# Download source code for development The eSDK (extensible SDK) needs to be setup to develop application/plugin code. See the [Qualcomm Intelligent Multimedia Software Development Kit (IM SDK) Quick Start Guide](https://docs.qualcomm.com/bundle/publicresource/topics/80-70018-51/introduction.html) for instructions on setting up the eSDK and downloading and compiling the source code. develop-own-app Sheet.2 Sheet.14 Preprocessing Preprocessing Sheet.1 qtimlvconverter qtimlvconverter Sheet.3 ML inference plugins ML inference plugins Sheet.4 Qualcomm IM SDK postprocessing plugins Qualcomm IM SDK postprocessing plugins Sheet.5 Qtimlqnn Used by BIN models QtimlqnnUsed by BIN models Sheet.6 Qtimlsnpe Used by DLC models QtimlsnpeUsed by DLC models Sheet.7 qtimltflite Used by TFLite models qtimltfliteUsed by TFLite models Sheet.8 qtimlvsegmentation qtimlvsegmentation Sheet.9 qtimlvdetection qtimlvdetection Sheet.10 qtimlvclassification qtimlvclassification Sheet.11 qtimlvpose qtimlvpose Dynamic connector Sheet.26 Sheet.27 qtimlvsuperresolution qtimlvsuperresolution The following pre-/postprocessing ML plugins are available with the Qualcomm IM SDK. Use these plugins to develop your own use case. | **Plugin** | **Functionality** | | --- | --- | | qtimlvconverter | Transforms incoming video buffers into neural-network tensors
while performing required format conversion and resizing. | | qtimlvclassification | Performs postprocessing of output tensors for classification use
cases. | | qtimlvdetection | Performs postprocessing of output tensors for detection use
cases. | | qtimlvsegmentation | Performs postprocessing of output tensors for pixel-level use
cases, like image segmentation, depth-map, etc. | | qtimlvpose | Performs postprocessing of output tensors for pose estimation
use cases. | | qtimlvsuperresolution | Performs postprocessing of the output tensors for video super
resolution use cases. | The Qualcomm IM SDK, supports the following use cases and related models. | **Use cases supported by Qualcomm IM SDK** | **Supported Models** | | --- | --- | | Classification | Models like Mobilenet. Currently Qualcomm AI Hub has 11
classification models supported. New models will keep getting
added to AI Hub. | | Detection | Models like ssd-mobilenet, yolov5, yolo-nas, and yolov8 | | Segmentation | Models like deeplabv3\_resnet and ffnet | | Pose detection | Models like posenet\_mobilenet | | Super resolution | Models like QuickSRNet, XLSR, etc. | Note A list of verified models from Qualcomm AI Hub is available in a [Integrate an AI Hub model in an application](https://docs.qualcomm.com/doc/80-70018-15B/topic/integrate-ai-hub-models.html). You can use many other models with similar postprocessing requirements, however it’s recommended to verify postprocessing support in the relevant Qualcomm IM SDK plugins before integrating your own model. Last Published: Oct 13, 2025 [Previous Topic Develop your own AI/ML application with the Qualcomm IM SDK](https://docs.qualcomm.com/bundle/publicresource/80-70018-15B/topics/develop-your-own-application-im-sdk.md) [Next Topic Integrate a custom AI model in an application](https://docs.qualcomm.com/bundle/publicresource/80-70018-15B/topics/integrate-custom-model.md)