# 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()