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| -rw-r--r-- | models.py | 37 |
1 files changed, 37 insertions, 0 deletions
diff --git a/models.py b/models.py new file mode 100644 index 0000000..5a28b27 --- /dev/null +++ b/models.py @@ -0,0 +1,37 @@ +# models.py +# EE4 Computer vision coursework: Models for GAN coursework +from keras.models import Model, Sequential +from keras.layers import * + +def get_generator: + generator = Sequential([ + Dense(128*7*7, input_dim=100, activation=LeakyReLU(0.2)), + BatchNormalization(), + Reshape((7,7,128)), + UpSampling2D(), + Convolution2D(64, 5, 5, border_mode='same', activation=LeakyReLU(0.2)), + BatchNormalization(), + UpSampling2D(), + Convolution2D(1, 5, 5, border_mode='same', activation='tanh') + ]) + + discriminator = Sequential([ + Convolution2D(64, 5, 5, subsample=(2,2), input_shape=(28,28,1), border_mode='same', activation=LeakyReLU(0.2)), + Dropout(0.3), + Convolution2D(128, 5, 5, subsample=(2,2), border_mode='same', activation=LeakyReLU(0.2)), + Dropout(0.3), + Flatten(), + Dense(1, activation='sigmoid') + ]) + return generator + +def get_discriminator: + discriminator = Sequential([ + Convolution2D(64, 5, 5, subsample=(2,2), input_shape=(28,28,1), border_mode='same', activation=LeakyReLU(0.2)), + Dropout(0.3), + Convolution2D(128, 5, 5, subsample=(2,2), border_mode='same', activation=LeakyReLU(0.2)), + Dropout(0.3), + Flatten(), + Dense(1, activation='sigmoid') + ]) + return discriminator |