# GStreamer command-line use cases

Source: [https://docs.qualcomm.com/doc/80-70017-50/topic/gstreamer-application-use-cases.html](https://docs.qualcomm.com/doc/80-70017-50/topic/gstreamer-application-use-cases.html)

GStreamer provides command-line tools such as [gst-launch-1.0](https://gstreamer.freedesktop.org/documentation/tools/gst-launch.html) tool to help you run the AI/ML and
        multimedia use cases.

## Prerequisites

- To access your host device, enable SSH. For instructions, see [Log in using SSH](https://docs.qualcomm.com/bundle/publicresource/topics/80-70017-254/how_to.html#use-ssh).
Note: If SSH is enabled, you can skip this
                        prerequisite.
- Enter the SSH shell and run the use cases:

        ssh root@<ip-addr of the target device>Copy to clipboard
- Enable the
                    display:

        export XDG_RUNTIME_DIR=/dev/socket/weston && export WAYLAND_DISPLAY=wayland-1Copy to clipboard
- Push the files from the Linux
                    host:

        scp <filename> root@<IP address of target device>:/opt/Copy to clipboard

- Ensure that display is connected to the device via the HDMI port.

## Supported inputs sources for sample applications

Table : Supported input sources

| SoC | Camera input | File input | RTSP input |
| :--- | :--- | :--- | :--- |
| QCS6490 | ✔ | ✔ | ✔ |
| QCS9075 | ❌ | ✔ | ✔ |
| QCS8275 | ❌ | ✔ | ✔ |

Note: For QCS8275, audio use cases are not supported.

- **[Machine learning use cases](https://docs.qualcomm.com/doc/80-70017-50/topic/machine-learning-use-cases.html)**  

The TensorFlow Lite runtime and Qualcomm Neural Processing SDK runtime are used for         inference in the machine learning use cases.
- **[Multimedia use cases](https://docs.qualcomm.com/doc/80-70017-50/topic/multimedia-use-cases.html)**  

The multimedia use cases show various multimedia scenarios using the GStreamer         pipelines.

Last Published: Oct 01, 2026

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