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QAI AppBuilder

Quick AI Application Builder (QAI AppBuilder) helps developers easily use the Qualcomm® AI Runtime SDK to deploy AI models and design AI applications on Qualcomm® SoC platforms equipped with Qualcomm® Hexagon™ Processor (NPU). It encapsulates model deployment APIs into a set of simplified interfaces for loading models to the NPU and performing inference. QAI AppBuilder significantly reduces the complexity of model deployment for developers and provides multiple demos as references for designing their own AI applications.

Supports Python API / C++ API

QAI-APPBUILDER Architecture

Supported Devices

DeviceSoC
Dragon Q6AQCS6490
Fogwise® AIRbox Q900QCS9075

Installation Methods

Clone the Repository

Device
git clone -b radxa-dev https://github.com/ZIFENG278/ai-engine-direct-helper.git && cd ai-engine-direct-helper

Install via Wheel Package

Create a Virtual Environment
tip

Create a virtual environment to isolate the Python libraries

Device
sudo apt install python3-venv
python3 -m venv .venv
source .venv/bin/activate
Device
pip3 install https://github.com/ZIFENG278/ai-engine-direct-helper/releases/download/radxa-dev-2.38.0/qai_appbuilder-2.38.0-cp312-cp312-linux_aarch64.whl

Build from Source

Device
git submodule update --init --recursive

Download QAIRT SDK

tip

Please download and extract the QAIRT SDK according to Download QAIRT SDK Package

Configure QAIRT Environment Variables
Device
export PRODUCT_SOC=6490 DSP_ARCH=68
Device
cd qairt/2.42.0.251225
source bin/envsetup.sh
export ADSP_LIBRARY_PATH=$QNN_SDK_ROOT/lib/hexagon-v${DSP_ARCH}/unsigned
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$QNN_SDK_ROOT/lib/aarch64-oe-linux-gcc11.2

Compile qai_appbuilder

Create a Virtual Environment
tip

Create a virtual environment to isolate the Python libraries

Device
sudo apt install python3-venv python3-dev cmake gcc g++
python3 -m venv .venv
source .venv/bin/activate
Compile qai_appbuilder Wheel
Device
pip3 install setuptools
cd ai-engine-direct-helper
python3 setup.py bdist_wheel

After compilation, a qai_appbuilder-2.38.0-cp312-cp312-linux_aarch64.whl file will be generated in the dist directory

Install qai_appbuilder

Install qai_appbuilder Wheel
Device
cd dist
pip3 install ./qai_appbuilder-2.38.0-cp312-cp312-linux_aarch64.whl

Create a qai_libs symlink in ai-engine-direct-helper/samples/python to link to the lib directory of the QAIRT SDK

tip

If you haven't downloaded the complete QAIRT_SDK, you can install qcom-qairt and then create the symlink.

qcom-qairt is a slimmed-down version of QAIRT-SDK, installing only the required files

Device
sudo apt install qcom-qnn-sdk-v68 qcom-genie-sdk-v68
Device
ln -s /usr/lib/aarch64-linux-gnu samples/python/qai_libs

Create ADSP Environment Variables

tip

If you installed the qcom-qairt package, use the following command to create the ADSP_LIBRARY_PATH environment variable

Device
export ADSP_LIBRARY_PATH=/usr/lib/aarch64-linux-gnu

Application Examples

tip

For QCS6490 Demos, please refer to Demo Examples

Device
cd ai-engine-direct-helper/samples/linux/python
  • Object Recognition

    ModelRun Command
    convnext_basepython3 convnext_base/convnext_base.py
    convnext_tinypython3 convnext_tiny/convnext_tiny.py
    efficientnet_b0python3 efficientnet_b0/efficientnet_b0.py
    efficientnet_b4python3 efficientnet_b4/efficientnet_b4.py
    efficientnet_v2_spython3 efficientnet_v2_s/efficientnet_v2_s.py
    googlenetpython3 googlenet/googlenet.py
    inception_v3python3 inception_v3/inception_v3.py
    levitpython3 levit/levit.py
    regnetpython3 regnet/regnet.py
    shufflenet_v2python3 shufflenet_v2/shufflenet_v2.py
    squeezenet1_1python3 squeezenet1_1/squeezenet1_1.py
    vitpython3 vit/vit.py
    wideresnet50python3 wideresnet50/wideresnet50.py
  • Image Segmentation

    ModelRun Command
    fcn_resnet50python3 fcn_resnet50/fcn_resnet50.py
  • Object Detection

    ModelRun Command
    yolov8_detpython3 yolov8_det/yolov8_det.py
  • Image Super-Resolution

    ModelRun Command
    quicksrnetmediumpython3 quicksrnetmedium/quicksrnetmedium.py
    real_esrgan_general_x4v3python3 real_esrgan_general_x4v3/real_esrgan_general_x4v3.py
    real_esrgan_x4pluspython3 real_esrgan_x4plus/real_esrgan_x4plus.py
    sesr_m5python3 sesr_m5/sesr_m5.py
    xlsrpython3 xlsr/xlsr.py

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