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| import os.path as osp | |
| import cv2 | |
| import numpy as np | |
| import itertools | |
| import os | |
| import sys | |
| sys.path.append(osp.join(osp.dirname(__file__), "..", "..")) | |
| from tqdm import tqdm | |
| from dust3r.datasets.base.base_multiview_dataset import BaseMultiViewDataset | |
| from dust3r.utils.image import imread_cv2 | |
| class UrbanSyn(BaseMultiViewDataset): | |
| def __init__(self, *args, ROOT, **kwargs): | |
| self.ROOT = ROOT | |
| self.video = False | |
| self.is_metric = True | |
| super().__init__(*args, **kwargs) | |
| self.loaded_data = self._load_data() | |
| def _load_data(self): | |
| rgb_dir = osp.join(self.ROOT, "rgb") | |
| basenames = sorted([f[:-4] for f in os.listdir(rgb_dir) if f.endswith(".png")]) | |
| self.img_names = basenames | |
| def __len__(self): | |
| return len(self.img_names) | |
| def get_image_num(self): | |
| return len(self.img_names) | |
| def _get_views(self, idx, resolution, rng, num_views): | |
| new_seed = rng.integers(0, 2**32) + idx | |
| new_rng = np.random.default_rng(new_seed) | |
| img_names = new_rng.choice(self.img_names, num_views, replace=False) | |
| views = [] | |
| for img_name in img_names: | |
| # Load RGB image | |
| rgb_image = imread_cv2(osp.join(self.ROOT, "rgb", f"{img_name}.png")) | |
| depthmap = np.load(osp.join(self.ROOT, "depth", f"{img_name}.npy")) | |
| sky_mask = ( | |
| imread_cv2(osp.join(self.ROOT, "sky_mask", f"{img_name}.png"))[..., 0] | |
| >= 127 | |
| ) | |
| depthmap[sky_mask] = -1.0 | |
| depthmap = np.nan_to_num(depthmap, nan=0, posinf=0, neginf=0) | |
| depthmap[depthmap > 200] = 0.0 | |
| intrinsics = np.load(osp.join(self.ROOT, "cam", f"{img_name}.npz"))[ | |
| "intrinsics" | |
| ] | |
| # camera pose is not provided, placeholder | |
| camera_pose = np.eye(4) | |
| rgb_image, depthmap, intrinsics = self._crop_resize_if_necessary( | |
| rgb_image, depthmap, intrinsics, resolution, rng=rng, info=img_name | |
| ) | |
| views.append( | |
| dict( | |
| img=rgb_image, | |
| depthmap=depthmap.astype(np.float32), | |
| camera_pose=camera_pose.astype(np.float32), | |
| camera_intrinsics=intrinsics.astype(np.float32), | |
| dataset="urbansyn", | |
| label=img_name, | |
| instance=f"{str(idx)}_{img_name}", | |
| is_metric=self.is_metric, | |
| is_video=False, | |
| quantile=np.array(1.0, dtype=np.float32), | |
| img_mask=True, | |
| ray_mask=False, | |
| camera_only=False, | |
| depth_only=False, | |
| single_view=True, | |
| reset=True, | |
| ) | |
| ) | |
| assert len(views) == num_views | |
| return views | |