OptiVision

Table of Contents

• Introduction
• Features
• Requirements
• Installation
• Contributers

Introduction

OptiVision is a sophisticated Java application engineered to maximize the potential of MLKit and pretrained TensorFlow models. Seamlessly integrating advanced computer vision functionalities, including face detection, pose estimation, visitor analysis, and face recognition, OptiVision revolutionizes visual analysis and processing. With intuitive controls and privacy-conscious features like face obscuring, OptiVision empowers users to explore the depths of machine learning-driven insights with ease and confidence.

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Features

• Face detection: The application can accurately detect and locate human faces in images and video streams.
• Pose detection: It can determine the position and orientation of a person's body in images or videos.
• Visitor analysis: The application provides insights and analytics on the number of visitors, their demographics, and behavior.
• Face recognition: It can recognize and identify individuals based on their facial features.
• Hide/Obscure Face options: Users can choose to hide or obscure faces in images or videos for privacy or anonymization purposes.

Requirements

To run this Java application, you need the following:

• Java Development Kit (JDK) 8 or above.
• MLKit library.
• Pretrained TensorFlow models for face detection, pose detection, and face recognition.

Installation

1. Install the Java Development Kit (JDK) if you haven't already.
2. Set up MLKit in your Java project. You can follow the official documentation of MLKit for Java for instructions on how to add MLKit to your project.
3. Download the pretrained TensorFlow models for face detection, pose detection, and face recognition.
4. Add the pretrained TensorFlow models to your project's resources or specify their file paths in the application code.

Contributers

If you encounter any problems, do not hesitate to contact.
@Egemen Eroglu
@Sahan Yarar