CATS vs DOGS Classification using Convolutional Neural Networks and Data Augmentation

Dataset Details

you can download dataset from google apis.

Dataset Description

Dataset contain 3000 images of Cats and Dogs, we will train our model on 1700 images,710 images for validation and 604 images for testing.

Training Images of cats = 850
Training Images of dogs = 850

Validation Images of Cats = 352
Validation Images of Dogs = 358

Testing Images of Cats = 304
Testing Images of Dogs = 300

Overfiting and Underfitting aviodence Techniques Used

1-Data Augmentation (zoom,horizontal_flip,rotation)
2-Dropout

Model Summary

I used convolutional neural networks with 32, 64 and 128 layers.


Training and Validation Graph:

Results

Achieved 84% Accuracy on Training data with epochs = 100
81% accuracy on validation data
80% accuracy on testing data