This project contains the script that can track the specific marker on the camera. This script is controlled by voice.
Python (the version is 3.13.7) and libraries open-cv, vosk and pyttsx3 are used.
The table of files' responsibilities:
| File | Responsibility |
|---|---|
| main.py | Launching all project flow |
| voice_assistant.py | Detecting voice and speaking to users |
| image_detector.py | Detecting fruit, managing camera functions |
This project is based on classes FruitDetector and VoiceAssistant. To run a camera and listen at once the threads are used, to control them the global variables were considered.
The brief description of classes types is shown in the following figure:
This project is able to detect fruit in a frame. The possible fruit that can be detected are presented in the following table. Realization of classes for a camera is based on open-cv library.
| Fruit Title | Lower HSV bound | Upper HSV bound |
|---|---|---|
| Orange | [5, 150, 150] | [15, 255, 255] |
| Green Apple | [40, 100, 80] | [80, 255, 255] |
| Tomato | [0, 180, 120] | [10, 255, 255] |
| Lemon | [20, 0, 0] | [40, 255, 255] |
The HSV color representation was used to find color pattern of fruit.
The realization of the code that is responsible for the fruit detecting is in file image_detector.py.
The VoiceAssistant class consists of two classes: Listener and Speaker. The VoiceAssistant uses Listener class to recognize a text so it could understand a command. The class Speaker is used to response to the user by VoiceAssistant. To recognize a command in text the regular expressions are used.
The class Listener uses vosk library to detect english voice. The vosk-model-small-en-us-0.15 was used, that can be found on github: https://github.com/alphacep/vosk-space/blob/master/models.md (February 13, 2026).
The class Speaker uses pyttsx3 to say to the user.
This voice assistant is able to react on the following list of commands:
| Command Title | Trigger Word | Reaction |
|---|---|---|
| Switching a camera | Camera | Turning on/off camera |
| Finding fruit | Find [orange/lemon/tomato] | Detecting the fruit on the camera |
| Making a screenshot | Screenshot | Making a picture that is in the camera |
| Quit | Quit/Exit | Finishing launched session |
These files can be found in the file voice_assistant.py.
First you should define a virtual environment (basic module venv of python is used), in the root directory of the project run these commands in your terminal to create and activate the virtual environment:
python -m venv venv
.\venv\Scripts\activate
After that run the following command to install required packages for this projects:
pip install -r req.txt
To run project run in the root of project:
python main.py