# Hardware-accelerated sample applications for AI Qualcomm Linux provides sample AI/ML applications that show the AI capabilities of the Qualcomm Linux platform. The following image shows the workflow to run these AI sample apps, from booting the device, downloading the models, transferring the models to the device to running the sample apps on the target device. Page-1 Sheet.86 Sheet.80 Sheet.1 Boot Qualcomm Linux device Boot Qualcomm Linux device Sheet.2 Download models from GitHub or AI Hub Download models from GitHub or AI Hub Sheet.3 Copy models to Qualcomm Linux device Copy models to Qualcomm Linux device Sheet.16 Run sample apps Run sample apps Sheet.83 Sheet.84 Sheet.85 **Workflow for using the sample applications** The following AI sample applications are part of Qualcomm IM SDK. For the complete list of supported sample applications, see [Sample applications](https://docs.qualcomm.com/doc/80-70030-50/topic/example-applications.html) in the Qualcomm IM SDK documentation. ## AI processing for object detection The [gst-ai-object-detection](https://docs.qualcomm.com/doc/80-70030-50/topic/gst-ai-object-detection.html) application allows you to detect objects within images and videos. The use cases show the execution of [YOLOv5](https://github.com/ultralytics/yolov5), [YOLOv8](https://github.com/ultralytics/ultralytics), and [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX/blob/main/README.md) using the Qualcomm Neural Processing SDK runtime, YOLOv8 using Qualcomm AI Engine direct, and YOLOv5 and YOLOv8 using LiteRT. The following figure shows the pipeline, which receives the input from a live camera feed, file, or an RTSP stream, preprocesses it, runs inferences on AI hardware, and displays the results on the screen. For information about the plugins used in the pipeline flow, see [object detection pipeline flow](https://docs.qualcomm.com/doc/80-70030-50/topic/gst-ai-object-detection.html#gst-ai-object-detection__section_p2w_33y_kbc). rtspsrc rtph264 depay h264parse V4l2h264dec tee qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess qtivcomposer sink_1 sink_0 qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess sink_1 sink_0 filesrc qtdemux h264parse V4l2h264dec qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess sink_1 sink_0 qtiqmmfsrc qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess sink_1 sink_0 Qualcomm Open source v4l2src v4l2src_caps waylandsink filesink qtirtspbin ## AI processing for multistream-inference The [gst-ai-multistream-inference](https://docs.qualcomm.com/doc/80-70030-50/topic/multistream-inference.html) application shows AI inference (object detection and classification) on up to 32 input streams from camera, file, or RTSP stream. The following figure shows the pipeline, which receives several input streams, preprocesses them, runs AI inferences, combines the streams, and merges them all into a single video output. The maximum number of input streams supported on each SoC are follows: - QCS6490: 8 - Qualcomm Dragonwing IQ-8275: 16 - Qualcomm Dragonwing IQ-9075: 32 Note IQ-8275 is not supported on Ubuntu Server. The output is displayed on an HDMI display, saved as an H.264 encoded MP4 file, or converted to an RTSP stream. For information about the plugins used in this pipeline, see [multistream-inference pipeline flow](https://docs.qualcomm.com/doc/80-70030-50/topic/multistream-inference.html#multistream-inference__section_opk_tn2_ncc). Qualcomm Open source tee qtivcomposer Waylandsink rtspsrc rtph264 depay h264parse V4l2h264dec filesrc qtdemux h264parse V4l2h264dec udpsink qtiqmmfsrc qtimlvconverter qtimltflite qtimlpostprocess qtimlvconverter qtimltflite qtimlpostprocess qtimlvconverter qtimltflite qtimlpostprocess filesink Camera input streams File input streams ## Parallel AI inference The [gst-ai-parallel-inference](https://docs.qualcomm.com/doc/80-70030-50/topic/gst-ai-parallel-inference.html) application allows you to perform object detection, object classification, pose detection, and image segmentation on an input stream from different sources, such as camera, file, or an RTSP network. The use cases implement the LiteRT models for object detection, image segmentation, classification, and pose detection. Note This application isn’t supported on IQ-8275. The following figure shows the pipeline, which receives input streams from a camera, file, or an RTSP stream, performs the parallel inferencing for the four use cases, and displays the results side by side on the screen. For information about the plugins used in the pipeline flow, see [parallel inference pipeline flow](https://docs.qualcomm.com/doc/80-70030-50/topic/gst-ai-parallel-inference.html#gst-ai-parallel-inference__section_gcg_r3s_lbc). Qualcomm Open source tee qtivcomposer Waylandsink rtspsrc rtph264 depay h264parse V4l2h264dec filesrc qtdemux h264parse V4l2h264dec qtiqmmfsrc qtimlvconverter qtimltflite qtimlpostprocess sink_1 sink_0 qtimlvconverter qtimltflite qtimlpostprocess sink_3 sink_2 qtimlvconverter qtimltflite qtimlpostprocess sink_5 sink_4 qtimlvconverter qtimltflite qtimlpostprocess sink_7 sink_6 ## Daisychain of object detection and pose estimation The [gst-ai-daisychain-detection-pose](https://docs.qualcomm.com/doc/80-70030-50/topic/daisy-chain-detection-and-pose-detection.html) application allows you to perform cascaded object detection and pose detection with a camera, file source, or an RTSP stream. The use cases involve detecting objects and estimating the body poses of the subject in an image or a video. The following figure show the application workflow, which receives the source, postprocesses it, runs inferences on AI hardware, and displays the results on the screen. For information about the plugins used in the pipeline flow, see [daisychain detection and pose pipeline flow](https://docs.qualcomm.com/doc/80-70030-50/topic/daisy-chain-detection-and-pose-detection.html#daisy-chain-detection-and-pose-detection__section_pqq_1ny_kbc). Inferbin tee tee qtimlvconverter Source qtivsplit Inference Postprocess metamuxer Inferbin tee qtimlvconverter qtivcomposer qtioverlay Inference video/x-rawz video/x-raw Postprocess metamuxer Qualcomm Opensource waylandsink filesink qtirtspbin Last Published: Jun 19, 2026 [Previous Topic GStreamer ML plugin and AI SDK APIs](https://docs.qualcomm.com/bundle/publicresource/80-70030-15/topics/interfaces.md) [Next Topic Develop an AI application](https://docs.qualcomm.com/bundle/publicresource/80-70030-15/topics/developer-workflow.md)