/DogsVsCatsRedux

Classifying images of cats and dogs with convolutional neural networks

Primary LanguageJupyter Notebook

Dog vs Cats

My experiments with the Kaggle competition Dogs vs Cats Redux. Project is structured as follows:

  • dataset.py: handles preprocessing and queueing of input data
  • bottleneck.py: handles preprocessing and queueing of Inception v4 bottlenecks
  • tfutil.py: a collection of helper functions for building, training and evaluating TensorFlow networks
  • DogsVsCats_Intro.ipynb: introduction, control and basic fully connected network (~66% on test set)
  • DogsVsCats_Conv.ipynb: convolutional network
  • DogsVsCats_Inception.ipynb: transfer learning with Google Inception v4
    • inception_v4.py, inception_utils.py: code to build Inception v4 network with TF-Slim, from TF-Slim models page

Setup

To work with this project, the data must be obtained from Kaggle and placed in data/raw. For transfer learning the Inception v4 checkpoint must also be downloaded and extracted into the project root.