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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 RE10K_Multi(BaseMultiViewDataset): | |
def __init__(self, *args, ROOT, **kwargs): | |
self.ROOT = ROOT | |
self.video = True | |
self.is_metric = False | |
self.max_interval = 128 | |
super().__init__(*args, **kwargs) | |
self.loaded_data = self._load_data() | |
def _load_data(self): | |
self.scenes = os.listdir(self.ROOT) | |
offset = 0 | |
scenes = [] | |
sceneids = [] | |
scene_img_list = [] | |
images = [] | |
start_img_ids = [] | |
j = 0 | |
for scene in tqdm(self.scenes): | |
scene_dir = osp.join(self.ROOT, scene) | |
rgb_dir = osp.join(scene_dir, "rgb") | |
basenames = sorted( | |
[f[:-4] for f in os.listdir(rgb_dir) if f.endswith(".png")], | |
key=lambda x: int(x), | |
) | |
num_imgs = len(basenames) | |
img_ids = list(np.arange(num_imgs) + offset) | |
cut_off = ( | |
self.num_views if not self.allow_repeat else max(self.num_views // 3, 3) | |
) | |
if num_imgs < cut_off: | |
print(f"Skipping {scene}") | |
continue | |
start_img_ids_ = img_ids[: num_imgs - cut_off + 1] | |
start_img_ids.extend([(scene, id) for id in start_img_ids_]) | |
sceneids.extend([j] * num_imgs) | |
images.extend(basenames) | |
scenes.append(scene) | |
scene_img_list.append(img_ids) | |
# offset groups | |
offset += num_imgs | |
j += 1 | |
self.scenes = scenes | |
self.sceneids = sceneids | |
self.images = images | |
self.start_img_ids = start_img_ids | |
self.scene_img_list = scene_img_list | |
self.invalid_scenes = {scene: False for scene in self.scenes} | |
def __len__(self): | |
return len(self.start_img_ids) | |
def get_image_num(self): | |
return len(self.images) | |
def _get_views(self, idx, resolution, rng, num_views): | |
invalid_seq = True | |
scene, start_id = self.start_img_ids[idx] | |
while invalid_seq: | |
while self.invalid_scenes[scene]: | |
idx = rng.integers(low=0, high=len(self.start_img_ids)) | |
scene, start_id = self.start_img_ids[idx] | |
all_image_ids = self.scene_img_list[self.sceneids[start_id]] | |
pos, ordered_video = self.get_seq_from_start_id( | |
num_views, start_id, all_image_ids, rng, max_interval=self.max_interval | |
) | |
image_idxs = np.array(all_image_ids)[pos] | |
views = [] | |
for view_idx in image_idxs: | |
scene_id = self.sceneids[view_idx] | |
scene_dir = osp.join(self.ROOT, self.scenes[scene_id]) | |
rgb_dir = osp.join(scene_dir, "rgb") | |
cam_dir = osp.join(scene_dir, "cam") | |
basename = self.images[view_idx] | |
try: | |
# Load RGB image | |
rgb_image = imread_cv2(osp.join(rgb_dir, basename + ".png")) | |
# Load depthmap, no depth, set to all ones | |
depthmap = np.ones_like(rgb_image[..., 0], dtype=np.float32) | |
cam = np.load(osp.join(cam_dir, basename + ".npz")) | |
intrinsics = cam["intrinsics"] | |
camera_pose = cam["pose"] | |
except: | |
print(f"Error loading {scene} {basename}, skipping") | |
self.invalid_scenes[scene] = True | |
break | |
rgb_image, depthmap, intrinsics = self._crop_resize_if_necessary( | |
rgb_image, depthmap, intrinsics, resolution, rng=rng, info=view_idx | |
) | |
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="realestate10k", | |
label=self.scenes[scene_id] + "_" + basename, | |
instance=f"{str(idx)}_{str(view_idx)}", | |
is_metric=self.is_metric, | |
is_video=ordered_video, | |
quantile=np.array(0.98, dtype=np.float32), | |
img_mask=True, | |
ray_mask=False, | |
camera_only=True, | |
depth_only=False, | |
single_view=False, | |
reset=False, | |
) | |
) | |
if len(views) == num_views: | |
invalid_seq = False | |
return views | |