identified that has a lower latency
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## Getting Started
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Build the container with
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```
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docker build -t realtime-od .
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docker build -t frigate .
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```
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Download a model from the [zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md).
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@ -31,7 +31,7 @@ docker run --rm \
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-e MQTT_HOST='your.mqtthost.com' \
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-e MQTT_TOPIC_PREFIX='cameras/1' \
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-e DEBUG='0' \
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realtime-od:latest
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frigate:latest
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```
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Example compose:
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@ -39,7 +39,7 @@ Example compose:
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  frigate:
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    container_name: frigate
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    restart: unless-stopped
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    image: realtime-od:latest
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    image: frigate:latest
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    volumes:
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      - <path_to_frozen_detection_graph.pb>:/frozen_inference_graph.pb:ro
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      - <path_to_labelmap.pbtext>:/label_map.pbtext:ro
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@ -70,11 +70,6 @@ def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, motion
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        cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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        cnts = imutils.grab_contours(cnts)
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        # if there are no contours, there is no motion
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        if len(cnts) < 1:
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            motion_frames = 0
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            continue
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        motion_found = False
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        # loop over the contours
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