# Image segmentation and display with LiteRT

Source: [https://docs.qualcomm.com/doc/80-70018-50/topic/single-camera-stream-with-image-segmentation-and-display.html](https://docs.qualcomm.com/doc/80-70018-50/topic/single-camera-stream-with-image-segmentation-and-display.html)

The use case uses the `deeplabv3_resnet50` LiteRT model to identify
        semantic segmentations in a scene from a camera stream. The use case is to compose the
        semantics and original video stream using qtivcomposer, and then display the
        results.

Run the use
            case:

    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::alpha=0.5 ! queue ! waylandsink fullscreen=true sync=false \
    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 ! \
    qtimlvsegmentation module=deeplab-argmax labels=/etc/labels/deeplabv3_resnet50.labels constants="deeplab,q-offsets=<0.0>,q-scales=<1.0>;" ! \
    video/x-raw,width=256,height=144 ! queue ! mixer.Copy to clipboard

To stop the use case,  use CTRL + C.

Figure : Pipeline for segmentation with qtivcomposer
            
            ![](data:image/png;base64,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)

The figure shows the flow of the use case execution:

1. Identify scenes from a video stream coming through a camera source.
2. Compose semantic segmentation and video stream using qtivcomposer.
3. Display the results.

The table provides the sequential processing stages of the pipeline execution:

| Process | Description |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70018-50/topic/qtiqmmfsrc.html) | <ol class="ol" id="single-camera-stream-with-image-segmentation-and-display__ol_f5k_g5n_vbc"><br>                                <li class="li">Collects the video stream (source) and creates two copies of the<br>                                        source:<ul class="ul" id="single-camera-stream-with-image-segmentation-and-display__ul_n44_nwl_vbc"><br>                                        <li class="li">One stream is sent to the qtivcomposer plugin to retain<br>                                            the video stream.</li><br><br>                                        <li class="li">The other stream is sent to the ML inferencing branch in<br>                                            the pipeline.</li><br><br>                                    </ul><br></li><br><br>                            </ol> |
| **Preprocessing** | **Preprocessing** |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70018-50/topic/qtimlvconverter.html) | <ol class="ol" id="single-camera-stream-with-image-segmentation-and-display__ol_xsf_q5l_vbc"><br>                                <li class="li">Receives the video stream on its sink pad.</li><br><br>                                <li class="li">Performs preprocessing:<ul class="ul" id="single-camera-stream-with-image-segmentation-and-display__ul_ff2_twl_vbc"><br>                                        <li class="li">Color conversion</li><br><br>                                        <li class="li">Scaling down/up</li><br><br>                                        <li class="li">Normalization on the stream data when the model expects<br>                                            the floating point values as input</li><br><br>                                    </ul><br></li><br><br>                                <li class="li">Converts the video stream to a tensor stream on its source<br>                                        pad.<p class="p">The segmentation model uses this tensor stream for<br>                                        inferencing.</p><br></li><br><br>                            </ol> |
| **Inferencing** | **Inferencing** |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70018-50/topic/qtimltflite.html) | <ol class="ol" id="single-camera-stream-with-image-segmentation-and-display__ol_lfr_35n_vbc"><br>                                <li class="li">Loads the segmentation model.</li><br><br>                                <li class="li">Modifies the graph for the chosen delegate.</li><br><br>                                <li class="li">Receives the tensor stream on its sinkpad.</li><br><br>                                <li class="li">Runs the inference and produces a tensor stream with the<br>                                    segmentation results on its source pad.</li><br><br>                            </ol> |
| **Postprocessing** | **Postprocessing** |
| [qtimlvsegmentation](https://docs.qualcomm.com/doc/80-70018-50/topic/qtimlvsegmentation.html) | <ol class="ol" id="single-camera-stream-with-image-segmentation-and-display__ol_mtr_k5n_vbc"><br>                                <li class="li">Receives the inference tensors on its sinkpad.</li><br><br>                                <li class="li">Converts the inference tensors into video formats that the<br>                                    multimedia plugins can process later.</li><br><br>                                <li class="li">Produces the semantic segmentations for the frame.</li><br><br>                                <li class="li">Loads the corresponding modules for the segmentation<br>                                        models.<p class="p">In this use case, qtimlvsegmentation does the<br>                                        following: </p><ol class="ol" type="a" id="single-camera-stream-with-image-segmentation-and-display__ol_ntr_k5n_vbc"><br>                                        <li class="li">Loads the deeplab-argmax submodule.</li><br><br>                                        <li class="li">Produces video frames with segmentation masks.</li><br><br>                                        <li class="li">Sends them to the sinkpad of qtivcomposer.</li><br><br>                                    </ol><br><br>                                </li><br><br>                            </ol> |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70018-50/topic/qtivcomposer.html) | <ol class="ol" id="single-camera-stream-with-image-segmentation-and-display__ol_nmc_lxl_vbc"><br>                                <li class="li">Receives the original video stream with segmentation mask on its<br>                                    sinkpads. </li><br><br>                                <li class="li">On its sourcepad, produces  GST buffers with contents composed<br>                                    of video streams from its sinkpads.</li><br><br>                            </ol> |
| **Output** | **Output** |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70018-50/topic/waylandsink.html) | <ol class="ol" id="single-camera-stream-with-image-segmentation-and-display__ol_qqc_c5n_vbc"><br>                                <li class="li">Receives the video stream on its sinkpad.</li><br><br>                                <li class="li">Submits the video stream to Weston. </li><br><br>                                <li class="li">Weston displays the following on the local display device:<ul class="ul" id="single-camera-stream-with-image-segmentation-and-display__ol_cjl_r5n_vbc"><br>                                        <li class="li">The video stream that's captured from the camera. </li><br><br>                                        <li class="li">The segmentation masks that are drawn over<br>                                            objects/components in that scene.</li><br><br>                                    </ul><br></li><br><br>                            </ol> |

**Parent Topic:** [LiteRT use cases](https://docs.qualcomm.com/doc/80-70018-50/topic/tensorflow-lite-use-cases.html)

Last Published: Jan 30, 2026

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