# qtimlvdetection

Source: [https://docs.qualcomm.com/doc/80-70014-50/topic/qtimlvdetection.html](https://docs.qualcomm.com/doc/80-70014-50/topic/qtimlvdetection.html)

The qtimlvdetection plugin processes output tensors of an Object Detection model from
        the ML inference plugin (such as qtimltflite, qtimlsnpe and qtimlqnn) into result of
        predictions.

Figure : GstBuffer workflow with qtimlvdetection
            
            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)

## Postprocessing

Figure : Postprocessing for object detection architecture
                
                ![](data:image/png;base64,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)

The negotiated [GstCaps](https://gstreamer.freedesktop.org/documentation/gstreamer/gstcaps.html) determines the processed output.
                The output can be either of the following:

- An image overlay mask (GstCaps: video/x-raw), which can be applied over the
                    original image using qtivcomposer.
    - The element uses the CPU-based [Cairo](https://www.cairographics.org) 2D graphics library to draw the prediction results in
                            ION/DMA buffers.
    - The GstImageBufferPool custom buffer pool class allocates the ION/DMA
                            buffers through IOCTL commands to the kernel.
- The GStreamer-formatted text (GstCaps: text/x-raw) containing the prediction
                    results. 
    The prediction results are parsed into GStreamer-formatted string
                        inside buffers allocated using regular system memory.

The module and labels properties of the plugin determine the method for the
                postprocessing operations.

- The module property specifies the postprocess module and is populated
                    dynamically at run time with the libraries available in
                        `/usr/lib/gstreamer-1.0/ml/modules/` containing the prefix
                        "`ml-vdetection`-".
- The labels property is a customized text file different for each machine
                    learning detection model that you must provide for the prediction labels.

Optional properties are available for adjusting the prediction results.

- Use results property to control the number of results displayed
- Use threshold property to set a confidence threshold for prediction. The results
                    with low confidence won't be displayed.

## Inheritance chain

[GObject](https://docs.gtk.org/gobject/) → [GstObject](https://gstreamer.freedesktop.org/documentation/gstreamer/gstobject.html?gi-language=c) → [GstElement](https://gstreamer.freedesktop.org/documentation/gstreamer/gstelement.html?gi-language=c) → [GstBaseTransform](https://gstreamer.freedesktop.org/documentation/base/gstbasetransform.html?gi-language=c) → GstMLVideoDetection

The following tables provide information on pad templates and element properties of
                qtimlvdetection. For use cases, see the detection use cases in [TensorFlow Lite use cases](https://docs.qualcomm.com/doc/80-70014-50/topic/tensorflow-lite-use-cases.html) and [Qualcomm Neural Processing SDK use cases](https://docs.qualcomm.com/doc/80-70014-50/topic/qualcomm-neural-processing-sdk-use-cases.html).

## Pad configuration

| Pad Name | Capabilities | Capabilities | Capabilities |
| --- | --- | --- | --- |
| SINK template: 'sink'<br><ul class="ul" id="qtimlvdetection__ul_zbh_g4z_q1c"><br>                                    <li class="li"><em class="ph i">Availability:</em> On request</li><br><br>                                    <li class="li"><em class="ph i">Direction:</em> sink</li><br><br>                                </ul> | neural-network/tensors | – | – |
| SRC template: 'src'<br><ul class="ul" id="qtimlvdetection__ul_u3p_g4z_q1c"><br>                                    <li class="li"><em class="ph i">Availability:</em> Always</li><br><br>                                    <li class="li"><em class="ph i">Direction:</em> source</li><br><br>                                </ul> | video/x-raw | format: | { (string)BGRA, (string)BGRx, (string)BGR16 } |
| SRC template: 'src'<br><ul class="ul" id="qtimlvdetection__ul_u3p_g4z_q1c"><br>                                    <li class="li"><em class="ph i">Availability:</em> Always</li><br><br>                                    <li class="li"><em class="ph i">Direction:</em> source</li><br><br>                                </ul> | video/x-raw(memory:GBM) | format: | { (string)BGRA, (string)BGRx, (string)BGR16 } |
| SRC template: 'src'<br><ul class="ul" id="qtimlvdetection__ul_u3p_g4z_q1c"><br>                                    <li class="li"><em class="ph i">Availability:</em> Always</li><br><br>                                    <li class="li"><em class="ph i">Direction:</em> source</li><br><br>                                </ul> | text/x-raw | format: | { (string)utf8 } |
|  |  |  |  |
|  |  |  |  |

## Element configuration

Table : Element properties for qtimlvdetection

| Property | Description |
| --- | --- |
| name | The name of the object<ul class="ul" id="qtimlvdetection__ul_mdx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">String. Default: "mlvideodetection0"</li><br><br>                                </ul> |
| parent | The parent of the object<ul class="ul" id="qtimlvdetection__ul_ndx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">Object of type "GstObject"</li><br><br>                                </ul> |
| qos | Handle Quality-of-Service events<ul class="ul" id="qtimlvdetection__ul_odx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">Boolean. Default: false</li><br><br>                                </ul> |
| module | Module name that is going to be used for processing the<br>                                    tensors<ul class="ul" id="qtimlvdetection__ul_pdx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">Enum "GstMLVideoDetectionModules" (0): none - No module,<br>                                        default invalid mode<ul class="ul" id="qtimlvdetection__ul_apg_1m4_myb"><br>                                            <li class="li">(1): face-detect - ml-vdetection-face-detect</li><br><br>                                            <li class="li">(2): ssd-mobilenet -<br>                                                ml-vdetection-ssd-MobileNet</li><br><br>                                            <li class="li">(3): YOLOv5m - ml-vdetection-yolov5m</li><br><br>                                            <li class="li">(4): YOLOv5s - ml-vdetection-yolov5s</li><br><br>                                        </ul><br></li><br><br>                                </ul> |
| labels | Labels file name<ul class="ul" id="qtimlvdetection__ul_qdx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">String. Default: null</li><br><br>                                </ul> |
| results | Number of results to display<ul class="ul" id="qtimlvdetection__ul_rdx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">Unsigned Integer. Range: 0 - 10 Default: 5</li><br><br>                                </ul> |
| threshold | Confidence threshold in %<ul class="ul" id="qtimlvdetection__ul_sdx_zl4_myb"><br>                                    <li class="li">flags: readable, writable</li><br><br>                                    <li class="li">Double Range: 10.0 - 100.0 Default: 10.0</li><br><br>                                </ul> |

**Parent Topic:** [Qualcomm GST plugins](https://docs.qualcomm.com/doc/80-70014-50/topic/qim-sdk-plugins.html)

Last Published: Oct 27, 2025

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