# Run AI/ML sample applications

Use Qualcomm Linux AI/ML features with Qualcomm AI Runtime SDK (Qualcomm® Neural
        Processing SDK and Qualcomm AI Engine direct), and LiteRT (formerly TFLite)
        models.

- **[Download model and label files](https://docs.qualcomm.com/doc/80-70018-50/topic/download-model-and-label-files.html)**  

Download the model and label files for QCS6490, QCS9075, and QCS8275 to run the AI/ML         sample applications.
- **[Image classification](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-classification.html)**  

The **gst-ai-classification** application allows you to identify the subject in an         image. The use cases use the Qualcomm Neural Processing SDK, LiteRT, or Qualcomm AI Engine         direct models.
- **[Object detection](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-object-detection.html)**  

The **gst-ai-object-detection** 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 [YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) using the Qualcomm Neural Processing SDK runtime,         YOLOv8 using Qualcomm AI Engine direct, and YOLOv5 and YOLOv8 using LiteRT.
- **[Pose detection](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-pose-detection.html)**  

 The **gst-ai-pose-detection** application allows you to detect the body pose of         the subject in an image or video. The use cases use an input stream from a camera, file, or         an RTSP source, use LiteRT and Qualcomm AI Engine direct models for pose detection, and         display the results on the screen.
- **[Image segmentation](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-segmentation.html)**  

The **gst-ai-segmentation** application allows you to divide an image into         different and meaningful parts or segments and assign a label to each homogenous segment         based on the similarity of the attributes. Use Qualcomm Neural Processing SDK runtime,         Qualcomm AI Engine direct runtime, and LiteRT for image segmentation.
- **[Image segmentation using Python with container](https://docs.qualcomm.com/doc/80-70018-50/topic/image-segmentation-using-python.html)**  

The application allows you to perform image segmentation using the Qualcomm Neural         Processing SDK with Python bindings, all from within a docker container.
- **[Parallel inferencing](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-parallel-inference.html)**  

The **gst-ai-parallel-inference** application allows you to perform object         detection, object classification, pose detection, and image segmentation on an input stream         from different sources such as a camera, a file, or an RTSP network. The use cases use the         LiteRT models for object detection, image segmentation, classification, and pose         detection.
- **[Multi input/output object detection](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-multi-input-output-object-detection.html)**  

The **gst-ai-multi-input-output-object-detection** application allows you to         perform objection detection on video streams from various sources such as a camera, a file,         or over a network such as RTSP.
- **[Daisy chain detection and classification](https://docs.qualcomm.com/doc/80-70018-50/topic/daisy-chain-detection-and-classification.html)**  

The **gst-ai-daisychain-detection-classification** application allows you to         perform cascaded object detection and classification with a camera, file source, or RTSP         stream. The use case involves detecting objects and classifying the detected         objects.
- **[Daisy chain detection and pose estimation](https://docs.qualcomm.com/doc/80-70018-50/topic/daisy-chain-detection-and-pose-detection.html)**  

The **gst-ai-daisychain-detection-pose** 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.
- **[Monodepth from video](https://docs.qualcomm.com/doc/80-70018-50/topic/mono-depth-from-video.html)**  

The **gst-ai-monodepth** application allows you to infer depth of a source feed         from a live camera stream, file, or an RTSP stream.
- **[Video super-resolution](https://docs.qualcomm.com/doc/80-70018-50/topic/video-super-resolution.html)**  

The **gst-ai-superresolution** application allows you to generate high resolution         video frames from low-resolution input.
- **[Multistream inference](https://docs.qualcomm.com/doc/80-70018-50/topic/multistream-inference.html)**  

The **gst-ai-multistream-inference** application shows AI inference (object         detection and classification) on up to 32 input streams coming from camera, file, or RTSP         stream.
- **[Multistream batch inference](https://docs.qualcomm.com/doc/80-70018-50/topic/multistream-batch-inference.html)**  

The **gst-ai-multistream-batch-inference** application shows batched AI inference         (object detection and segmentation) on up to 24 input streams from video files.
- **[AI smart codec](https://docs.qualcomm.com/doc/80-70018-50/topic/ai-smart-codec.html)**  

The **gst-ai-smartcodec-example** application reduces network bandwidth and         storage resources for input from a camera or a file source.
- **[Face detection](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-face-detection.html)**  

The **gst-ai-face-detection** application collects the live video input from a         camera, file, or an RTSP stream and uses the Qualcomm AI Engine direct and LiteRT face         detection models to produce a preview with the overlaid AI model output on the HDMI         display.
- **[Face recognition](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-face-recognition.html)**  

The **gst-ai-face-recognition** application collects the live video input from a         camera or an RTSP stream and shares this input for face detection, facial landmarking and         face recognition. It uses the face\_det\_quantized models for face         detection, `facemap_3dmm_quantized` model for facial landmarking, and             `face_attrib_net_quantized` model for face recognition         labels.
- **[Audio classification](https://docs.qualcomm.com/doc/80-70018-50/topic/audio-classification.html)**  

The **gst-ai-audio-classification** application shows the audio classification         using the input from a file source and microphone. The classification results and video         preview are displayed.
- **[Metadata parsing](https://docs.qualcomm.com/doc/80-70018-50/topic/gst-ai-metadata-parser.html)**  

The **gst-ai-metadata-parser-example** application takes the live video stream         input from camera, file, or RTSP source, and passes the stream to the YOLO models for object         detection and preview. The overlaid AI model output with label and bounding boxes is         displayed on an HDMI display. The extracted metadata is logged in the console and used to         count the number of humans in the frame.
- **[AI USB camera](https://docs.qualcomm.com/doc/80-70018-50/topic/ai-usb-camera.html)**  

The **gst-ai-usb-camera-app** streams the video from a USB webcam connected to the         Qualcomm EVK. This webcam should be accessible as a /dev/videoX device.         Additionally, you can perform object detection and preview the results.

**Parent Topic:** [Sample applications](https://docs.qualcomm.com/doc/80-70018-50/topic/example-applications.html)

Last Published: Jan 30, 2026

[Previous Topic
Sample applications](https://docs.qualcomm.com/bundle/publicresource/80-70018-50/topics/example-applications.md) [Next Topic
Download model and label files](https://docs.qualcomm.com/bundle/publicresource/80-70018-50/topics/download-model-and-label-files.md)