Network

network.py

from keras import models
from keras import layers

model = models.Sequential()

model.add(layers.Conv2D(
    filters=32,
    kernel_size=(3, 3),
    strides=(1, 1),
    padding='valid',
    activation='relu',
    input_shape=(150, 150, 3)
))
model.add(layers.MaxPool2D((2, 2)))

model.add(layers.Conv2D(
    filters=64,
    kernel_size=(3, 3),
    strides=(1, 1),
    padding='valid',
    activation='relu',
))
model.add(layers.MaxPool2D((2, 2)))

model.add(layers.Conv2D(
    filters=128,
    kernel_size=(3, 3),
    strides=(1, 1),
    padding='valid',
    activation='relu',
))
model.add(layers.MaxPool2D((2, 2)))

model.add(layers.Conv2D(
    filters=128,
    kernel_size=(3, 3),
    strides=(1, 1),
    padding='valid',
    activation='relu',
))
model.add(layers.MaxPool2D((2, 2)))

model.add(layers.Flatten())
model.add(layers.Dense(512, activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))