Spaces:
Paused
Paused
| from typing import Any | |
| import numpy as np | |
| import rembg | |
| import torch | |
| from PIL import Image | |
| import sf3d.models.utils as sf3d_utils | |
| def create_intrinsic_from_fov_deg(fov_deg: float, cond_height: int, cond_width: int): | |
| intrinsic = sf3d_utils.get_intrinsic_from_fov( | |
| np.deg2rad(fov_deg), | |
| H=cond_height, | |
| W=cond_width, | |
| ) | |
| intrinsic_normed_cond = intrinsic.clone() | |
| intrinsic_normed_cond[..., 0, 2] /= cond_width | |
| intrinsic_normed_cond[..., 1, 2] /= cond_height | |
| intrinsic_normed_cond[..., 0, 0] /= cond_width | |
| intrinsic_normed_cond[..., 1, 1] /= cond_height | |
| return intrinsic, intrinsic_normed_cond | |
| def default_cond_c2w(distance: float): | |
| c2w_cond = torch.as_tensor( | |
| [ | |
| [0, 0, 1, distance], | |
| [1, 0, 0, 0], | |
| [0, 1, 0, 0], | |
| [0, 0, 0, 1], | |
| ] | |
| ).float() | |
| return c2w_cond | |
| def remove_background( | |
| image: Image, | |
| rembg_session: Any = None, | |
| force: bool = False, | |
| **rembg_kwargs, | |
| ) -> Image: | |
| do_remove = True | |
| if image.mode == "RGBA" and image.getextrema()[3][0] < 255: | |
| do_remove = False | |
| do_remove = do_remove or force | |
| if do_remove: | |
| image = rembg.remove(image, session=rembg_session, **rembg_kwargs) | |
| return image | |
| def resize_foreground( | |
| image: Image, | |
| ratio: float, | |
| ) -> Image: | |
| image = np.array(image) | |
| assert image.shape[-1] == 4 | |
| alpha = np.where(image[..., 3] > 0) | |
| y1, y2, x1, x2 = ( | |
| alpha[0].min(), | |
| alpha[0].max(), | |
| alpha[1].min(), | |
| alpha[1].max(), | |
| ) | |
| # crop the foreground | |
| fg = image[y1:y2, x1:x2] | |
| # pad to square | |
| size = max(fg.shape[0], fg.shape[1]) | |
| ph0, pw0 = (size - fg.shape[0]) // 2, (size - fg.shape[1]) // 2 | |
| ph1, pw1 = size - fg.shape[0] - ph0, size - fg.shape[1] - pw0 | |
| new_image = np.pad( | |
| fg, | |
| ((ph0, ph1), (pw0, pw1), (0, 0)), | |
| mode="constant", | |
| constant_values=((0, 0), (0, 0), (0, 0)), | |
| ) | |
| # compute padding according to the ratio | |
| new_size = int(new_image.shape[0] / ratio) | |
| # pad to size, double side | |
| ph0, pw0 = (new_size - size) // 2, (new_size - size) // 2 | |
| ph1, pw1 = new_size - size - ph0, new_size - size - pw0 | |
| new_image = np.pad( | |
| new_image, | |
| ((ph0, ph1), (pw0, pw1), (0, 0)), | |
| mode="constant", | |
| constant_values=((0, 0), (0, 0), (0, 0)), | |
| ) | |
| new_image = Image.fromarray(new_image, mode="RGBA") | |
| return new_image | |