| from PIL import Image | |
| import numpy as np | |
| import torch | |
| from .view_base import BaseView | |
| class NegateView(BaseView): | |
| def __init__(self): | |
| pass | |
| def view(self, im): | |
| return -im | |
| def inverse_view(self, noise): | |
| ''' | |
| Negating the variance estimate is "weird" so just don't do it. | |
| This hack seems to work just fine | |
| ''' | |
| invert_mask = torch.ones_like(noise) | |
| invert_mask[:3] = -1 | |
| return noise * invert_mask | |
| def make_frame(self, im, t): | |
| im_size = im.size[0] | |
| frame_size = int(im_size * 1.5) | |
| # map t from [0, 1] -> [1, -1] | |
| t = 1 - t | |
| t = t * 2 - 1 | |
| # Interpolate from pixels from [0, 1] to [1, 0] | |
| im = np.array(im) / 255. | |
| im = ((2 * im - 1) * t + 1) / 2. | |
| im = Image.fromarray((im * 255.).astype(np.uint8)) | |
| # Paste on to canvas | |
| frame = Image.new('RGB', (frame_size, frame_size), (255, 255, 255)) | |
| frame.paste(im, ((frame_size - im_size) // 2, (frame_size - im_size) // 2)) | |
| return frame | |