Overview Object Flow Node

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
  1. Input: Object Detection mqtt result message, ROI section definition, Object Counting result message (optional)
  2. Output: Heatmap image (base64 format), dwell time information
  3. Supported architecture: Currently supported on amd64 devices.
Node Parameters
The following parameters are used in the object flow node.

Name: Input the node name used in a specific flow.
  1. default: object flow
  2. type: string
Upload Interval: The upload interval defines the interval for uploading the output data to the cloud. After each upload interval, the data is reset. This means that the heatmap is based on the data during the upload interval (and recalculated every interval).

    • Related Articles

    • 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 Input: MQTT message (results from object detection node) Output: MQTT message containing IN / OUT results ...

    • 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 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 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 Image Classification Node

      The Image Classification Node is used to classify an image into several categories, using pre-trained or custom deep learning models on GPU, CPU, TPU and VPU. Input and Output Input: Frame from a video file, IP or USB camera. Output: MQTT message ...