# qtimlvclassification
Source: [https://docs.qualcomm.com/doc/80-70022-50/topic/qtimlvclassification.html](https://docs.qualcomm.com/doc/80-70022-50/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.
Note: This plugin is going to be deprecated.
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 and Qualcomm Neural Processing SDK use cases.
## Pad configuration
Table : Pad templates for qtimlvclassification
| Pad Name | Capabilities | Capabilities | Capabilities |
| --- | --- | --- | --- |
| SINK template: 'sink'