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A PyTorch-based deep learning project for classifying images of open and closed eyes using the MRL Eye Dataset with MLflow for experiment tracking.

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Open Closed Eyes Classification

This project aims to classify images of open and closed eyes using the MRL Eye Dataset. It leverages PyTorch for deep learning, torchvision for image preprocessing, and MLflow for experiment tracking. The dataset consists of gray-scale images captured under different lighting conditions and by various devices.

Project Overview

The goal of this project is to classify images into two categories:

  • Open Eye
  • Closed Eye

This project is implemented in Python and uses PyTorch for model building and training. The training process is tracked and logged using MLflow.

Dataset

The MRL Eye Dataset is a large-scale collection of infrared images of human eyes. This dataset is publicly available here.

The dataset is divided into:

  • Open Eyes
  • Closed Eyes

About

A PyTorch-based deep learning project for classifying images of open and closed eyes using the MRL Eye Dataset with MLflow for experiment tracking.

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