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In this repo, Raspberry Pi was connected to the Hikvision IP camera and get prediction with yolov8 tflite model.

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shoxa0707/Deploy-Yolov8-in-Raspberry-Pi

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Deploy TensorflowLite model in Raspberry Pi with Hikvision ip camera

Introduction

Raspberry Pi has long been the gold standard for inexpensive single-board computing, powering everything from robots to smart home devices to digital kiosks. When it launched in 2019, the Raspberry Pi 4 took Pi to another level, with performance that’s good enough to use in a pinch as a desktop PC, plus the ability to output 4K video at 60 Hz or power dual monitors. More recently, the Raspberry Pi 4 (8GB) model came out, offering enough RAM for serious desktop computing, productivity and database hosting.

Get started

First of all, you should prepare devices(Raspberry Pi and Hikvision ip camera) to launch program.

It's easy after you watch these demo videos:

  1. Install Raspberry Pi SD card (You must install 64-bit OS for this project)
  2. Setup Hikvision ip camera

Installation

  1. Clone repo

    https://github.com/shoxa0707/Deploy-Yolov8-in-Raspberry-Pi.git
    cd Yolov8-in-RaspberryPi
  2. Install dependent packages

    pip install -r requirements.txt

After installation done. The project is ready to launch:

python run.py

About

In this repo, Raspberry Pi was connected to the Hikvision IP camera and get prediction with yolov8 tflite model.

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