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ai_edge's Introduction

Running Deep neural network dedicated to Espressif SoCs

This repository created for experimental study for deploying Deep neural networks on Espressif SoCs and evaluating their performance.

Overview

Tensorflow_lite and ESP-DL are two main frameworks to deploy DNN on Espressif SoCs. Projects are placed in the folders with same name as their used framework. Some tools are developed and placed in ESP-DL/Tools to facilitate some tasks like converting ONNX model to C/CPP codes ready to compile.

Software requirements

ESP-IDF V5.x.

Python 3.7.

Instalation steps

git clone --recursive https://github.com/Farzinkh/AI_EDGE.git

cd AI_EDGE

pip install -r requirements.txt

Hardwares to Utilize

ESP32-CAM

Download Schematic

ESP32-S3

Download Schematic

With a microSD Card Adapter Module

ai_edge's People

Contributors

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ai_edge's Issues

ESP-DL ONNX Conversion for quantization tool

Hello Frazinkh,

I am also a student who is interested int ML and embedded AI.
I found your repo while browsing for ESP-DL stuff. Furthermore, I want to compare ESP-DL TVM with the quantization tool, but it is harder than I thought.
At the moment I am facing some problems with the quantization tool from ESP and I wonder if you could help me out.

In one of your colab scripts, I found the following, could you explain to me why?
## Second way (not working with ESP_DL optimizer)

Maybe we could get in contact. I would be very happy to receive a reply.

accuracy has decreased after quatization

hello, I met the same problem that the accuracy of the model has decreased after quantization. But I can't figure out this problem through the repository in your github. I really want to know how do you solved this problem? thank you.

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