# Elements
Links under the GStreamer element name (first column of the table) contain
the description of element properties, in the format generated by
gst-inspect-1.0 utility.
## Inference plugins
| Element | Description |
|----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [gvadetect](./gvadetect.md) | Performs object detection and *optionally* object classification/segmentation/pose estimation. Inputs: ROIs (regions of interest) or full frame. Output: object bounding box detection along with prediction metadata. The `queue` element must be put directly after the `gvadetect` element in pipeline.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect model=$mDetect device=GPU[CPU,NPU] ! queue ! … OUT
|
| [gvaclassify](./gvaclassify.md) | Performs object classification/segmentation/pose estimation. Inputs: ROIs or full frame. Output: prediction metadata. The `queue` element must be put directly after the `gvaclassify` element in the pipeline.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect model=$mDetect device=GPU ! queue ! gvaclassify model=$mClassify device=CPU ! queue ! … OUT
|
| [gvainference](./gvainference.md) | Executes any inference model and outputs raw results. Does not interpret data and does not generate metadata. The `queue` element must be put directly after the `gvainference` element in the pipeline.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect model=$mDetect device=GPU ! queue ! gvainference model=$mHeadPoseEst device=CPU ! queue ! … OUT
|
| [gvatrack](./gvatrack.md) | Tracks objects across video frames using zero-term or short-term tracking algorithms. Zero-term tracking assigns unique object IDs and requires object detection to run on every frame. Short-term tracking allows for tracking objects between frames, reducing the need to run object detection on each frame.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect model=$mDetect device=GPU ! gvatrack tracking-type=short-term-imageless ! … OUT
|
| [gvaaudiodetect](./gvaaudiodetect.md) | Legacy plugin. Performs audio event detection using the `AclNet` model.
Example:
gst-launch-1.0 … ! decodebin3 ! audioresample ! audioconvert ! audio/x-raw … ! audiomixer … ! gvaaudiodetect model=$mAudioDetect ! … OUT
|
| [gvagenai](./gvagenai.md) | Performs inference using GenAI models. It can be used to generate text descriptions from images or video.
Example:
gst-launch-1.0 … ! decodebin3 ! videoconvert ! gvagenai model=$mGenAI device=GPU ! … OUT
|
## Auxiliary plugins
| Element | Description |
|------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [gvaattachroi](./gvaattachroi.md) | Adds user-defined regions of interest to perform inference on (instead of full frame). Example: monitoring road traffic in a city camera feed; splitting large image into smaller pieces, and running inference on each piece (healthcare cell analytics).
Example:
gst-launch-1.0 … ! decodebin3 ! gvaattachroi roi=xtl,ytl,xbr,ybr gvadetect inference-region=1 ! … OUT
|
| [gvafpscounter](./gvafpscounter.md) | Measures frames per second across multiple video streams in a single GStreamer process.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect … ! gvafpscounter ! … OUT
|
| [gvametaaggregate](./gvametaaggregate.md) | Aggregates inference results from multiple pipeline branches.
Example:
gst-launch-1.0 … ! decodebin3 ! tee name=t t. ! queue ! gvametaaggregate name=a ! gvaclassify … ! gvaclassify … ! gvametaconvert … ! gvametapublish … ! fakesink t. ! queue ! gvadetect … ! a.
|
| [gvametaconvert](./gvametaconvert.md) | Converts the metadata structure to JSON or raw text formats. Can write output to a file.|
| [gvametapublish](./gvametapublish.md) | Publishes the JSON metadata to MQTT or Kafka message brokers or files.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect model=$mDetect device=GPU … ! gvametaconvert format=json … ! gvametapublish … ! … OUT
|
| [gvapython](./gvapython.md) | Provides a callback to execute user-defined Python functions on every frame. It is used to augment DLStreamer with user-defined algorithms (e.g. metadata conversion, inference post-processing).
Example:
gst-launch-1.0 … ! gvaclassify ! gvapython module={gvapython.callback_module.classAge_pp} ! … OUT
|
| [gvarealsense](./gvarealsense.md) | Provides integration with Intel RealSense cameras, enabling video and depth stream capture for use in GStreamer pipelines. |
| [gvawatermark](./gvawatermark.md) | Overlays the metadata on the video frame to visualize the inference results.
Example:
gst-launch-1.0 … ! decodebin3 ! gvadetect … ! gvawatermark ! … |
:::{toctree}
:maxdepth: 1
:hidden:
gvadetect
gvaclassify
gvainference
gvatrack
gvaaudiodetect
gvagenai
gvaattachroi
gvafpscounter
gvametaaggregate
gvametaconvert
gvametapublish
gvapython
gvarealsense
gvawatermark
gstelements
:::