Cats vs Dogs Classifier

Project Overview

This project classifies two classes of images which are dogs and cats. We can divide the projects into parts as following :

1.Load the dataset.

2.Preprocessing the data such as : (Rescale , Resize , divide the data into validation and training).

3.build the classifer using keras and TensorFlow .

4.Training the data using classifer.

5.Compare between the models and get the best classifer model.

6.Use the classifer to classify new data.

Dataset

The dataset used for training purpose has been used from Kaggle. You can download the dataset from:

https://www.kaggle.com/c/dogs-vs-cats/data

The training folder has 20000 training samples and about 5000 validation samples.

Accuracy

The model has an accuracy of 86% on the training set and 83.68% on the validation set.

Prerequisites

python v3.8

tensorflow v2.5

keras v2.2.5

numpy v1.21.0

pandas v1.2.4

matplotlib v3.4.2

tqdm v4.61.1