# vgg16 = VGG16() # (None, 224, 224, 3)
# model = VGG19()
model = Xception()
model = ResNet101()
model = ResNet101V2()
model = ResNet152()
model = ResNet152V2()
model = ResNet50()
model = ResNet50V2()
model = InceptionV3()
model = InceptionResNetV2()
model = MobileNet()
model = MobileNetV2()
model = DenseNet121()
model = DenseNet169()
model = DenseNet201()
model = NASNetLarge()
model = NASNetMobile()
# vgg16.summary()
'''
model= Sequential()
# model.add(vgg16)
# model.add(Flatten())
model.add(Dense(256))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(Dense(10, activation='softmax'))
model.summary()
'''
model = DenseNet121()
model = DenseNet169()
model = DenseNet201()
model = NASNetLarge()
model = NASNetMobile()
vgg16 = VGG16(
weights=None,
include_top=False,
classes=10,
input_shape=(224, 224, 3),
# classifier_activation="softmax"
)
# (None, 224, 224, 3)
# 모델 다운 받아 와야함
vgg16.summary()
# 잘만든 모델 가져다 쓰는 거 = 전이학습
# 이미지 모델에서 준우승 한 모델
# VGG16이랑 엮기
model = Sequential()
model.add(vgg16)
model.add(Dense(256))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(Dense(10, activation='softmax'))
model.summary()
