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Inception v3 Example

This document explains how to use the QAI AppBuilder Python library to run the Inception-v3 object detection model on the Radxa Dragon Q6A.

Install QAI AppBuilder​

tip

Please follow the QAI AppBuilder Installation Guide

Run the Example​

Install Dependencies​

Device
pip3 install requests tqdm qai-hub py3_wget opencv-python torch

Run the Script​

  • Navigate to the example directory

    Device
    cd ai-engine-direct-helper/samples/linux/python

  • Prepare the input image. The following image is used as an example:

    Input Image

  • Execute the inference

    Device
    python3 inception_v3/inception_v3.py --image ./inception_v3/input.jpg
    (.venv) ubuntu@ubuntu:~/git_clone/ai-engine-direct-helper/samples/linux/python$ python3 inception_v3/inception_v3.py --image ./inception_v3/input.jpg
    Current file directory: /home/ubuntu/git_clone/ai-engine-direct-helper/samples/linux/python/inception_v3
    model_path: /home/ubuntu/git_clone/ai-engine-direct-helper/samples/linux/python/inception_v3/models/inception_v3.bin
    /prj/qct/webtech_scratch20/mlg_user_admin/qaisw_source_repo/rel/qairt-2.37.1/point_release/SNPE_SRC/avante-tools/prebuilt/dsp/hexagon-sdk-5.4.0/ipc/fastrpc/rpcmem/src/rpcmem_android.c:38:dummy call to rpcmem_init, rpcmem APIs will be used from libxdsprpc

    Top 5 predictions for image:

    goldfish 0.9550418258
    rock beauty 0.0439209454
    anemone fish 0.0008165489
    puffer 0.000045009
    ambulance 0.0000313302

    /prj/qct/webtech_scratch20/mlg_user_admin/qaisw_source_repo/rel/qairt-2.37.1/point_release/SNPE_SRC/avante-tools/prebuilt/dsp/hexagon-sdk-5.4.0/ipc/fastrpc/rpcmem/src/rpcmem_android.c:42:dummy call to rpcmem_deinit, rpcmem APIs will be used from libxdsprpc
       902.9ms [WARNING] Time: model_destroy inceptionV3 17.96

The output shows that goldfish has the highest confidence score, which matches the content of the input image.