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update config example
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@ -47,16 +47,24 @@ mqtt:
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# - rgb24
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####################
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# Global object configuration. Applies to all cameras and regions
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# unless overridden at the camera/region levels.
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# Global object configuration. Applies to all cameras
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# unless overridden at the camera levels.
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# Keys must be valid labels. By default, the model uses coco (https://dl.google.com/coral/canned_models/coco_labels.txt).
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# All labels from the model are reported over MQTT. These values are used to filter out false positives.
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# min_area (optional): minimum width*height of the bounding box for the detected person
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# max_area (optional): maximum width*height of the bounding box for the detected person
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# threshold (optional): The minimum decimal percentage (50% hit = 0.5) for the confidence from tensorflow
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####################
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objects:
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person:
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min_area: 5000
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max_area: 100000
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threshold: 0.5
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track:
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- person
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- car
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- truck
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filters:
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person:
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min_area: 5000
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max_area: 100000
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threshold: 0.5
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cameras:
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back:
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@ -91,18 +99,21 @@ cameras:
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################
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take_frame: 1
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################
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# Overrides for global object config
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################
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objects:
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person:
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min_area: 5000
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max_area: 100000
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threshold: 0.5
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track:
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- person
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filters:
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person:
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min_area: 5000
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max_area: 100000
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threshold: 0.5
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################
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# size: size of the region in pixels
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# x_offset/y_offset: position of the upper left corner of your region (top left of image is 0,0)
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# min_person_area (optional): minimum width*height of the bounding box for the detected person
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# max_person_area (optional): maximum width*height of the bounding box for the detected person
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# threshold (optional): The minimum decimal percentage (50% hit = 0.5) for the confidence from tensorflow
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# Tips: All regions are resized to 300x300 before detection because the model is trained on that size.
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# Resizing regions takes CPU power. Ideally, all regions should be as close to 300x300 as possible.
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# Defining a region that goes outside the bounds of the image will result in errors.
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@ -111,18 +122,9 @@ cameras:
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- size: 350
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x_offset: 0
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y_offset: 300
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objects:
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car:
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threshold: 0.2
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- size: 400
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x_offset: 350
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y_offset: 250
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objects:
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person:
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min_area: 2000
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- size: 400
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x_offset: 750
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y_offset: 250
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objects:
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person:
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min_area: 2000
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