# Image classification and encode with TFLite

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

The use cases use the InceptionV3 TFLite model to classify scenes from a single
        camera stream and either overlay or compose the classification labels, and then encode the
        stream.

## Variant 1: 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 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 ! v4l2h264enc capture-io-mode=5 output-io-mode=5 ! h264parse ! queue ! mp4mux ! queue ! filesink location=/opt/video.mp4 split. ! queue ! qtimlvconverter ! queue ! qtimltflite delegate=external external-delegate-path=libQnnTFLiteDelegate.so external-delegate-options="QNNExternalDelegate,backend_type=htp;" model=/opt/inceptionv3.tflite ! 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 overlay and encode
                
                ![](data:image/png;base64,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)

The figure shows the flow of the use case execution:

1. Identify the stream coming through a camera source.
2. Overlay the classification labels using overlaylib.
3. Encode the stream as a H.264 bitstream.
4. Multiplex the stream in an MP4 container and stored as an MP4 file.

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"><br>                                    <li class="li">The video stream is collected from a camera source plugin<br>                                        and two copies are created:<ul class="ul" id="single-camera-stream-with-image-classification-and-encode__ol_kh3_dyv_r1c"><br>                                            <li class="li">One stream is sent to the qtimetamux plugin to<br>                                                retain the video stream.</li><br><br>                                            <li class="li">The other stream is sent to a 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-encode__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-encode__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** |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimltflite.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-encode__ol_bwn_s5l_vbc"><br>                                    <li class="li">Loads the classification 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-encode__ol_gr1_w5l_vbc"><br>                                    <li class="li">Receives the inference tensors from a classification model<br>                                        on its 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-encode__ol_rrb_1xl_vbc"><br>                                            <li class="li">Loads the InceptionV3 submodule.</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-encode__ol_ll3_x5l_vbc"><br>                                    <li class="li">Receives the video stream and text stream with<br>                                        classification results corresponding to video stream on its<br>                                        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-encode__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> |
| [v4l2h264enc](https://docs.qualcomm.com/doc/80-70015-50/topic/v4l2h264enc.html) | <ol class="ol"><br>                                    <li class="li">Applies parameters to each frame of the video stream it is<br>                                        receiving on its sinkpad.</li><br><br>                                    <li class="li">Encodes it into bitstream and sends it over its<br>                                        sourcepad.</li><br><br>                                </ol> |
| h264parse | Adds additional information corresponding to the bitstream to<br>                                GStreamer buffer meta. |
| mp4mux | Receives these buffers and creates containers with format<br>                                specification buffers. |
| **Output** | **Output** |
| Filesink | Stores the resulting stream in a<br>                                    /opt/video.mp4 file. |
| Playback | Pull video.mp4 from the host machine and<br>                                play it on a media player:<br>`scp root@<IP address of<br>                                        target device>:/opt/ <destination<br>                                directory>` |

## Variant 2: Use qtivcomposer to mix original frame with classification
                mask

Run the use
                case:

    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 ! qtivcomposer name=mixer sink_1::position="<30, 30>" sink_1::dimensions="<320, 180>" ! queue ! video/x-raw\(memory:GBM\),format=NV12,width=1920,height=1080,interlace-mode=progressive,colorimetry=bt601 ! v4l2h264enc capture-io-mode=5 output-io-mode=5 ! h264parse ! queue ! mp4mux ! queue ! filesink location=/opt/video.mp4 split. ! queue ! qtimlvconverter ! queue ! qtimltflite delegate=external external-delegate-path=libQnnTFLiteDelegate.so external-delegate-options="QNNExternalDelegate,backend_type=htp;" model=/opt/inceptionv3.tflite ! queue ! qtimlvclassification threshold=40.0 results=2 module=mobilenet labels=/opt/classification.labels ! video/x-raw,format=BGRA,width=640,height=360 ! queue ! mixer.Copy to clipboard

To stop the use case, press CTRL + C.

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

The figure shows the flow of the use case execution:

1. Identify the stream coming through a camera source.
2. Compose the classification labels and video stream using qtivcomposer.
3. Encode the stream as an H.264 bitstream.
4. Multiplex the stream in an MP4 container and store it as an MP4 file.

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-encode__ol_l2f_zgm_vbc"><br>                                    <li class="li">Collects the video stream (source) from a camera and creates<br>                                        two copies of the source:<ul class="ul" id="single-camera-stream-with-image-classification-and-encode__ol_m2f_zgm_vbc"><br>                                            <li class="li">One stream is sent to the qtimetamux plugin to<br>                                                retain 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-encode__ol_t2f_zgm_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-encode__ul_u2f_zgm_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 an 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 the tensor stream<br>                                            for inferencing.</p><br></li><br><br>                                </ol> |
| **Inferencing** | **Inferencing** |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimltflite.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-encode__ol_v2f_zgm_vbc"><br>                                    <li class="li">Loads the classification 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 the 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-encode__ol_w2f_zgm_vbc"><br>                                    <li class="li">Receives the inference tensors from a classification model<br>                                        on its 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-encode__ol_x2f_zgm_vbc"><br>                                            <li class="li">Loads InceptionV3 submodule.</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-encode__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> |
| [v4l2h264enc](https://docs.qualcomm.com/doc/80-70015-50/topic/v4l2h264enc.html) | <ol class="ol" id="single-camera-stream-with-image-classification-and-encode__ol_aff_zgm_vbc"><br>                                    <li class="li">Applies parameters to each frame of the video stream it is<br>                                        receiving on its sinkpad.</li><br><br>                                    <li class="li">Encodes it into bitstream and sends it over its<br>                                        sourcepad.</li><br><br>                                </ol> |
| h264parse | Adds additional information corresponding to the bitstream to<br>                                GStreamer buffer meta. |
| mp4mux | Receives these buffers and creates containers with format<br>                                specification buffers. |
| **Output** | **Output** |
| Filesink | Stores the resulting stream in a<br>                                    /opt/video.mp4 file. |
| Playback | Pull video.mp4 from the host machine and<br>                                play it on a media player:<br>`scp root@<IP address of<br>                                        target device>:/opt/ <destination<br>                                directory>` |

**Parent Topic:** [TensorFlow Lite use cases](https://docs.qualcomm.com/doc/80-70015-50/topic/tensorflow-lite-use-cases.html)

Last Published: Oct 27, 2025

[Previous Topic
Image classification and display with TFLite](https://docs.qualcomm.com/bundle/publicresource/80-70015-50/topics/single-camera-stream-with-image-classification-and-display.md) [Next Topic
Object detection and display with TFLite](https://docs.qualcomm.com/bundle/publicresource/80-70015-50/topics/single-camera-stream-with-object-detection-and-display.md)