In [13]:

    

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
from tensorflow.keras.applications.densenet import DenseNet121, preprocess_input
from dogcat_data import generators
from tensorflow.keras.models import load_model
import numpy as np
import matplotlib.pyplot as plt


    

In [14]:

    

train_generator, validation_generator = generators(preprocess_input, 224, 224, 9)

images, labels = next(validation_generator)
#print(images[0])
plt.rcParams['figure.figsize'] = (10,10)
for i in range(9):
    plt.subplot(3,3,i+1)
    plt.imshow((images[i] - np.min(images[i])) / np.ptp(images[i]), interpolation='none')
    plt.title("label {}".format(labels[i]))
    plt.axis('off')


    

    




Found 1800 images belonging to 2 classes.
Found 2000 images belonging to 2 classes.






    

In [ ]:

    

model = load_model('transfered.h5')