Elements

Links under GStreamer element name (first column of the table) contain description of element properties, in the format generated by gst-inspect-1.0 utility

Element	Description
gvadetect	Performs object detection using SSD-like (including MobileNet-V1/V2 and ResNet), YoloV2/YoloV3/YoloV2-tiny/YoloV3-tiny and FasterRCNN-like object detection models.
gvaclassify	Performs object classification. Accepts the ROI or full frame as an input and outputs classification results with metadata.
gvainference	Runs deep learning inference using any model with an RGB or BGR input.
gvaaudiodetect	Performs audio event detection using AclNet model.
gvatrack	Performs object tracking using zero-term or short-term tracking algorithms. Zero-term tracking assigns unique object IDs and requires object detection to run on every frame. Short-term tracking allows to track objects between frames, thereby reducing the need to run object detection on each frame.
gvametaaggregate	Aggregates inference results from multiple pipeline branches.
gvametaconvert	Converts the metadata structure to the JSON format.
gvametapublish	Publishes the JSON metadata to MQTT or Kafka message brokers or files.
gvapython	Provides a callback to execute user-defined Python functions on every frame. Can be used for metadata conversion, inference post-processing, and other tasks.
gvawatermark	Overlays the metadata on the video frame to visualize the inference results.
gvafpscounter	Measures frames per second across multiple streams in a single process.
gvaattachroi	Provides the ability to define one or more regions of interest to perform inference on, instead of the full frame.
python_object_association	Assigns unique ID to ROI via DeepSORT algorithm.