GoogLeNet Example

This document describes how to use the QAI AppBuilder Python API to run inference with the GoogLeNet object recognition model on Qualcomm® Hexagon™ Processor (NPU).

Supported Devices

Device	SoC
Dragon Q6A	QCS6490
Dragon Q8B	SC8280XP
Fogwise® AIRbox Q900	QCS9075

Install QAI AppBuilder

tip

1. Please install QAI AppBuilder according to QAI AppBuilder Installation Guide.

2. Please configure ADSP environment variables according to Create ADSP Environment Variables.

Run the Example

Install Dependencies

Device

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

Run the Script

• Navigate to the example directory

QCS6490

Device

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

SC8280XP

Device

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

QCS9075

Device

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

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

  

  input image

• Run inference

  Device

  python3 googlenet/googlenet.py

  $ python3 googlenet/googlenet.py
       0.0ms [WARNING]  <W> Initializing HtpProvider
  
  /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-5.5.5/ipc/fastrpc/rpcmem/src/rpcmem_android.c:38:dummy call to rpcmem_init, rpcmem APIs will be used from libxdsprpc
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
     157.6ms [WARNING] Time: Read model file to memory. 8.91
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
     180.6ms [WARNING] Time: contextCreateFromBinary. 22.97
  
     180.7ms [WARNING] Time: UnmapViewOfFile. 0.00
  
     181.6ms [WARNING] Time: model_initialize googlenet 181.55
  
     255.7ms [WARNING] Time: model_inference googlenet 2.67
  
  Top 5 predictions for image:
  
  Samoyed 0.948613584
  West Highland White Terrier 0.0060515446
  Alaskan tundra wolf 0.0052576731
  Pomeranian 0.0047871661
  Chow Chow 0.0035575195
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
       0.0ms [WARNING]  <W> This META does not have Alloc2 Support
  
  /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-5.5.5/ipc/fastrpc/rpcmem/src/rpcmem_android.c:42:dummy call to rpcmem_deinit, rpcmem APIs will be used from libxdsprpc
     353.7ms [WARNING] Time: model_destroy googlenet 93.43
  

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