traffic-accidents-model2-v1.py

# Building the first model iteration
model = models.Sequential()
model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(64 ,64,  3)))
model.add(layers.MaxPooling2D((2, 2)))

model.add(layers.Conv2D(32, (4, 4), activation='relu'))
model.add(layers.MaxPooling2D((2, 2)))

model.add(layers.Conv2D(64, (3, 3), activation='relu'))
model.add(layers.MaxPooling2D((2, 2)))

model.add(layers.Flatten())
model.add(layers.Dense(64, activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy', optimizer="sgd", metrics=['acc'])

# Training the model
history = model.fit(train_images,
                    train_labels,
                    epochs=10,
                    batch_size=32,
                    validation_data=(val_images, val_labels))