# Image classification and display with Neural Processing SDK 

Source: [https://docs.qualcomm.com/doc/80-70015-50/topic/single-camera-stream-with-image-classification-and-display-with-mobilenet-v1.html](https://docs.qualcomm.com/doc/80-70015-50/topic/single-camera-stream-with-image-classification-and-display-with-mobilenet-v1.html)

The use cases use an Inceptionv3 model with Qualcomm Neural Processing SDK to
        classify scenes, either overlay or compose the classification labels, and then display the
        results.

You can use any publicly available classification model with TensorFlow and convert it to
            the `.dlc` format as described in [TensorFlow Model Conversion](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-2/model_conv_tensorflow.html).

## Use qtioverlay plugin to apply classification overlay

Run the use
                case:

    setprop persist.overlay.use_c2d_blit 2Copy to clipboard

    gst-launch-1.0 -e --gst-debug=2 \
    qtiqmmfsrc name=camsrc ! video/x-raw\(memory:GBM\),format=NV12,width=1280,height=720,framerate=30/1,compression=ubwc ! queue ! tee name=split \
    split. ! queue ! qtimetamux name=metamux ! queue ! qtioverlay ! queue ! waylandsink fullscreen=true sync=false \
    split. ! queue ! qtimlvconverter ! queue ! qtimlsnpe delegate=dsp <mobilenet based DLC model> ! queue ! qtimlvclassification threshold=40.0 results=2 module=mobilenet labels=<label file> ! text/x-raw ! queue ! metamux.Copy to clipboard

To stop the use case, press CTRL + C.

Figure : Pipeline for classification overlay
                
                ![](data:image/png;base64,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)

The figure shows the flow of the use case execution:

- Classify scenes from a video stream coming through a camera source.
- Overlay classification labels using overlaylib.
- Display the results on a local display.

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

| Process | Description |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70015-50/topic/qtiqmmfsrc.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_l2f_zgm_vbc"><br>                                    <li class="li">Collects the video stream (source) and creates two copies of<br>                                        the source:<ul class="ul" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_m2f_zgm_vbc"><br>                                            <li class="li">One stream is sent to qtimetamux plugin to retain<br>                                                the video stream.</li><br><br>                                            <li class="li">The other stream is sent to an ML inferencing<br>                                                pipeline.</li><br><br>                                        </ul><br></li><br><br>                                </ol> |
| **Preprocessing** | **Preprocessing** |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlvconverter.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__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-classification-and-display-with-mobilenet-v1__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<br>                                                expects 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 classification model uses this tensor stream<br>                                            for inferencing.</p><br></li><br><br>                                </ol> |
| **Inferencing** | **Inferencing** |
| [qtimlsnpe](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlsnpe.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_bwn_s5l_vbc"><br>                                    <li class="li">Loads the 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>                                        inference results on its source pad.</li><br><br>                                </ol> |
| **Postprocessing** | **Postprocessing** |
| [qtimlvclassification](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlvclassification.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_gr1_w5l_vbc"><br>                                    <li class="li">Receives the inference tensors from the model on its<br>                                        sinkpad.</li><br><br>                                    <li class="li">Converts the tensors into formats such as video or text that<br>                                        the multimedia plugins can process later.</li><br><br>                                    <li class="li">Applies the threshold to the chosen number of results.</li><br><br>                                    <li class="li">Loads the corresponding modules of the classification<br>                                        models. <p class="p">In this use case, qtimlvclassification does the<br>                                            following:</p><ol class="ol" type="a" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_rrb_1xl_vbc"><br>                                            <li class="li">Loads the submodule of the model.</li><br><br>                                            <li class="li">Produces results as structures of text.</li><br><br>                                            <li class="li">Sends them to the sinkpad of qtimetamux.</li><br><br>                                        </ol><br></li><br><br>                                </ol> |
| [qtimetamux](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimetamux.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_ll3_x5l_vbc"><br>                                    <li class="li">Receives the video stream and text stream with<br>                                        classification results corresponding to the video stream on<br>                                        its sinkpads.</li><br><br>                                    <li class="li">Produces GST buffers with the contents of video stream on<br>                                        its sink pad.</li><br><br>                                    <li class="li">Adds classification result from data sinkpad to GST buffer<br>                                        meta (meta muxing) on its source pad.</li><br><br>                                </ol> |
| [qtioverlay](https://docs.qualcomm.com/doc/80-70015-50/topic/qtioverlay.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_wst_y5l_vbc"><br>                                    <li class="li">Receives the multiplexed stream.</li><br><br>                                    <li class="li">Overlays the classification labels on the VideoFrame using<br>                                        CL. </li><br><br>                                    <li class="li">Produces GST buffers with overlays in its source pad.</li><br><br>                                </ol> |
| **Output** | **Output** |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70015-50/topic/waylandsink.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_fd3_wc5_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 renders the video stream and possible classifications<br>                                        generated for that scene on a local display device.</li><br><br>                                </ol> |

## Use qtivcomposer to mix original frame with classification mask

Run the use case:

    setprop persist.overlay.use_c2d_blit 2Copy to clipboard

    gst-launch-1.0 -e \
    qtiqmmfsrc name=camsrc ! video/x-raw\(memory:GBM\),format=NV12,width=1280,height=720,framerate=30/1,compression=ubwc ! queue ! tee name=split \
    split. ! queue ! qtimetamux name=metamux ! queue ! qtioverlay ! queue ! waylandsink fullscreen=true sync=false \
    split. ! queue ! qtimlvconverter ! queue ! qtimlsnpe delegate=dsp model=/opt/inceptionv3.dlc ! queue ! qtimlvclassification threshold=40.0 results=2 module=mobilenet labels=/opt/classification.labels ! text/x-raw ! queue ! metamux.Copy to clipboard

To stop the use case, press CTRL + C.

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

The figure shows the flow of the use case execution:
- Classify scenes from a video stream coming through a camera source.
- Compose classification labels and video stream together using
                        qtivcomposer.
- Display the results to a local display.

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

| Process | Description |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70015-50/topic/qtiqmmfsrc.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_x5l_jd5_vbc"><br>                                    <li class="li">Collects the video stream (source) and creates two copies of<br>                                        the source:<ul class="ul" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ul_n44_nwl_vbc"><br>                                            <li class="li">One stream is sent to the qtivcomposer plugin to<br>                                                retain the video stream.</li><br><br>                                            <li class="li">The other stream is sent to the ML inferencing<br>                                                branch in the pipeline.</li><br><br>                                        </ul><br></li><br><br>                                </ol> |
| **Preprocessing** | **Preprocessing** |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlvconverter.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_i5w_4wl_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-classification-and-display-with-mobilenet-v1__ol_zdw_qwl_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 a model<br>                                                expects 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 classification model uses this tensor stream<br>                                            for inferencing.</p><br></li><br><br>                                </ol> |
| **Inferencing** | **Inferencing** |
| [qtimlsnpe](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlsnpe.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_u1l_cxl_vbc"><br>                                    <li class="li">Loads the 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>                                        inference results on its source pad.</li><br><br>                                </ol> |
| **Postprocessing** | **Postprocessing** |
| [qtimlvclassification](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlvclassification.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_o3v_2xl_vbc"><br>                                    <li class="li">Receives the inference results from the model on its<br>                                        sinkpad. </li><br><br>                                    <li class="li">Converts the inference tensors into formats like video or<br>                                        text that the multimedia plugins can process later.</li><br><br>                                    <li class="li">Applies the threshold to the chosen number of results. </li><br><br>                                    <li class="li">Loads the corresponding modules for the classification<br>                                        models. <p class="p">In this use case, qtimlvclassification does the<br>                                            following: </p><ol class="ol" type="a" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_p3v_2xl_vbc"><br>                                            <li class="li">Loads the submodule of the model.</li><br><br>                                            <li class="li">Produces results as video frames with classification<br>                                                labels.</li><br><br>                                            <li class="li">Sends them to the sinkpad of qtivcomposer.</li><br><br>                                        </ol><br></li><br><br>                                </ol> |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70015-50/topic/qtivcomposer.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_nmc_lxl_vbc"><br>                                    <li class="li">Receives the original video stream with classification<br>                                        results on its sinkpads. </li><br><br>                                    <li class="li">On its sourcepad, produces GST buffers with contents<br>                                        composed of video streams from its sinkpads.</li><br><br>                                </ol> |
| **Output** | **Output** |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70015-50/topic/waylandsink.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-display-with-mobilenet-v1__ol_cgt_mwl_vbc"><br>                                    <li class="li">Receives the video in its sinkpad</li><br><br>                                    <li class="li">Submits the video stream to Weston. </li><br><br>                                    <li class="li">Weston renders the video stream and possible classifications<br>                                        generated for that scene on a local display device.</li><br><br>                                </ol> |

**Parent Topic:** [Qualcomm Neural Processing SDK use cases](https://docs.qualcomm.com/doc/80-70015-50/topic/qualcomm-neural-processing-sdk-use-cases.html)

Last Published: Oct 27, 2025

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