Welcome to my Udacity Machine Learning Engineer Nanodegree Capstone Project! This is a PyTorch Convolutional Neural Network (CNN) project that, given an image of a dog, the algorithm identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
There are two datasets used in this project, a Dog Image Dataset and a Human Image Datasets. Both are available for download here:
Dog Dataset. Unzip the folder and place it in main folder with the jupyter notebook, at location "/dogImages". The "/dogImages" folder should contain 133 folders, each corresponding to a different dog breed.
Human Dataset. Unzip the folder and place it in main folder with the jupyter notebook, at location "/lfw".
- /haarcascades Folder - OpenCV provides many pre-trained face detectors, stored as XML files on github. In this folder is one of these detectors used in the project to find human faces in images.
- dog_app.ipynb - This is the notebook where the entire project was made and tested. It needs access to both datasets in order to work properly.
- dog_app.pdf - The same notebook in pdf format.
- Proposal.pdf - This is the original document send to Udacity with the proposal of the project.
- Report.pdf - This is my final report, explaining the entire process from start to finish.
If you want to do the original project from scratch, clone the repository and navigate to the downloaded folder.
git clone https://github.com/udacity/deep-learning-v2-pytorch.git
cd deep-learning-v2-pytorch/project-dog-classification