# Multi-input AI inferencing

Source: [https://docs.qualcomm.com/doc/80-70014-50/topic/gst-ai-multi-input-output-object-detection.html](https://docs.qualcomm.com/doc/80-70014-50/topic/gst-ai-multi-input-output-object-detection.html)

The **gst-ai-multi-input-output-object-detection** application enables you to
        perform object detection on multiple video streams from different sources such as a camera,
        a file, or over a network such as Real-Time Streaming Protocol (RTSP).

The figure shows the pipeline workflow, which captures video streams for inferencing from
            different sources such as camera, file, or RTSP. For information on the plugins used in
            the pipeline, see [Pipeline flow](https://docs.qualcomm.com/doc/80-70014-50/topic/gst-ai-multi-input-output-object-detection.html#gst-ai-multi-input-output-object-detection__section_qbz_bsq_nbc).

Figure : Multi-input AI inferencing pipeline
            
            ![](data:image/png;base64,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)

## Prerequisites

- Push the model and label files to the device to run the application. For more
                    information, see [Download the model and label files](https://docs.qualcomm.com/doc/80-70014-50/topic/ai-ml-sample-applications.html#ai-ml-sample-applications__prereq_v23_cxc_gbc).
- Enable SSH in Permissive mode to securely access your host device. For
                    instructions, see [How to SSH?](https://docs.qualcomm.com/bundle/publicresource/topics/80-70014-254/how_to.html#how-to-ssh-)
- Use the following command to enter the SSH shell and execute the use
                        cases:

        ssh root@<ip-addr of the target device>Copy to clipboard
- Run the following command to enable the Permissive
                    mode:

        setenforce 0Copy to clipboard
- Run the following command to enable the
                    display:

        export XDG_RUNTIME_DIR=/dev/socket/weston && export WAYLAND_DISPLAY=wayland-1Copy to clipboard
- Run the following command to push the files from host
                    machine:

        scp <filename> root@<IP address of target device>:/opt/Copy to clipboard

## Set up YOLOv5 environment

- Download the [YOLOv5](https://github.com/ultralytics/yolov5) model.

Running the yolov5.tflite model requires a Python environment.

Note: Modify the following commands according to the Python
                version in your host environment.

1. To create the Python 3.8 virtual environment, run the following
                    commands:

        sudo apt-get install python3.8Copy to clipboard

        python3.8 -m venv py3.8Copy to clipboard

        source py3.8/bin/activateCopy to clipboard
2. To generate the yolov5.tflite model, run the following
                        commands:

        git clone https://github.com/ultralytics/yolov5.gitCopy to clipboard

        cd yolov5Copy to clipboard

        python -m pip install -r requirements.txt tensorflow-cpuCopy to clipboard

        python export.py --weights yolov5m.pt --img 320 --include tflite --int8 --data data/coco128.yamlCopy to clipboard

    Enter
                        SSH shell and execute the following
                    command:

        scp yolov5m-int8.tflite root@<IP address of the device>:/opt/yolov5.tfliteCopy to clipboard

## Use cases

[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) and YOLOv5 models are trained on
                the same Common Objects in Context (COCO) dataset.

Enter SSH shell and run the following command to copy the YOLO-NAS label files to
                YOLOv5:

cp /opt/yolonas.labels /opt/yolov5.labelsCopy to clipboard

Note: The following commands provide the default model and label
                paths. If you have a different folder structure, replace the default paths in the
                command-line parameters.

- Run the AI object detection on streams from two
                    cameras:

        gst-ai-multi-input-output-object-detection --num-camera=2 --display --model=/opt/yolov5.tflite --labels=/opt/yolov5.labelsCopy to clipboard
- Run AI object detection on streams from a file
                    source:

        gst-ai-multi-input-output-object-detection --num-file=2 --display --model=/opt/yolov5.tflite --labels=/opt/yolov5.labelsCopy to clipboard

The
                    default source path for the video files is /opt/video1.mp4
                    and /opt/video2.mp4.
- Run AI object detection on streams from an RTSP
                        source:

        gst-ai-multi-input-output-object-detection --num-rtsp=2 --display --model=/opt/yolov5.tflite --labels=/opt/yolov5.labelsCopy to clipboard

    The
                        default ip:port for the RTSP source is 127.0.0.1:8554.
- Take the input source video stream from a file and display the output as
                        follows:
    - Display the output on a screen.
    - Save the output on a file.
    - Send the output over network through RTSP streaming.

Before executing this use case, use the following command to run the
                        RTSP server in a separate console on
                        target:

        gst-rtsp-server -p 8900 -a "<IP address of device>"  -m /live "( udpsrc name=pay0 port=<port_num> caps=\
        \"application/x-rtp,media=video,clock-rate=90000,\
        encoding-name=H264,payload=96\" )"Copy to clipboard

    Run the following
                        command to execute the use
                        cases:

        gst-ai-multi-input-output-object-detection --num-file=4 -d -f /opt/app.mp4 --out-rtsp --model=/opt/yolov5.tflite --labels=/opt/yolov5.labels -i <ip_address> -p <port_num>Copy to clipboard

    To
                        view the RTSP stream on the host PC, do the following:

    - Install VLC Media Player on the host machine and set the environment
                            variables.
    - On the Linux host, do one of the following to see the RTSP
                            stream:

            vlc -vvv rtsp://<ip_address>:8900/liveCopy to clipboard

            ffplay -rtsp_transport tcp rtsp://<ip_address>:8900/liveCopy to clipboard
    - On the Windows host, do the following:
        1. Open the VLC media player.
        2. Select Media<abbr title="and then"> &gt; </abbr>Open Network Stream or press CTRL +
                                        N).
        3. Enter `rtsp://<ip_address>:8900/live`.
        4. Click Play.

Note: Ensure that the total number of input streams
                        from camera, RTSP, and file source does not exceed 6.

- To stop the use case, press CTRL +
                    C.
- To display the available help options, run the following commands in SSH
                    shell:

        gst-ai-multi-input-output-object-detection -hCopy to clipboard

## Expected output

The processed results are displayed on an HDMI screen, saved as H.264 encoded MP4
                file, or streamed over the RTSP server.

Figure : Expected output for gst-ai-multi-input-output-object-detection
                    application
                
                ![](data:image/png;base64,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)

## Pipeline flow

The table lists the plugins used to execute the multi input/output inference
                    use cases:| Plugin | Description |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70014-50/topic/qtiqmmfsrc.html) | Captures the camera live stream and employs the tee to split the<br>                                stream for inferencing. |
| Sources | <ul class="ul" id="gst-ai-multi-input-output-object-detection__ul_z1z_x4f_w1c"><br>                                    <li class="li">The pipeline does the following for a file source:<ul class="ul" id="gst-ai-multi-input-output-object-detection__ul_qzm_1r4_tbc"><br>                                            <li class="li">Captures the video stream using filesrc.</li><br><br>                                            <li class="li">Demultiplexes using qtdemux.</li><br><br>                                            <li class="li">Parses the stream data using h264parse.</li><br><br>                                            <li class="li">Decodes the data using <a href="https://docs.qualcomm.com/doc/80-70014-50/topic/v4l2h264dec.html">v4l2h264dec</a>.</li><br><br>                                            <li class="li">Uses tee to split the stream for inferencing.</li><br><br>                                        </ul><br></li><br><br>                                    <li class="li">The pipeline does the following for a RTSP source:<ul class="ul" id="gst-ai-multi-input-output-object-detection__ul_vsj_2r4_tbc"><br>                                            <li class="li">Captures the RTSP stream using rtspsrc followed by<br>                                                rtph264depay, h264parse, and <a href="https://docs.qualcomm.com/doc/80-70014-50/topic/v4l2h264dec.html">v4l2h264dec</a>. </li><br><br>                                            <li class="li">Uses tee to split the stream for inferencing.</li><br><br>                                        </ul><br></li><br><br>                                </ul> |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70014-50/topic/qtimlvconverter.html) | <ol class="ol" id="gst-ai-multi-input-output-object-detection__ol_kgt_hnq_nbc"><br>                                    <li class="li">Receives the video stream on its sink pad.</li><br><br>                                    <li class="li">Performs the following preprocessing on the stream data.<br>                                        This is done when the model expects floating-point values as<br>                                            input.<ol class="ol" type="a" id="gst-ai-multi-input-output-object-detection__ol_drd_jnq_nbc"><br>                                            <li class="li">Color conversion</li><br><br>                                            <li class="li">Scaling (up or down)</li><br><br>                                            <li class="li">Normalization</li><br><br>                                        </ol><br></li><br><br>                                </ol><br><br>                                <br>The tensor stream is used for inferencing in the later stages of<br>                                    the pipeline. |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70014-50/topic/qtimltflite.html) | Runs on the TFLite runtime and uses the yolov5.tflite model for<br>                                    object detection.<br><ol class="ol" id="gst-ai-multi-input-output-object-detection__ol_l2x_zjq_nbc"><br>                                    <li class="li">After the inference runtime receives the tensor stream on<br>                                        its sink pad, it executes the inference.</li><br><br>                                    <li class="li">Produces a tensor stream with the inference results on its<br>                                        source pad.</li><br><br>                                </ol> |
| [qtimlvdetection](https://docs.qualcomm.com/doc/80-70014-50/topic/qtimlvdetection.html) | Converts the inference tensors that it receives on its sink pad<br>                                into video formats that the multimedia plugins can process<br>                                later. |
| [qtivcomposer](https://docs.qualcomm.com/doc/80-70014-50/topic/qtivcomposer.html) | <ol class="ol" id="gst-ai-multi-input-output-object-detection__ol_dmb_2vr_lbc"><br>                                    <li class="li">Composes frames with contents from its sink pads</li><br><br>                                    <li class="li">Pushes the GStreamer buffers containing these composed<br>                                        frames to its source pad.</li><br><br>                                </ol> |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70014-50/topic/waylandsink.html) | <ol class="ol" id="gst-ai-multi-input-output-object-detection__ol_kjr_fvr_lbc"><br>                                    <li class="li">Waylandsink submits the video stream received on its sink<br>                                        pad to Wayland compositor.</li><br><br>                                    <li class="li">Renders the video stream on a local display.</li><br><br>                                </ol> |
| Filesink | Takes the video stream that it receives on its sink pad  saves it<br>                                as an H.264-encoded MP4 file. |
| udpsink | <ol class="ol" id="gst-ai-multi-input-output-object-detection__ul_skp_cds_nbc"><br>                                    <li class="li">Serves as a network sink.</li><br><br>                                    <li class="li">Transmits UDP packets to the network.</li><br><br>                                </ol> |

Use the following command to pull the files from host
                machine:

    scp root@<IP address of target device>:/opt/ <destination directory>Copy to clipboard

**Known issue**

This application encounters an issue when using input from multiple sources such as
                camera, file, and RTSP. As a workaround, the application restricts itself to using
                only one input source at a time.

**Parent Topic:** [AI/ML sample applications](https://docs.qualcomm.com/doc/80-70014-50/topic/ai-ml-sample-applications.html)

Last Published: Oct 27, 2025

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