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Author:: Raj Mehrotra
Date:: 25-08-2018
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The famous Cats-vs-Dogs dataset.
I have used a self laid ConvNet to classify the image into 2 classes either a Dog or a Cat.
The images used are of 100*100 pixels each. The images are first converted to the numpy array of pixel values using the python ZipFile module. The images are then divided into the training ,cross-validation,testing set containing 20000 , 5000 , 12500 images respectively. Also I have used data augmentation technique to avoid chances of overfitting the model.
Finally I achieved a decent accuracy of about 88 % on the validation set.