Image Classification
AIoT
QNN
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Model Information

Source model

  • Input shape: [1x3x224x224], [1x77]
  • Number of parameters: 43.02M, 105.16M
  • Model size: 172.10M, 122.99M
  • Output shape: [1x512], [1x512]

Source model repository: clip-vit-base-patch16

Inference with AidLite SDK

SDK installation

Model Farm uses AidLite SDK as the model inference SDK. For details, please refer to the https://docs.aidlux.com/software/ai-sdk/aidlite_guide(https://docs.aidlux.com/software/ai-sdk/aidlite_guide)

  • Install AidLite SDK
# Install the appropriate version of the aidlite sdk
sudo aid-pkg update
sudo aid-pkg install aidlite-sdk
# Download the qnn version that matches the above backend. Eg Install QNN2.36 Aidlite: sudo aid-pkg install aidlite-qnn236
sudo aid-pkg install aidlite-{QNN VERSION}
  • Verify AidLite SDK
# aidlite sdk c++ check
python3 -c "import aidlite ; print(aidlite.get_library_version())"

# aidlite sdk python check
python3 -c "import aidlite ; print(aidlite.get_py_library_version())"

Run Demo

# Environment setup
pip install ftfy packaging regex tqdm Pillow numpy
# Run example
cd model_farm_clip-vit-16_qcs8550_qnn2.36_fp16_aidlite/python
python3 run_test.py