Overview Object Counting Node

Overview Object Counting Node

The Object Counting Node is used to count one or multiple objects which are previously detected by the object detection node.

Input and Output
  1. Input: MQTT message (results from object detection node)
  2. Output: MQTT message containing IN / OUT results for each detected label or object.
Node Sections
The Object Counting node consists of two main parts:
  1. General Settings: Select the camera mode, backup and publish interval (for publishing messages to the cloud)
  2. Other Settings: Set the colors of the detection output boxes and define if the output boxes should be shown or not.
Node Parameters
The following parameters are used in the Object Counting node.

Name: Input the node name used in a specific flow.
  1. default: object-counting
  2. type: string
Camera Mode: Select if your camera is mounted to view a horizontal or vertical scene. Depending on the selection, the proper algorithms will be selected. We currently support horizontal mode.
  1. default: horizontal
Backup Interval: The backup interval specifies for how long the container will store the results of object counts. The results are stored in a csv file in case something happens to the container or device. When the device recovers it it will restore the latest values from the csv and starts counting again from the last value.
  1. default: 1 hour
Publish Interval: The container uploads the counting data to the cloud InfluxDB every publish interval.

Show Result: Defines if the detection output boxes should be shown or not.
  1. default: true
  2. type: boolean
Text Color: Refers to the color of the text with the counting information shown on the preview video stream.
  1. Default: [100, 255, 255]
Line Color: Refers to the color of the line for the boxes which are showing the detection results in the preview video stream.
  1. Default: [200, 50, 50]



    • Related Articles

    • Overview Object Flow Node

      The Object Flow Node detects and tracks people from an input video stream to compose a heatmap and to calculate the average dwell time. Input and Output Input: Object Detection mqtt result message, ROI section definition, Object Counting result ...
    • Overview Object Tracking Node

      The Object Tracking Node is used to track several objects which were previously detected by the object detection node across several frames.  Input and Output Input: Output of object detection node. Output: MQTT message containing the tracking ...
    • Overview Object Detection Node

      The Object Detection Node is used to detect several different objects off the shelf with pre-trained or custom deep learning models on GPU, CPU, VPU (Intel Movidius Myriad X) or TPU (Google Coral). Input and Output Input: Frame from a video file, IP ...
    • Overview Object Segmentation Node

      The Object Segmentation Node is used to segment several different objects off the shelf with pre-trained or custom deep learning models on GPU, CPU, VPU (Myriad) and TPU. Input and Output Input: Frame from a video file, IP or USB camera. Output: MQTT ...
    • Overview Region of Interest (ROI) Node

      The Region of Interest (ROI) node allows to filter a portion of an image that you want to perform some other operation on. ROI can be set for each camera stream and is therefore device specific. While the ROI node needs to be added to your flow, it ...