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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 EDEN_Multi(BaseMultiViewDataset):
def __init__(self, *args, ROOT, **kwargs):
self.ROOT = ROOT
self.video = True
self.is_metric = True
super().__init__(*args, **kwargs)
self.loaded_data = self._load_data()
def _load_data(self):
scenes = os.listdir(self.ROOT)
img_names = []
for scene in 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")]
)
img_names.extend([(scene, basename) for basename in basenames])
self.img_names = img_names
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.permutation(self.img_names)
views = []
i = 0
while len(views) < num_views:
# Load RGB image
scene, img_name = img_names[i]
try:
rgb_image = imread_cv2(
osp.join(self.ROOT, scene, "rgb", f"{img_name}.png")
)
depthmap = np.load(
osp.join(self.ROOT, scene, "depth", f"{img_name}.npy")
)
depthmap = np.nan_to_num(depthmap, nan=0, posinf=0, neginf=0)
intrinsics = np.load(
osp.join(self.ROOT, scene, "cam", f"{img_name}.npz")
)["intrinsics"]
# camera pose is not provided, placeholder
camera_pose = np.eye(4)
except:
i += 1
continue
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="EDEN",
label=img_name,
instance=osp.join(self.ROOT, scene, "rgb", f"{img_name}.png"),
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,
)
)
i += 1
return views
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