ysharc/dog-breed-classifier

Classifying 133 dog breeds using transfer learning and CNN

Quick start

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

   	git clone https://github.com/ysharc/dog-breed-classifier.git
   	cd dog-breed-classifier
   

2. Download the dog dataset. Unzip the folder and place it in the repo, at location path/to/dog-project/dogImages.

3. 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.

4. Donwload the VGG-16 bottleneck features for the dog dataset. Place it in the repo, at location path/to/dog-project/bottleneck_features.

5. Obtain the necessary Python packages, and switch Keras backend to Tensorflow.

   For Mac/OSX:

   	conda env create -f requirements/aind-dog-mac.yml
   	source activate aind-dog
   	KERAS_BACKEND=tensorflow python -c "from keras import backend"
   

   For Linux:

   	conda env create -f requirements/aind-dog-linux.yml
   	source activate aind-dog
   	KERAS_BACKEND=tensorflow python -c "from keras import backend"
   

   For Windows:

   	conda env create -f requirements/aind-dog-windows.yml
   	activate aind-dog
   	set KERAS_BACKEND=tensorflow
   	python -c "from keras import backend"
   

6. Open the notebook and follow the instructions. I recommend running this with GPU support.

   	jupyter notebook dog_app.ipynb