# Run Qualcomm IM SDK sample application using EVK

To run a sample application using a Qualcomm evaluation kit, ensure that the eSDK
is setup and that your environment meets the prerequisites.

The Qualcomm IM SDK contains sample applications that enable you to experience the
features of the Qualcomm evaluation kit. These applications serve as a reference for
custom use cases on the Qualcomm evaluation kit. For the list of default reference
applications, see [Qualcomm IM SDK sample applications](https://docs.qualcomm.com/bundle/publicresource/topics/80-70023-50/example-applications.html).

Prerequisites

The prerequisites for running the reference applications are as follows:

- A Qualcomm evaluation kit: Connected to a monitor through HDMI or DisplayPort
- An SSH connection with the Qualcomm evaluation kit; [establish an SSH connection](https://docs.qualcomm.com/bundle/publicresource/topics/80-70023-254/how_to.html#use-ssh)
with the device. Once connected, the
Qualcomm evaluation kit is accessible through its configured
IP address. The IP address is needed further to push models and
artifacts needed to run AI/ML applications.
- Model downloaded from AI Hub and the corresponding
[label files](https://github.com/quic/sample-apps-for-qualcomm-linux/tree/main/qualcomm-linux/artifacts/labels).
- Ensure that the device is powered on and the Wayland display is visible on the monitor.

Setup eSDK for development

The eSDK (extensible SDK) needs to be setup to develop
application/plugin code. See the [Qualcomm Intelligent Multimedia SDK Quick Start Guide](https://docs.qualcomm.com/bundle/publicresource/topics/80-70023-51/install-sdk.html)
for instructions on setting up the eSDK and downloading and compiling the source code.

- [Classify objects using a default model](https://docs.qualcomm.com/doc/80-80020-15B/topic/classify-objects-with-default-model.html)
The *gst-ai-classification* sample application demonstrates the
capability of hardware to perform classification on a video stream.

The pipeline receives the video stream from the camera, file source,
or real-time streaming protocol (RTSP), performs preprocessing,
conducts inference on AI hardware, and displays the results on the
screen.
- [Use a custom model with the sample app](https://docs.qualcomm.com/doc/80-80020-15B/topic/customize-reference-app.html)
It uses a custom-trained YoloV8 model as an example.

Last Published: Feb 27, 2026

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