MobileNet V2 Implementation from scratch

This repository contains the implementation of MobileNetV2 to classify images of cats and dogs using TensorFlow.

Repository Structure

• models/: Contains the MobileNetV2 model definition.
• utils/: Contains utility functions for preprocessing and image handling.
• train.py: Script to train the model.
• evaluate.py: Script to evaluate the model.
• predict.py: Script to make predictions using the trained model.
• requirements.txt: List of dependencies.
• mobilenet_v2_cats_vs_dogs.h5: Pre-trained weights provided for your convenience.

Usage

Training

To train the model, run:

python train.py

Evaluation

To evaluate the model, run:

python evaluate.py

Prediction

Download your desired image and save it in the main directory of project with the name example.jpg

# For Example
wget -q -O example.jpg https://cdn-prod.medicalnewstoday.com/content/images/articles/322/322868/golden-retriever-puppy.jpg

Run the predict.py script to make predictions using the trained model:

python predict.py

Dependencies

Install the required dependencies using:

pip install -r requirements.txt

Dataset

The dataset used for training is the Cats vs. Dogs dataset from TensorFlow Datasets.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

The MobileNetV2 model architecture is inspired by the original MobileNetV2 paper.