🐕 RedBag Predictor

📌 Project Overview

The RedBag-Predictor is a predictive microservice developed at Fatec Registro, designed to provide fast and accurate diagnoses for dogs with cataracts. Using Convolutional Neural Networks (CNNs), this API classifies images to determine whether an animal is healthy or affected by cataracts.

This Python-based microservice works in conjunction with the RedBag-Core, which acts as the core backend, handling user management, database operations, and API integrations.

👉 Access the RedBag-Core for more details.

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🚀 Getting Started

Prerequisites

Before running this project, ensure you have the following installed:

• Python
• Cloudinary Account
• RedBag-Core (must be running for full functionality)

Cloning the Repository

Clone this project to your local machine:

git clone https://github.com/MateusOK/RedBag-Predictor.git

After cloning, navigate to the project directory and install dependencies:

cd RedBag-Predictor
pip install -r requirements.txt

Environment Variables

Set up a .env file with your Cloudinary credentials:

CLOUD_NAME={YOUR_CLOUD_NAME}
API_KEY={YOUR_API_KEY}
API_SECRET={YOUR_API_SECRET}

Starting the API

Run the application:

python app.py

Ensure the Java API is running for full system functionality.

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📍 API Endpoints

Method	Route	Description
GET	/result/{public_id}	Returns the prediction result for an uploaded image
GET	/health	Checks if the API is running correctly

Example Responses

GET /result/{public_id}

Response:

{
  "prediction": "unhealthy",
  "confidence": 0.89
}

GET /health

Response:

{
  "status": "alive"
}

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🤝 Collaborators

Special thanks to all contributors to this project:

• Mateus Ribeiro
• Gustavo Eyros
• Rian Yuri
• Luiz Lopes

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This project is licensed under the MIT License.