def get_distance(im1, im2):
    K.clear_session()
    model = deep_rank_model()
    K.clear_session()
    # for layer in model.layers:
    #     print (layer.name, layer.output_shape)
    K.clear_session()
    model.load_weights("./deepranking.h5")
    K.clear_session()
    image1 = Image.open(urlopen(im1))

    # image1 = load_img(im1)
    image1 = img_to_array(image1).astype("float64")
    image1 = transform.resize(image1, (224, 224))
    image1 *= 1. / 255
    image1 = np.expand_dims(image1, axis=0)

    embedding1 = model.predict([image1, image1, image1])[0]

    image2 = Image.open(urlopen(im2))

    # image2 = load_img(im2)
    image2 = img_to_array(image2).astype("float64")
    image2 = transform.resize(image2, (224, 224))
    image2 *= 1. / 255
    image2 = np.expand_dims(image2, axis=0)

    embedding2 = model.predict([image2, image2, image2])[0]

    distance = sum([(embedding1[idx] - embedding2[idx]) ** 2 for idx in range(len(embedding1))]) ** 0.5

    print(distance)
    return distance