Dog and Cat Image Classifier using CNN

This project implements a Convolutional Neural Network (CNN) to classify images of dogs and cats. The model is trained on a dataset containing 8000 images for training and 2000 images for testing.

Overview
Requirements
Usage
Project Structure
Results
License

Overview

The objective of this project is to build and train a CNN that can accurately classify images as either dogs or cats. The model is trained on a labeled dataset consisting of 8000 training images and evaluated on a separate test set of 2000 images.

Requirements

Make sure you have the following dependencies installed:

Python 3.x
TensorFlow
Keras
Other dependencies (you can install them using pip install -r requirements.txt)

Usage

Clone the repository:

git clone git@github.com:basantashah/dog_cat_CNN-AI.git

Navigate to the project directory:
```
cd dog-cat-image-classifier
```
Install the dependencies:
```
pip install -r requirements.txt
```
Train the model:
```
python train_model.py
```
Evaluate the model:
```
python evaluate_model.py
```

Make predictions:

python predict.py path/to/your/image.jpg

Project Structure

'''└───Resources
    ├───single_prediction
    ├───test_set
    │   ├───cats
    │   └───dogs
    └───training_set
        ├───cats
        └───dogs'''

data/: Contains the training and testing datasets.
models/: Stores the trained CNN model.
train_model.py: Script for training the CNN.
evaluate_model.py: Script for evaluating the model on the test set.
predict.py: Script for making predictions on new images.
README.md: Project documentation.

Results

The trained model achieved an accuracy of X% on the test set. Here are some sample predictions:

Image 1: Dog
Image 2: Cat
...

Feel free to explore the project, experiment with different architectures, and contribute to its improvement.

License

I have developed for my learning purpose, anyone can pull and help improve the code as per their requirement

basantashah/dog_cat_CNN-AI