Skip to main content
Please refer GStreamer Plugin Documentation for standard GStreamer plugins.

Welcome

The QIM SDK extends the powerful GStreamer multimedia framework by introducing a comprehensive suite of plugins tailored for building end-to-end AI, video, and streaming pipelines. Designed to work seamlessly alongside existing open-source GStreamer components, these plugins enable developers to rapidly prototype, deploy, and scale real-world applications without sacrificing flexibility or performance. With the increasing demand for intelligent multimedia applications—such as smart surveillance, video analytics, and edge AI—the QIM SDK provides optimized building blocks that simplify pipeline development while ensuring efficient execution. Developers can combine standard GStreamer elements with QIM-specific plugins to construct modular pipelines that handle everything from data ingestion and preprocessing to inference, post-processing, and streaming. A key advantage of the QIM SDK is its ability to leverage heterogeneous compute resources available on Qualcomm platforms, including the GPU, DSP, and camera subsystem. This enables high-throughput, low-latency processing for both AI/ML workloads and multimedia operations. The plugins are designed to abstract hardware complexity while still allowing fine-grained control when needed. Whether you are building simple media pipelines or complex AI-driven workflows, the QIM SDK provides a scalable and efficient foundation to accelerate development and deployment.

Plugin Classification

1. AI / ML Plugins

PluginDescription
qtimlvconverterConverts input data into ML-friendly tensor formats
qtimlonnxExecutes ONNX-based machine learning models
qtimlqnnRuns models using Qualcomm Neural Network backend
qtimlsnpeRuns models using Snapdragon Neural Processing Engine
qtimltfliteExecutes TensorFlow Lite models
qtimldemuxSplits multiplexed ML data streams
qtimlpostprocessHandles output parsing and post-processing

2. Video Processing Plugins

PluginDescription
qtivtransformPerforms scaling, rotation, and format conversion
qtivcomposerComposes multiple video streams into one
qtivoverlayAdds graphical overlays (bounding boxes, text)
qtivsplitSplits video streams into multiple outputs

3. Camera Plugin

PluginDescription
qticamsrcCaptures video directly from the camera stack

4. Codec / V4L2 Plugins

PluginDescription
v4l2h264decHardware-accelerated H.264 decoder
v4l2h264encHardware-accelerated H.264 encoder
v4l2h265decHardware-accelerated H.265 (HEVC) decoder
v4l2h265encHardware-accelerated H.265 encoder
v4l2vp9decHardware-accelerated VP9 decoder
v4l2av1decHardware-accelerated AV1 decoder
qtijpegencJPEG image encoder

5. Streaming Plugins

PluginDescription
qtirtspbinEnables RTSP streaming pipelines
qtiredissinkStreams data to Redis endpoints
qtisocketsinkSends data over network sockets
qtisocketsrcReceives data over network sockets
waylandsinkDisplays output using Wayland

6. Metadata & Utilities Plugins

PluginDescription
qtimetamuxCombines metadata streams
qtimlmetaparserParses ML metadata outputs
qtimsgpubPublishes messages to external systems
qtimsgsubSubscribes to external message streams
qtiobjtrackerTracks detected objects across frames
qtibatchBatches multiple frames or inputs for processing

Proprietary Plugins

The following plugins are only available in qcom-multimedia-proprietary-image.
For more information on QLI images refer to Qualcomm Linux release

Summary

By combining these plugins with standard GStreamer elements, the QIM SDK empowers developers to construct scalable, production-ready multimedia and AI pipelines. The modular architecture ensures flexibility, while hardware acceleration across GPU, DSP, and camera subsystems ensures optimal performance.