# qtimlvsegmentation Source: [https://docs.qualcomm.com/doc/80-70020-50/topic/qtimlvsegmentation.html](https://docs.qualcomm.com/doc/80-70020-50/topic/qtimlvsegmentation.html) The qtimlvsegmentation plugin processes output tensors of an image segmentation/depth estimation model from the ML inference plugin (such as qtimltflite, qtimlsnpe, and qtimlqnn) into result of predictions. The processed output is an image mask (GstCaps: video/x-raw). [GstCaps](https://gstreamer.freedesktop.org/documentation/gstreamer/gstcaps.html) determines the dimensions and format, which is applied over the original image using qtivcomposer. For this mask, 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 module and labels properties of the plugin determine the method for the postprocessing operations. - The module property specifies the postprocessing module. It's populated dynamically at runtime with the libraries available in `/usr/lib/gstreamer-1.0/ml/modules/` containing the prefix "`ml-vsegmentation-`-". - The labels property is a customized text file different for each machine learning detection model that you must provide for the prediction labels. Figure : GstBuffer workflow with qtimlvsegmentation ## 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) → GstMLVideoSegmentation The following tables provide information on pad templates and element properties of qtimlvsegmentation. For use cases, see the segmentation 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'
| neural-network/tensors | – | – | | SRC template: 'src'
| video/x-raw | format: | { (string)BGRA, (string)BGRx, (string)BGR16 } | | SRC template: 'src'
| text/x-raw | format: | { (string)utf8 } | | | | | | ## Element configuration Table : Element properties for qtimlvsegmentation | Property | Description | | --- | --- | | name | The name of the object. | | parent | The parent of the object. | | qos | Handle Quality-of-Service events. | | module | Module name that's used for processing the tensors. | | labels | The filename of the labels. | **Parent Topic:** [Configure ML plugins](https://docs.qualcomm.com/doc/80-70020-50/topic/inferencing-plugins.html) Last Published: Jan 30, 2026 [Previous Topic qtimlvdetection](https://docs.qualcomm.com/bundle/publicresource/80-70020-50/topics/qtimlvdetection.md) [Next Topic qtimlvpose](https://docs.qualcomm.com/bundle/publicresource/80-70020-50/topics/qtimlvpose.md)