import keras
import numpy as np
import sys
import cv2
from keras.utils import np_utils
from keras.datasets import mnist
from keras.models import load_model, Model
from keras.layers import Conv2D, MaxPooling2D
from keras.preprocessing.image import img_to_array, load_img
from keras.preprocessing import image
import matplotlib.pyplot as plt

name = 'img.jpg'

model = load_model('catsvsdogs_saved/cvd')
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
img = load_img(name, target_size=(150,150))
img_plot = load_img(name)

x = img_to_array(img)
x /= 255
x = np.expand_dims(x, axis=0)

img_class = model.predict_classes(x)
img_d = model.predict(x)

print(img_class)
print(img_d)

cs = ''
if img_class[0][0] == 0:
    cs = 'кот'
    img_d[0][0] = 1 - img_d[0][0]
else:
    cs = 'пёс'

plt.imshow(img_plot)
plt.title('Я думаю, что это ' + cs + ' (' + str(int(img_d[0][0]*100)) + '%)')
plt.show()