Cat vs. Dog Image Classifier

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PROJECT OVERVIEW

Image classifier trained to distinct between cats and dogs images. Convolutional Neural Network was built with Keras & Tensorflow(GPU). Heroku-hosted web application was built with Flask framework.

Kaggle Dataset

CONVOLUTIONAL NEURAL NETWORK CHARACTERISTICS

1. Image Input Shape - 128,128,3, activation - relu
2. Three additional Convolutional Layers (batch size - respectively 32,64,128, dropout rate - 0.25,0.2,0.3)
3. Units in hidden layer - 128
4. Compiler - optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy']
5. Acc - 89% Loss - 25% (approx 30min/epoch on GPU)
6. CNN Code Location: deep_learning/ConvolutionalNeuralNetwork.py

TOOLS, MODULES & TECHNIQUES:

Travis CI

Python – web development:

Flask

Python – CNN:

keras | tensorflow | scikit-image | pandas | numpy | h5py

Web Development:

HTML | CSS | Bootstrap | Materialize

Thank you,

Lukasz Malucha