Capstone project for Machine Learning Engineer Nanodegree program on Udacity. Given an image of a dog, the algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
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Clone the original 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
NOTE: if you are using the Udacity workspace, you DO NOT need to re-download the datasets in steps 2 and 3 - they can be found in the /data folder as noted within the workspace Jupyter notebook.
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Download the dog dataset. Unzip the folder and place it in the repo, at location
path/to/dog-project/dogImages. ThedogImages/folder should contain 133 folders, each corresponding to a different dog breed. -
Download the human dataset. Unzip the folder and place it in the repo, at location
path/to/dog-project/lfw. If you are using a Windows machine, you are encouraged to use 7zip to extract the folder. -
Make sure you have already installed the necessary Python packages according to the README in the program repository.
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Open a terminal window and navigate to the project folder. Open the notebook and follow the instructions.
jupyter notebook dog_app.ipynb