Object-Detection-with-Voice-Feedback-using-Raspberry-Pi-4-and-Bullseye-OS.

Introduction

In this Project, I teach you how to set up the TensorFlow Lite and Voice Feedback on the Raspberry Pi 4 using latest Bulleye OS (Debian version: 11) and use it to run object detection models with voice feedback. In this work, I will use the Raspberry Pi 3 and 4 running either Bulleye OS or latest Debian 64 bit version supported.(Raspbian OS Repo Link: https://www.raspberrypi.com/software/operating-systems/).

Lesson 1 - How to Set Up TensorFlow Lite on the Raspberry Pi

Step 1. Check Python Version in Raspberry Pi

In this tutorial Tensorflow Lite installation currently supported python version is 3.5, 3.6, 3.7, 3.8 & 3.9(above)..

python3 --version

Step 2. Update the Raspberry Pi

sudo apt update

sudo apt install rpi-update

Step 3. Download & Unzip My Github Repository

clone My GitHub repository

git clone https://github.com/thyagarajank/Object-Detection-with-Voice-Feedback-using-Raspberry-Pi-4-and-bullseye-OS.git

Unzip the Folder "Object-Detection-with-Voice-Feedback-using-Raspberry-Pi-and-Tensorflow-Lite". Move the all files to "tflite1" folder.

uzip Object-Detection-with-Voice-Feedback-using-Raspberry-Pi-4-and-bullseye-OS

Step 4. Create New Directory

Create New Dir at (/home/pi/)

mkdir tflite1

Copy all Files to "tflite1"

cp -r Object-Detection-with-Voice-Feedback-using-Raspberry-Pi-4-and-bullseye-OS/* tflite1/

Work in this "/home/pi/tflite1" directory.

cd /home/pi/tflite1
pwd

Step 5. Create a Virtual Environment called "tflite1-env".

Intall Virtualenv

sudo pip3 install virtualenv

Create the "tflite-env" Virtual Environment

python3 -m venv tflite1-env

Activate Virtual Environment

source tflite1-env/bin/activate

Step 6. Install TensorFlow Lite & Other Dependencies.

OpenCV required packages and other libraries mention in .sh (shell) script. it will automatically download and installed.

cd rpi-bullseye-opencv4.5.5/

Run shell script(Installing OpenCV 4.6.0 and the dependencies on your Raspberry Pi 64-bit OS) It will take minimal 2.0 hour !

bash install.sh 

cd ..

Install TensorFlow Lite Runtime.

sudo apt-get install python3-tflite-runtime

Install Opencv-python.

pip3 install opencv-python

Install shell script TFlite and Packages

cd tensorflow-lite-bullseye/

Install Tensorflow-lite.sh

bash tensorflow-lite.sh 

python3 -m pip install tflite-runtime

Install Tensorflow Lite 2.5.0(tflite_runtime-2.5.0.post1-cp39-cp39-linux_armv7l.whl)

pip3 install https://github.com/google-coral/pycoral/releases/download/v2.0.0/tflite_runtime-2.5.0.post1-cp39-cp39-linux_armv7l.whl

Step 7. Download Google's sample TFLite model

coco_ssd_mobilenet_v1_1.0_quant_2018_06_29 object detection model run on TensorFlow Lite

wget https://storage.googleapis.com/download.tensorflow.org/models/tflite/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.zip

Unzip the download folder.

unzip coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.zip -d Sample_TFLite_model

NOTE: If use own custom detection model. Do not Download Google's SSDLite-MobileNet-v2 object detection model(step 7). Copy your own custom Model File to Sample_TFLite_model.

Lesson 2 - Run Object Detection in TensorFlow Lite

Checklist

• 1. Setup your webcam or Picamera plugged in
• 2. Enabled camera interface in Raspberry Pi (Click the raspberry icon in the top left corner of the screen, select--> Preferences --> Raspberry Pi Configuration, and go to the Interfaces tab and verify Camera is set to Enabled. After reboot the Raspberry Pi.)
• 3. Closing applications you aren't using and free up memory.
• 4. Before running the command, make sure the tflite1-env environment is active. (tflite1-env) appears in front of the terminial. This command for run object detection model only.

Step 8. Run the TensorFlow Lite Object Detection Model Only

Webcam Image object Detection Python Program.

python3 object_only_webcam.py --modeldir=Sample_TFLite_model

Step 9. Install Text to Speech Packages.

• 1. pyttx3
• 2. espeak Intall "pyttsx3" Text to Speech (TTS) library for Python 2 and 3

pip install pyttsx3

Install espeak library

sudo apt-get install espeak

Issue in install espeak Package

Try this 2 Command

sudo apt update && sudo apt install rpi-update

sudo apt-get install python-espeak

Step 10. Run the TensorFlow Lite Object Detection Model with Voice Feedback.

This Python Program for run object detection with voice feedback.

python3 object_voice_webcam.py --modeldir=Sample_TFLite_model

Lesson 3 - Train own Custom Object Detection Model

https://github.com/thyagarajank/tensorflow-own-custom-object-detection-model-in-google-colab Tensorflow (.pb file) Custom Model Training In colab (Code Availble in My Github). Tensorflow(.pb) file to Tensorflow Lite (.tflite) file Convertion Program (Upload Soon).