Dog-vs-Cat-image-classification

This is simple mini project which predicts image of dog or cat with the help of machine learning algorithm called Convolution Neural Network (CNN).

The idea was taken from https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition

Model Implementation

This is simple model which uses 2 conv layer, 2 Maxpool layer and 2 Fully connected layers at the last.

Layer Sequence

[Input (64, 64, 3)] -> [Conv (128)] -> [Pool]  ->[Conv (128)] -> [Pool]  ->  [Full (128)] -> [Full (1)] -> [Output]

• Convolution layer Filter size = 3 X 3
• Max pool uses size of 2 X 2
• learning rate = 0.001
• dropout = 0.2 from prevent overfitting
• no_of_epochs = 50
• train_test_split = 80%-20%

-> Total time taken 25.48 hours for entire program to execute. Laptop configuration is :

• Microsoft Windows 10
• GPU- Nvidia Geforce 940-MX(4GB)
• RAM - 4GB
• Processor - Intel Core i5 6200 @ 2.8 - 3.0 GHz
• Tensorlfow version = 1.7
• Keras use as tensorflow backend

Result

Loss : 0.2421 
Accuracy : 0.9526