Cat-Dog CNN Binary Classification

Overview

This repository contains code for a Convolutional Neural Network (CNN) model to perform binary classification on images of cats and dogs. The model is trained on a dataset of labeled images, and it can predict whether an input image contains a cat or a dog.

Installation

1. Clone the repository to your local machine:

  git clone [email protected]:SaidiSouhaieb/Keras-Binary-Classification.git

  cd Keras-Binary-Classification

2. Install required dependecies

  pip install -r requirements.txt   

Usage

1. Download model from cloud drive link : [https://drive.google.com/drive/folders/1wd5g_VsN1tJsiBwmvhZcaFff8hRChbCi?usp=sharing]

2. Place file near "model_predict.ipynb"

3. Add image path in the "img_path" variable

4. Predict!

Data

1. Download data below link : [https://www.kaggle.com/datasets/chetankv/dogs-cats-images]

2. Follow data structure below

Data Augmentation

1. Pass the data as structured below

2. Create Data Augmented folder

3. Wait as the images get created

Training

Data Structure

  dataset/
  |-- train/
  |   |-- cats/
  |   |-- dogs/
  |-- test/
  |   |-- cats/
  |   |-- dogs/

Pass the augmented data created before.

Thank You.