text_plain_output_2.png application_vnd.jupyter.stderr_output_1.png
from keras.layers import Dense, Dropout, Flatten, Input, Conv2D, MaxPooling2D, BatchNormalization, Activation, UpSampling2D, GlobalAveragePooling2D

from keras.models import Sequential, Model

from tensorflow.keras.applications import EfficientNetB0

from tensorflow.keras.applications import EfficientNetB0
efnb0 = EfficientNetB0(weights='imagenet', include_top=False, input_shape=(224, 224, 3))
model = Sequential()
model.add(efnb0)
model.add(GlobalAveragePooling2D())
model.add(Dropout(0.2))
model.add(Dense(1024, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(512, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(4, activation='sigmoid'))
for layer in efnb0.layers:
    layer.trainable = False
model.summary()