Dog Breed Identification

This project leverages transfer learning to identify dog breeds from dog images. Using TensorFlow and Keras, MobileNet V2 is trained on a diverse dataset of dog breeds.

Features

• Classifies images into various dog breeds.
• A total of 120 unique dog breeds.
• Utilizes a user-friendly interface via Streamlit (coming soon).

Dataset

The model is trained on a comprehensive dataset from Kaggle containing images of multiple dog breeds.

• (https://www.kaggle.com/c/dog-breed-identification)

Model Training

The model employs transfer learning with MobileNet V2, which includes:

• Data Augmentation: To enhance model robustness by creating variations of the training images.
• Early Stopping: To prevent overfitting by stopping training when the validation loss stops improving.
• Performance Metrics: Accuracy and loss are tracked during training, with visualizations provided.

Installation

To set up the project, clone the repository and install the required libraries:

• Pandas
• Numpy
• MatplotLib
• TensorFlow
• Keras

git clone https://github.com/sreejith2005/Dog-Breed-Identification.git
cd Dog-Breed-Identification
pip install -r requirements.txt