Project Title: Image Classification with Keras

Overview

This project is designed to demonstrate the capabilities of deep learning in image classification tasks. Using a dataset (e.g., dogs vs. cats), the project employs various neural network architectures to classify images. It includes data preprocessing, model training, evaluation, and prediction stages.

Features

• Data processing with NumPy and Pandas.
• Image extraction and preprocessing using OpenCV.
• Implementation of convolutional neural networks with Keras and TensorFlow.
• Model training with real-time data augmentation.
• Evaluation of model performance using accuracy and loss metrics.
• Prediction on new, unseen images.

Requirements

• Python 3.x
• NumPy
• Pandas
• OpenCV
• TensorFlow
• Keras

Installation

Instructions for setting up the project environment:

git clone https://github.com/qqmath/keras-cat-dog
pip install numpy pandas opencv-python tensorflow keras

Dataset

The dataset used for training is the "Dogs vs. Cats Redux: Kernels Edition" from Kaggle.