# Python applications

Source: [https://docs.qualcomm.com/doc/80-70017-50/topic/python-sample-applications.html](https://docs.qualcomm.com/doc/80-70017-50/topic/python-sample-applications.html)

Qualcomm Linux integrates support for Python through the [gstreamer1.0-python](https://git.codelinaro.org/clo/le/meta-qti-gst/-/blob/imsdk.lnx.2.0.0.r2-rel/recipes-gst/packagegroups/packagegroup-qcom-gst.bb?ref_type=heads#L45) package.
        Qualcomm IM SDK supports Python bindings that allow you to create GStreamer-based
        applications in Python. The Python bindings for all the GST plugins are enabled through the
            `gst-python` utility.

Run the custom use cases using Python to use the multimedia and AI/ML features of
            Qualcomm Linux.
Note: As a reference, Python-based sample
                applications with Python bindings are provided in this guide.

## Prerequisites

- To create the directory on the device, run the following commands in a
                    shell:

        mount -o remount,rw /Copy to clipboard

        mkdir -p /opt/data/Copy to clipboard
- Ensure that the model and label files are available on the device. For
                    instructions, see [Download model, label and config JSON files for LiteRT and Qualcomm AI Engine direct](https://docs.qualcomm.com/doc/80-70017-50/topic/ai-ml-sample-applications.html#ai-ml-sample-applications__section_fsl_lgz_scc).
- Ensure that the model and label file are renamed according to the application in
                    use.
- Enable the
                    display:

        export XDG_RUNTIME_DIR=/dev/socket/weston && export WAYLAND_DISPLAY=wayland-1Copy to clipboard
- Push the files from the host machine to the target
                    device:

        scp <video.mp4> root@<IP address of target device>:/opt/data/Copy to clipboard

## Source information for Python applications

| Application | CodeLinaro Git - source path | Demonstrates | Supported SoC |
| --- | --- | --- | --- |
| [Camera encoding](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-encode.html) | [gst-camera-encode.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-camera-encode.py?ref_type=heads) | Encode a single camera stream and dump the output. | QCS6490 |
| [Multi-camera streaming using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/multi-camera-streaming-python-sample-app.html) | [gst-multi-camera-example](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-multi-camera-stream-example.py?ref_type=heads) | Stream from two camera sensors simultaneously. | QCS6490 |
| [Concurrent video playback (video wall) using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/video-wall-using-python.html) | [gst-concurrent-videoplay-composition.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-concurrent-videoplay-composition.py?ref_type=heads) | Supports concurrent video playback and renders them<br>                                on a screen. | QCS6490 |
| [Concurrent video playback (video wall) using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/video-wall-using-python.html) | [gst-concurrent-videoplay-composition.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-concurrent-videoplay-composition.py?ref_type=heads) | Supports concurrent video playback and renders them<br>                                on a screen. | QCS9075 |
| [Concurrent video playback (video wall) using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/video-wall-using-python.html) | [gst-concurrent-videoplay-composition.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-concurrent-videoplay-composition.py?ref_type=heads) | Supports concurrent video playback and renders them<br>                                on a screen. | QCS8275 |
| [Object detection and display](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-detection-display.html) | [gst-ai-object-detection.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-ai-object-detection.py) | Object detection on streams from a camera or a file source and<br>                                the output is either displayed or saved to a file. | QCS6490 |
| [Decode and object detection using RTSP stream](https://docs.qualcomm.com/doc/80-70017-50/topic/rts-decode-ai-detection-yolo-v8-overlay-display.html) | [gst-rtspsrc-detection-display.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-rtspsrc-detection-display.py) | Object detection and display with input from an RTSP<br>                                stream. | QCS6490 |
| [Object detection and classification](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-ai-detection-overlay-composer-display.html) | [gst-camera-two-stream-detection-and-classification-side-by-side.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-camera-two-stream-detection-and-classification-side-by-side.py?ref_type=heads) | Object detection and classification of objects in a scene<br>                                displayed by the AI overlay composer. | QCS6490 |
| [Transform and encode a camera stream](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-transform-downscale-and-rotate-encode.html) | [gst-camera-rotate-downscale-file.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-camera-rotate-downscale-file.py?ref_type=heads) | Rotate, downscale, and encode a camera stream. | QCS6490 |
| [Camera encode, object detection, and display](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-encode-file-detection-yolov8-overlay-display.html) | [gst-camera-two-stream-encode-file-detection-display.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-camera-two-stream-encode-file-detection-display.py?ref_type=heads) | Encode a camera stream and save it to a file. | QCS6490 |
| [Object detection, classification, and segmentation](https://docs.qualcomm.com/doc/80-70017-50/topic/object-detection-classification-and-segmentation-python-sample-app.html) | [gst-filesrc-2detection-classification-segmentation-side-by-side.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-filesrc-2detection-classification-segmentation-side-by-side.py?ref_type=heads) | Object detection from a scene in a camera stream, classification<br>                                on scenes from the video stream, and semantic segmentations for the<br>                                video. | QCS6490 |
| [Parallel inference using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/parallel-inference-using-python.html) | [gst-parallel-inference.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-parallel-inference.py?ref_type=heads) | Multiple AI/ML models run in parallel (object detection,<br>                                classification, segmentation, and pose detection) on streams from a<br>                                camera, file source, or RTSP. | QCS6490 |
| [Daisy chain detection and pose detection using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/daisy-chain-detection-and-pose-detection-using-python.html) | [gst-ai-daisychain-detection-pose.py](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-python-examples/gst-daisychain-detection-pose.py?ref_type=heads) | Perform cascaded object detection and pose detection with a<br>                                camera source, file source, or an RTSP stream. | QCS6490 |
|  |  |  |  |
|  |  |  |  |

## Supported inputs sources for sample applications

Table : Supported input sources

| SoC | Camera input | File input | RTSP input |
| :--- | :--- | :--- | :--- |
| QCS6490 | ✔ | ✔ | ✔ |
| QCS9075 | ❌ | ✔ | ✔ |
| QCS8275 | ❌ | ✔ | ✔ |

- **[Camera encoding](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-encode.html)**  

The **gst-camera-encode-example** application allows you to record and encode a         single camera stream.
- **[Concurrent video playback (video wall) using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/video-wall-using-python.html)**  

The **gst-concurrent-videoplay-composition.py** application supports concurrent         video playback for MP4 AVC (H.264) videos and performs composition on a video wall         display.
- **[Multi-camera streaming using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/multi-camera-streaming-python-sample-app.html)**  

The **gst-multi-camera-example.py** application enables you to stream from two         camera sensors simultaneously. The application composes the camera feeds side by side to         display on a screen or encodes and stores the video streams to files.
- **[Object detection and display](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-detection-display.html)**  

The **gst-ai-object-detection.py** application enables you to detect objects in         the camera stream or a file stream and display the results or save the output to a         file.
- **[Decode and object detection using RTSP stream](https://docs.qualcomm.com/doc/80-70017-50/topic/rts-decode-ai-detection-yolo-v8-overlay-display.html)**  

The **gst-rtspsrc-detection-display.py** script receives an RTSP stream as a         source, decodes it, uses [YOLOv8](https://github.com/ultralytics/ultralytics) LiteRT model to identify the object in a         scene from the camera stream and overlay the bounding boxes over the detected objects. The         results are shown on the display.
- **[Object detection and classification](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-ai-detection-overlay-composer-display.html)**  

The **gst-camera-two-stream-detection-and-classification-side-by-side.py**         application uses a YOLOv8 LiteRT model to detect and classify objects in the scene displayed         by the AI overlay composer.
- **[Transform and encode a camera stream](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-transform-downscale-and-rotate-encode.html)**  

The **gst-camera-rotate-downscale-file.py** application  rotates, downscales, and         encodes a camera stream. The transformed stream is then saved to a file.
- **[Camera encode, object detection, and display](https://docs.qualcomm.com/doc/80-70017-50/topic/camera-encode-file-detection-yolov8-overlay-display.html)**  

The **gst-camera-two-stream-encode-file-detection-display.py** application encodes         the camera stream and saves it to a file. The application uses a YOLOv8 LiteRT model to         identify the objects in a scene from a camera stream. The application overlays the bounding         boxes over the detected objects and displays the results.
- **[Object detection, classification, and segmentation](https://docs.qualcomm.com/doc/80-70017-50/topic/object-detection-classification-and-segmentation-python-sample-app.html)**  

The **gst-filesrc-2detection-classification-segmentation-side-by-side.py** script         identifies an object from a scene in a camera stream, overlays the bounding boxes over the         detected objects, classifies scenes from the video stream, and produces semantic         segmentations for the video. The output is displayed side by side on a screen.
- **[Parallel inference using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/parallel-inference-using-python.html)**  

The **gst-parallel-inference.py** application receives a video input from a         camera, file, or an RTSP stream and sends it to a four channel parallel processing by AI         models (classification, object detection, pose detection and segmentation). The output is         displayed as a preview with the overlaid AI models.
- **[Daisy chain detection and pose detection using Python](https://docs.qualcomm.com/doc/80-70017-50/topic/daisy-chain-detection-and-pose-detection-using-python.html)**  

The **gst-ai-daisychain-detection-pose.py** application enables you to perform         cascaded object detection and pose detection with input from a camera, file source, or an         RTSP stream.
- **[Customize a Python sample application](https://docs.qualcomm.com/doc/80-70017-50/topic/customize-a-python-sample-application.html)**  

You can develop custom sample applications using the instructions in this         procedure.

Last Published: Oct 01, 2026

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