Project Overview

Welcome to the Convolutional Neural Networks (CNN) project in Udacity's DeepLearning Nanodegree! At the end of this project, the code will accept any user-supplied image as input. If a dog is detected in the image, it will provide an estimate of the dog's breed. If a human is detected, it will provide an estimate of the dog breed that is most resembling. The image below displays potential sample output of your finished project.

The Road Ahead

We break the notebook into separate steps:

• Import Datasets
• Detect Humans
• Detect Dogs
• Create a CNN to Classify Dog Breeds (from Scratch)
• Create a CNN to Classify Dog Breeds (using Transfer Learning)
• Test the Algorithm

Some Interesting Results:

• Final Model's Test Accuracy: 76% (641/836 images).

This dog's breed is: Welsh springer spaniel

Hello, Human! If you were a dog, you would look like: Canaan dog

Hello, Human! If you were a dog, you would look like: Chinese shar-pei

Hello, Human! If you were a dog, you would look like: French Bulldog

Hello, Human! If you were a dog, you would look like: Dogue de bordeaux

For more details

Visit the detailed Jupyter Notebook: dog_app.ipynb