AgarVision

Welcome to AgarVision, a cutting-edge mobile application specifically designed to revolutionize the way researchers count bacterial colonies on agar plates. By automating this crucial process, AgarVision significantly enhances accuracy and efficiency in biotechnological research environments.

Elevating Research with AgarVision

AgarVision was crafted during Phase B of our capstone project, employing advanced technologies such as OpenCV for real-time image segmentation, and K-means clustering to manage variations in texture and color, even with limited datasets. Our goal is to mitigate human error in manual counts and streamline research workflows.

Core Features

• Advanced Image Segmentation: Leverages OpenCV's adaptive thresholding techniques for precise image segmentation.
• Accurate Colony Detection: Utilizes custom-developed contour detection algorithms to pinpoint and delineate bacterial colonies with remarkable accuracy.
• Sophisticated Clustering: Applies K-means clustering to address textural and color inconsistencies, ensuring minimal data does not compromise result accuracy.
• Enhanced Security: Features top-tier security protocols including data encryption and user token authentication to safeguard sensitive information.
• Efficient Data Management: Employs Firebase for robust cloud storage solutions, complete with regular backups for unparalleled data integrity and reliability.

Project Architecture

• AgarVision_Client: A Flutter-based mobile application.
• AgarVision_Server: Backend service handling complex data processing and computations.
• App Screens: Explore the user interface designs and app functionality through detailed screenshots.
• AgarVision Maintenance Guide.docx: Comprehensive guide for maintaining the application.
• AgarVision User Guide.docx: Detailed manual for end-users to navigate and utilize the application effectively.
• Final Project B - Presentation.pptx: A presentation showcasing the developmental strides in Phase B of the project.
• Final Project Phase A.docx: Documentation outlining the initial stages of the project.
• Phase B Abstract.docx: A concise abstract detailing the objectives and achievements of Phase B.

Getting Started

Set up AgarVision with these simple steps:

git clone https://github.com/IbraheemGanayim/AgarVision.git
cd AgarVision
# Installation instructions for both client and server applications

Using AgarVision

For a detailed walkthrough on how to maximize your use of AgarVision, please consult the AgarVision Maintenance Guide.docx.

We are excited to see how AgarVision will transform your research operations!