# Image segmentation and encode with LiteRT Source: [https://docs.qualcomm.com/doc/80-70022-50/topic/single-camera-stream-with-image-segmentation-and-encode.html](https://docs.qualcomm.com/doc/80-70022-50/topic/single-camera-stream-with-image-segmentation-and-encode.html) The use case implements the `deeplabv3_resnet50` LiteRT model to compose the semantic segmentations and original video stream, encode this stream, and then multiplex it in an MP4 container. Note: For Ubuntu Server, `sudo` access is necessary to write the encoded stream to the `/etc/media` folder. Run the use case on the target device: gst-launch-1.0 -e --gst-debug=2 \ qtiqmmfsrc name=camsrc ! video/x-raw,format=NV12_Q08C,width=1280,height=720,framerate=30/1 ! queue ! tee name=split \ split. ! queue ! qtivcomposer name=mixer sink_1::dimensions="<1920,1080>" sink_1::alpha=0.5 ! queue ! \ video/x-raw,format=NV12,width=1920,height=1080,interlace-mode=progressive,colorimetry=bt601 ! \ v4l2h264enc capture-io-mode=4 output-io-mode=5 ! h264parse ! queue ! mp4mux ! queue ! filesink location=/etc/media/video.mp4 \ split. ! queue ! qtimlvconverter ! queue ! qtimltflite delegate=external external-delegate-path=libQnnTFLiteDelegate.so \ external-delegate-options="QNNExternalDelegate,backend_type=htp;" model=/etc/models/deeplabv3_plus_mobilenet_quantized.tflite ! queue ! \ qtimlpostprocess module=deeplab-argmax labels=/etc/labels/deeplabv3_resnet50.json ! video/x-raw,width=256,height=144 ! queue ! mixer.Copy to clipboard To stop the use case, use CTRL + C. The following figure shows the flow of the use case execution: 1. Identify the scenes from a video stream coming through a camera source. 2. Compose the semantic segmentation and video stream using qtivcomposer. 3. Encode the stream as a H.264 bit stream and multiplex the stream in an MP4 container. Figure : Pipeline for segmentation and encode with qtivcomposer Qualcomm Open source camsrc tee qtimlvconverter qtivcomposer v4l2h264enc h264parse mp4mux filesink qtimltflite qtimlpostprocess The following table provides the sequential processing stages of the pipeline execution: | Process | Description | | --- | --- | | [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70022-50/topic/qtiqmmfsrc.html) |

  1. Collects the video stream (source) and creates two copies of the
    source:


| | **Preprocessing** | **Preprocessing** | | [qtimlvconverter](https://docs.qualcomm.com/doc/80-70022-50/topic/qtimlvconverter.html) |

  1. Receives the video stream on its sink pad.


  2. Performs preprocessing:


  3. Converts the video stream to a tensor stream on its source
    pad.

    The segmentation model uses this tensor stream for
    inferencing.




| | **Inferencing** | **Inferencing** | | [qtimltflite](https://docs.qualcomm.com/doc/80-70022-50/topic/qtimltflite.html) |

  1. Loads the segmentation model.


  2. Modifies the graph for the chosen delegate.


  3. Receives the tensor stream on its sinkpad.


  4. Runs the inference and produces a tensor stream with the
    segmentation results on its source pad.


| | **Postprocessing** | **Postprocessing** | | qtimlpostprocess |

  1. Receives the inference tensors on its sinkpad.


  2. Converts the inference tensors into video formats that the
    multimedia plugins can process later.


  3. Produces the semantic segmentations for the frame.


  4. Loads the corresponding modules for the segmentation
    models.

    In this use case, qtimlpostprocess does the
    following:


    1. Loads the deeplab-argmax submodule.


    2. Produces video frames with segmentation masks.


    3. Sends them to the sinkpad of qtivcomposer.






| | [qtivcomposer](https://docs.qualcomm.com/doc/80-70022-50/topic/qtivcomposer.html) |

  1. Receives the original video stream with segmentation mask on its
    sinkpads.


  2. Produces on its sourcepad GST buffers with contents composed of
    video streams from its sinkpads.


| | [v4l2h264enc](https://docs.qualcomm.com/doc/80-70022-50/topic/v4l2h264enc.html) |

  1. Applies parameters to each frame of the video stream it's
    receiving on its sinkpad.


  2. Encodes it into bit stream and sends it over its sourcepad.


| | h264parse | Adds more information about the bit stream to the GStreamer buffer
meta. | | mp4mux | Receives these buffers and creates the container format specification
buffers. | | **Output** | **Output** | | Filesink | Stores the resulting stream in a
/etc/media/video.mp4 file. | | Playback | Pull video.mp4 from the host computer and play
it on a media player:
`scp root@ device>:/etc/media/video.mp4 directory>` | **Parent Topic:** [LiteRT use cases](https://docs.qualcomm.com/doc/80-70022-50/topic/tensorflow-lite-use-cases.html) Last Published: Feb 20, 2026 [Previous Topic Image segmentation and display with LiteRT](https://docs.qualcomm.com/bundle/publicresource/80-70022-50/topics/single-camera-stream-with-image-segmentation-and-display.md) [Next Topic Pose estimation and display with LiteRT](https://docs.qualcomm.com/bundle/publicresource/80-70022-50/topics/single-camera-stream-with-pose-estimation-and-display.md)