# Multi-camera streaming using Python The **gst-multi-camera-stream-example.py** application allows you to stream from two camera sensors simultaneously. The application composes the camera feeds side by side to display on a screen or encodes and stores the video streams to files. capsfilter qtivcomposer waylandsink qtiqmmfsrc/camera 0 qtiqmmfsrc/camera 1 capsfilter capsfilter v4l2h264enc h264parse mp4mux filesink qtiqmmfsrc/camera 0 qtiqmmfsrc/camera 1 capsfilter v4l2h264enc h264parse mp4mux filesink qtivcomposer composition Video encoding Qualcomm Open source **Figure : gst-multi-camera-example.py pipeline** For information about the plugins used in this pipeline, see [Pipeline flow](https://docs.qualcomm.com/doc/80-80021-50/topic/multi-camera-streaming-python-sample-app.html#section-vp3-hss-ndc). ## Run the application on the target device 1. Ensure that you complete the [Prerequisites](https://docs.qualcomm.com/doc/80-80021-50/topic/prerequisites-for-python-sample-applications.html). 2. Run any of the following use cases: - View the output (preview) on display: gst-multi-camera-stream-example.py -D 1 --width=1920 --height=1080 Copy to clipboard - View the encoder output: gst-multi-camera-stream-example.py -D 0 --width=1920 --height=1080 --framerate=30/1 Copy to clipboard 3. To display the available help options, run the following command: gst-multi-camera-stream-example.py --help Copy to clipboard ## Expected output For the video composition pipeline, the output is displayed as preview. ![../../_images/gst-multi-camera-example.png](data:image/png;base64,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) **Figure : Expected output for gst-multi-camera-example.py application–Preview** For video encoding pipeline, the output is saved to a file. ## Pipeline flow The following table lists the plugins used in the multi-camera streaming pipeline: | Pipeline | Description | | --- | --- | | Preview on display |

  1. qtiqmmfsrc captures video from both camera0 and camera1.


  2. Capsfilter is applied to enforce constraints on the raw video data.


  3. qtivcomposer composites the video streams and sends the composited video data to Wayland display sink.


  4. Waylandsink shows the live preview.


| | Encoder dump on the device |

  1. qtiqmmfsrc captures video from both camera0 and camera1.


  2. Capsfilter is applied to enforce constraints on the raw video data.


  3. v4l2h264enc is used to encode the video using the H.264 format.


  4. H264parse is used to parse the video.


  5. Mp4mux is used to multiplex the video into an MP4 container.


  6. Filesink is used to write the video to a file.


| ## Related information [Multi-camera streaming](https://docs.qualcomm.com/doc/80-80021-50/topic/gst-multi-camera-stream-example.html) Last Published: Mar 26, 2026 [Previous Topic Concurrent video playback (video wall) using Python](https://docs.qualcomm.com/bundle/publicresource/80-80021-50/topics/video-wall-using-python.md) [Next Topic Object detection and display](https://docs.qualcomm.com/bundle/publicresource/80-80021-50/topics/camera-detection-display.md)