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

def getI(path):
    return np.asarray(Image.open(path).convert('RGB').resize((100, 100))) / 255

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

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

print(predict(image1, image2))

pdb.set_trace()