  We propose Image-Semantic-Transformation-Reconstruction-Circle(ISTRC) model,
a novel and powerful method using facenet's Euclidean latent space to
understand the images. As the name suggests, ISTRC construct the circle, able
to perfectly reconstruct images. One powerful Euclidean latent space embedded
in ISTRC is FaceNet's last layer with the power of distinguishing and
understanding images. Our model will reconstruct the images and manipulate
Euclidean latent vectors to achieve semantic transformations and semantic
images arthimetic calculations. In this paper, we show that ISTRC performs 10
high-level semantic transformations like "Male and female","add smile","open
mouth", "deduct beard or add mustache", "bigger/smaller nose", "make older and
younger", "bigger lips", "bigger eyes", "bigger/smaller mouths" and "more
attractive". It just takes 3 hours(GTX 1080) to train the models of 10 semantic
transformations.
