age_detect_model.py

model=Sequential()
model.add(Conv2D(16,kernel_size=(3,3), activation="relu" ,input_shape=IMAGE_SIZE + [3], padding='same'))

model.add(Conv2D(32, kernel_size=(3,3), activation="relu",padding='same'))
model.add(BatchNormalization()) 
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Dropout(0.30))

model.add(Conv2D(64, kernel_size=(3,3), activation="relu",padding='same'))
#model.add(BatchNormalization()) 
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Dropout(0.35))

model.add(Conv2D(128, kernel_size=(3,3), activation="relu",padding='same'))
#model.add(MaxPooling2D(pool_size=(2,2)))
model.add(BatchNormalization()) 
model.add(Dropout(0.45))

model.add(Flatten())
model.add(Dense(64, activation="relu"))
model.add(Dense(num_classes, activation="softmax"))