In this project, 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.
In this project, we can explore the state-of-the-art CNN models for classification and localization.
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Install Jupyter Notebook.
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Clone the repository and navigate to the downloaded folder.
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Download the dog dataset. Unzip the folder and place it in the repo, at location path/to/dog-project/dogImages. The dogImages/ folder should contain 133 folders, each corresponding to a different dog breed.
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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.
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Make sure you have already installed the necessary Python packages according to the
requirements.txtin the repository. -
Open a terminal window and navigate to the project folder. Open the notebook using:
jupyter notebook dog_app.ipynb
NOTE: If the code is taking too long to run, you will need to either reduce the complexity of thhe CNN architecture or switch to running the code on a GPU.