application_vnd.jupyter.stderr_output_2.png text_plain_output_1.png
from efficientnet import EfficientNetB5

from keras.layers import Dense, Dropout, GlobalAveragePooling2D, LeakyReLU

from keras.models import Model, Sequential

import os

import sys

import numpy as np
import pandas as pd
import cv2
import os
import sys

sys.path.append(os.path.abspath('../input/efficientnet/efficientnet-master/efficientnet-master/'))
from efficientnet import EfficientNetB5
from keras.layers import Dense, Dropout, GlobalAveragePooling2D, LeakyReLU
from keras.models import Model, Sequential
def create_effnetB5_model(input_shape, n_out):
    base_model = EfficientNetB5(weights=None, include_top=False, input_shape=input_shape)
    model = Sequential()
    model.add(base_model)
    model.add(Dropout(0.25))
    model.add(Dense(1024))
    model.add(LeakyReLU())
    model.add(GlobalAveragePooling2D())
    model.add(Dropout(0.5))
    model.add(Dense(n_out, activation='sigmoid'))
    return model