Mammography Classification

This repository contains a deep learning model for classifying mammogram images. The goal is to assist in the detection of breast cancer by distinguishing between benign, malignant, and normal cases. The model uses a Convolutional Neural Network (CNN) trained on a publicly available dataset.

Features

• Classification Model: A CNN designed for image classification.
• Dataset: Utilizes a dataset of mammogram images with labels for benign, malignant, and normal cases.
• Preprocessing: Includes scripts for data augmentation and normalization to improve model performance.
• Training: Provides a training pipeline to fine-tune the model.
• Evaluation: Scripts for evaluating the model's accuracy, precision, and recall.

Installation

1. Clone the repository:

   git clone [https://github.com/PieriFra/Mamografias.git](https://github.com/PieriFra/Mamografias.git)
   cd Mamografias

2. Install dependencies:

   pip install -r requirements.txt

Usage

1. Prepare the data: Place your mammogram images in the data/raw folder. The folder structure should be data/raw/{benign, malignant, normal}.

2. Run the training script:

   python train.py

3. Evaluate the model:

   python evaluate.py