1 min to read
Cats vs Dogs Classifier
A Convolutional Neural Networks (CNN) implementation of cats and dogs’ image classifier.
Model: "sequential_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 62, 62, 32) 896
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 31, 31, 32) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 29, 29, 32) 9248
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 14, 14, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 6272) 0
_________________________________________________________________
dense_1 (Dense) (None, 128) 802944
_________________________________________________________________
dense_2 (Dense) (None, 1) 129
=================================================================
Total params: 813,217
Trainable params: 813,217
Non-trainable params: 0
_________________________________________________________________
Optimizer: ‘Adam’
Image Augmentation: to add more variety in the dataset, some augmentation has been done. Augmentations like shearing, zooming and flipping have been done.
Check out the whole project as notebook here.
If you liked this project, please consider buying me a coffee
Comments