Project Overview

This project consists of using convolutional neural networks (CNNs) to produce an algorithm composed of a pipeline of CNNs. That algorithm identifies if an image provided by the user contains a person, a dog or neither. In the case of a dog, the algorithm responds with the dog breed. In the case of a person the algorithm responds with the dog breed the person in the picture most resembles. Finally in the case of neither a dog nor a person in the image the algorithm will respond with invalid input.

Project Instructions

Instructions

1. Clone the repository and navigate to the downloaded folder.

   	git clone https://github.com/GuilhermeBaldo/project-dog-breed-classification.git
   	cd project-dog-breed-classification
   

2. Download the dog dataset. Unzip the folder and place it in the repo, at location dogImages/. The dogImages/ folder should contain 133 folders, each corresponding to a different dog breed.

3. Download the human dataset. Unzip the folder and place it in the repo, at location lfw/. If you are using a Windows machine, you are encouraged to use 7zip to extract the folder.

4. Create the conda environemnt usint the environment.yml file.

   	conda env create --file=environment.yaml
   

5. Open a terminal window and navigate to the project folder. Open the notebook and follow the instructions.

   	jupyter notebook dog_app.ipynb