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A brief guide to Acuitylite

Acuitylite is an end-to-end neural-network deployment tool for embedded systems.
Acuitylite support converting caffe/darknet/onnx/tensorflow/tflite models to TIM-VX/TFLite cases. In addition, Acuitylite support asymmetric uint8 and symmetric int8 quantization.

System Requirement

  • OS: Ubuntu Linux 20.04 LTS 64-bit (recommend)
  • Python Version: python3.8 (needed)


pip install acuitylite



Framework Support

Tips: You can export a TFLite app and using tflite-vx-delegate to run on TIM-VX if the exported TIM-VX app does not meet your requirements.

How to run TIM-VX case

The exported TIM-VX case supports both make and cmake.
Please set environment for build and run case:

  • TIM_VX_DIR=/path/to/tim-vx/build/install
  • VIVANTE_SDK_DIR=/path/to/tim-vx/prebuilt-sdk/x86_64_linux

Attention: The TIM_VX_DIR path should include lib and header files of TIM-VX. You can refer TIM-VX to build TIM-VX.


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