Raspberry pi TensorFlow-lite Object detection

Raspberry pi TensorFlow-lite Object detection

How to use TensorFlow Lite object detection models on the Raspberry Pi.



TensorFlow Lite is an optimized framework for deploying lightweight deep learning models on resource-constrained edge devices. TensorFlow Lite models have faster inference time and require less processing power, so they can be used to obtain faster performance in realtime applications.


  

System Requirements

Hardware

·     Raspberry Pi Board (4B , 3B+)

·     IP Camera, USB Camera or Pi Camera

·     SD Card 32GB

·     5V DC. 2A Power Supply

Software

·     OS Raspbien 10 ( buster )

·     Python 3.7.2

·     Tensorflow lite 1.14.0

·     OpenCV 4.0.0

Machine Learning Model : MobileNet SSD V2 Quantised

 

Source Code
https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi


Reference

Install Tensorflow on Raspberry pi
https://www.tensorflow.org/install/source_rpi

Tensorflow Model Zoo
https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md

How to Run TensorFlow Lite Object Detection

https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi/blob/master/Raspberry_Pi_Guide.md