import tensorflow.keras as keras
from PIL import Image
import numpy as np
import ipdb

class g:
    def __init__(self, path):
        self.image = np.asarray(Image.open(path).convert('RGB').resize((100, 100))) / 255

    def show(self):
        self.image.show()

def predict(image1, image2):
    return model.predict([np.array([image2.image]), np.array([image1.image])]) 

model = keras.models.load_model('../siamese_100x100_pretrainedb_vgg16')
image1 = g('data/fruits/fruits-360/Training/Avocado/r_254_100.jpg')
image2 = g('data/fruits/fruits-360/Training/Avocado/r_250_100.jpg')

print(predict(image1, image2))

ipdb.set_trace()