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.

gvaactionrecognitionbin

Performs full-frame action recognition inference using action-recognition-0001’s/driver-action-recognition-adas-0002’s encoder and decoder models.