Image Classifier

Python Jupyter Notebook with Convolutional Neural Network image classifier implemented in Keras 🖼️. It's Google Colab ready.

Check out corresponding Medium article:

Image Classifier - Cats🐱 vs Dogs🐶 with Convolutional Neural Networks (CNNs) and Google Colab’s Free GPU

Usage

Structure your data as follows:

data/
	training/
		class_a/
			class_a01.jpg
			class_a02.jpg
			...
		class_b/
			class_b01.jpg
			class_b02.jpg
			...
	validation/
		class_a/
			class_a01.jpg
			class_a02.jpg
			...
		class_b/
			class_b01.jpg
			class_b02.jpg
			...

For binary classifications you are good to go!

For non-binary classifications:

add other classes to training and validation directories
change class_mode from "binary" to "categorical"
change loss function from "binary_crossentropy" to "categorical_crossentropy"

Performance

Dataset: Dogs vs Cats

Description: Binary classification. Two classes two distinguish - dogs and cats.

Training: 10 000 images per class

Validation: 2 500 images per class

model_1

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_5 (Conv2D)            (None, 198, 198, 32)      896       
_________________________________________________________________
activation_9 (Activation)    (None, 198, 198, 32)      0         
_________________________________________________________________
max_pooling2d_5 (MaxPooling2 (None, 99, 99, 32)        0         
_________________________________________________________________
conv2d_6 (Conv2D)            (None, 97, 97, 32)        9248      
_________________________________________________________________
activation_10 (Activation)   (None, 97, 97, 32)        0         
_________________________________________________________________
max_pooling2d_6 (MaxPooling2 (None, 48, 48, 32)        0         
_________________________________________________________________
flatten_3 (Flatten)          (None, 73728)             0         
_________________________________________________________________
dense_5 (Dense)              (None, 16)                1179664   
_________________________________________________________________
activation_11 (Activation)   (None, 16)                0         
_________________________________________________________________
dropout_3 (Dropout)          (None, 16)                0         
_________________________________________________________________
dense_6 (Dense)              (None, 1)                 17        
_________________________________________________________________
activation_12 (Activation)   (None, 1)                 0         
=================================================================
Total params: 1,189,825
Trainable params: 1,189,825
Non-trainable params: 0
_________________________________________________________________

model_2

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_4 (Conv2D)            (None, 198, 198, 32)      896       
_________________________________________________________________
activation_6 (Activation)    (None, 198, 198, 32)      0         
_________________________________________________________________
max_pooling2d_4 (MaxPooling2 (None, 99, 99, 32)        0         
_________________________________________________________________
conv2d_5 (Conv2D)            (None, 97, 97, 32)        9248      
_________________________________________________________________
activation_7 (Activation)    (None, 97, 97, 32)        0         
_________________________________________________________________
max_pooling2d_5 (MaxPooling2 (None, 48, 48, 32)        0         
_________________________________________________________________
conv2d_6 (Conv2D)            (None, 46, 46, 64)        18496     
_________________________________________________________________
activation_8 (Activation)    (None, 46, 46, 64)        0         
_________________________________________________________________
max_pooling2d_6 (MaxPooling2 (None, 23, 23, 64)        0         
_________________________________________________________________
flatten_2 (Flatten)          (None, 33856)             0         
_________________________________________________________________
dense_3 (Dense)              (None, 64)                2166848   
_________________________________________________________________
activation_9 (Activation)    (None, 64)                0         
_________________________________________________________________
dropout_2 (Dropout)          (None, 64)                0         
_________________________________________________________________
dense_4 (Dense)              (None, 1)                 65        
_________________________________________________________________
activation_10 (Activation)   (None, 1)                 0         
=================================================================
Total params: 2,195,553
Trainable params: 2,195,553
Non-trainable params: 0
_________________________________________________________________

model_3

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_4 (Conv2D)            (None, 198, 198, 32)      896       
_________________________________________________________________
activation_6 (Activation)    (None, 198, 198, 32)      0         
_________________________________________________________________
max_pooling2d_4 (MaxPooling2 (None, 99, 99, 32)        0         
_________________________________________________________________
conv2d_5 (Conv2D)            (None, 97, 97, 64)        18496     
_________________________________________________________________
activation_7 (Activation)    (None, 97, 97, 64)        0         
_________________________________________________________________
max_pooling2d_5 (MaxPooling2 (None, 48, 48, 64)        0         
_________________________________________________________________
conv2d_6 (Conv2D)            (None, 46, 46, 128)       73856     
_________________________________________________________________
activation_8 (Activation)    (None, 46, 46, 128)       0         
_________________________________________________________________
max_pooling2d_6 (MaxPooling2 (None, 23, 23, 128)       0         
_________________________________________________________________
flatten_2 (Flatten)          (None, 67712)             0         
_________________________________________________________________
dense_3 (Dense)              (None, 64)                4333632   
_________________________________________________________________
activation_9 (Activation)    (None, 64)                0         
_________________________________________________________________
dropout_2 (Dropout)          (None, 64)                0         
_________________________________________________________________
dense_4 (Dense)              (None, 1)                 65        
_________________________________________________________________
activation_10 (Activation)   (None, 1)                 0         
=================================================================
Total params: 4,426,945
Trainable params: 4,426,945
Non-trainable params: 0
_________________________________________________________________

model_4

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_7 (Conv2D)            (None, 198, 198, 32)      896       
_________________________________________________________________
activation_11 (Activation)   (None, 198, 198, 32)      0         
_________________________________________________________________
max_pooling2d_7 (MaxPooling2 (None, 99, 99, 32)        0         
_________________________________________________________________
conv2d_8 (Conv2D)            (None, 97, 97, 64)        18496     
_________________________________________________________________
activation_12 (Activation)   (None, 97, 97, 64)        0         
_________________________________________________________________
max_pooling2d_8 (MaxPooling2 (None, 48, 48, 64)        0         
_________________________________________________________________
conv2d_9 (Conv2D)            (None, 46, 46, 128)       73856     
_________________________________________________________________
activation_13 (Activation)   (None, 46, 46, 128)       0         
_________________________________________________________________
max_pooling2d_9 (MaxPooling2 (None, 23, 23, 128)       0         
_________________________________________________________________
flatten_3 (Flatten)          (None, 67712)             0         
_________________________________________________________________
dense_5 (Dense)              (None, 128)               8667264   
_________________________________________________________________
activation_14 (Activation)   (None, 128)               0         
_________________________________________________________________
dropout_3 (Dropout)          (None, 128)               0         
_________________________________________________________________
dense_6 (Dense)              (None, 1)                 129       
_________________________________________________________________
activation_15 (Activation)   (None, 1)                 0         
=================================================================
Total params: 8,760,641
Trainable params: 8,760,641
Non-trainable params: 0
_________________________________________________________________

model_5

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_1 (Conv2D)            (None, 200, 200, 32)      896       
_________________________________________________________________
conv2d_2 (Conv2D)            (None, 200, 200, 32)      9248      
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 100, 100, 32)      0         
_________________________________________________________________
conv2d_3 (Conv2D)            (None, 100, 100, 64)      18496     
_________________________________________________________________
conv2d_4 (Conv2D)            (None, 100, 100, 64)      36928     
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 50, 50, 64)        0         
_________________________________________________________________
conv2d_5 (Conv2D)            (None, 50, 50, 128)       73856     
_________________________________________________________________
conv2d_6 (Conv2D)            (None, 50, 50, 128)       147584    
_________________________________________________________________
max_pooling2d_3 (MaxPooling2 (None, 25, 25, 128)       0         
_________________________________________________________________
conv2d_7 (Conv2D)            (None, 25, 25, 256)       295168    
_________________________________________________________________
conv2d_8 (Conv2D)            (None, 25, 25, 256)       590080    
_________________________________________________________________
max_pooling2d_4 (MaxPooling2 (None, 12, 12, 256)       0         
_________________________________________________________________
flatten_1 (Flatten)          (None, 36864)             0         
_________________________________________________________________
dense_1 (Dense)              (None, 256)               9437440   
_________________________________________________________________
dropout_1 (Dropout)          (None, 256)               0         
_________________________________________________________________
dense_2 (Dense)              (None, 256)               65792     
_________________________________________________________________
dropout_2 (Dropout)          (None, 256)               0         
_________________________________________________________________
dense_3 (Dense)              (None, 1)                 257       
_________________________________________________________________
activation_1 (Activation)    (None, 1)                 0         
=================================================================
Total params: 10,675,745
Trainable params: 10,675,745
Non-trainable params: 0
_________________________________________________________________