# qtimlvclassification Source: [https://docs.qualcomm.com/doc/80-70020-50/topic/qtimlvclassification.html](https://docs.qualcomm.com/doc/80-70020-50/topic/qtimlvclassification.html) The qtimlvclassification plugin processes output tensors of an image classification model from the ML inference plugin (such as qtimltflite, qtimlsnpe, and qtimlqnn) into a result of predictions. The negotiated [GstCaps](https://gstreamer.freedesktop.org/documentation/gstreamer/gstcaps.html) determines the processed output on the plug-in output. It can be either of the following: - An image mask (GstCaps: video/x-raw), which is applied over the original image using qtivcomposer. - A GStreamer formatted text (GstCaps: text/x-raw) containing the prediction results. The qtimlvclassification plugin uses the CPU-based [Cairo](https://www.cairographics.org) 2D graphics library for image overlay mask. The image overlay mask allows it 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. In the versatile text format, the prediction results are parsed into GStreamer-formatted string inside the buffers allocated using the regular system memory. The module and labels properties of the plugin determine the method used for postprocessing operations. - The module property specifies the postprocessing module, which runs dynamically at runtime with the available libraries at `in /usr/lib/gstreamer-1.0/ml/modules/` containing the prefix `ml-aclassification-` - 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 the `results` property to control the number of results that are displayed - Use the `threshold` property to set a confidence threshold for prediction. The results with low confidence aren't displayed. Figure : Postprocessing for object detection architecture Figure : qtimlvclassification in pipeline ## 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) → GstMLVideoClassification The following tables provide information on pad templates and element properties of qtimlsnpe. For use cases, see the classification use cases in [LiteRT use cases](https://docs.qualcomm.com/doc/80-70020-50/topic/tensorflow-lite-use-cases.html) and [Qualcomm Neural Processing SDK use cases](https://docs.qualcomm.com/doc/80-70020-50/topic/qualcomm-neural-processing-sdk-use-cases.html). ## Pad configuration | Pad Name | Capabilities | Capabilities | Capabilities | | --- | --- | --- | --- | | SINK template: 'sink'



*Availability:* On request



*Direction:* sink | neural-network/tensors | – | – | | SRC template: 'src'



*Availability:* Always



*Direction:* source | video/x-raw | format: | { (string)BGRA, (string)BGRx, (string)BGR16 } | | SRC template: 'src'



*Availability:* Always



*Direction:* source | video/x-raw | format: | { (string)BGRA, (string)BGRx, (string)BGR16 } | | SRC template: 'src'



*Availability:* Always



*Direction:* source | text/x-raw | format: | { (string)utf8 } | | | | | | | | | | | ## Element configuration Table : Element properties of qtimlvclassification | Property | Description | | --- | --- | | name | The name of the object. | | parent | The parent of the object. | | qos | Handle the quality-of-service events. | | module | Module name that's used for processing the tensors.
| | labels | The filename of the labels. | | results | Number of results for display. | | threshold | Confidence threshold in %. | **Parent Topic:** [Configure ML plugins](https://docs.qualcomm.com/doc/80-70020-50/topic/inferencing-plugins.html) Last Published: Jan 30, 2026 [Previous Topic qtimlqnn](https://docs.qualcomm.com/bundle/publicresource/80-70020-50/topics/qtimlqnn.md) [Next Topic qtimlaclassification](https://docs.qualcomm.com/bundle/publicresource/80-70020-50/topics/qtimlaclassification.md)