Function pgan

serving-ml-models/backend/model/pgan.py:17–26

()

num_images = 1

def pgan():
    noise, _ = model.buildNoiseData(num_images)
    with torch.no_grad():
        generated_images = model.test(noise)

    transform = Transforms.Compose([Transforms.Normalize((-1., -1., -1.), (2, 2, 2)),
                                    Transforms.ToPILImage()])
    generated_images = generated_images[0]
    generated_images = transform(generated_images.clamp(min=-1, max=1))
    return generated_images