Egg Detection Using CNN Architecture
This repository contains a web-based application for classifying egg conditions (fertile, infertile, and dead) using a Convolutional Neural Network (CNN) model. The model is trained using image data and deployed via a Flask web application to allow users to upload and classify new egg images easily.
Key Features:
- Image classification into three categories: fertile, infertile, and dead.
- CNN model built with TensorFlow and Keras.
- Flask-based web interface for user interaction and image uploads.
- Supports real-time predictions on uploaded images.
- Suitable for use in hatchery or poultry industries to automate egg sorting.
Technologies Used:
- Python
- TensorFlow / Keras
- Flask
- Gunicorn (for deployment)
- HTML / CSS (Frontend)
- Bootstrap (optional styling)
Compatible for deployment on platforms like Railway, Render, and PythonAnywhere
But here, Deploying using railway https://railway.com/
