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import os
import cv2
import json
import numpy as np
import os.path as osp
from collections import deque
from dust3r.utils.image import imread_cv2
from .base_many_view_dataset import BaseManyViewDataset
class habitat(BaseManyViewDataset):
def __init__(self, num_seq=200, num_frames=5, *args, ROOT, **kwargs):
self.ROOT = ROOT
super().__init__(*args, **kwargs)
self.num_seq = num_seq
self.num_frames = num_frames
# load all scenes
self.load_all_scenes(ROOT, num_seq)
def __len__(self):
return len(self.scene_list) * self.num_seq
def load_all_scenes(self, base_dir, num_seq=200):
self.scenes = {}
data_all = os.listdir(base_dir)
print('All datasets in Habitat:', data_all)
for data in data_all:
scenes = os.listdir(osp.join(base_dir, data))
self.scenes[data] = scenes
self.scenes = {(k, v2): list(range(num_seq)) for k, v in self.scenes.items()
for v2 in v}
self.scene_list = list(self.scenes.keys())
def _get_views(self, idx, resolution, rng, attempts=0):
data, scene = self.scene_list[idx // self.num_seq]
seq_id = idx % self.num_seq
imgs_idxs_ = list(range(1, self.num_frames+1))
rng.shuffle(imgs_idxs_)
imgs_idxs = deque(imgs_idxs_)
views = []
while len(imgs_idxs) > 0:
im_idx = imgs_idxs.popleft()
impath = osp.join(self.ROOT, data, scene, f"{seq_id:08}_{im_idx}.jpeg")
depthpath = osp.join(self.ROOT, data, scene, f"{seq_id:08}_{im_idx}_depth.exr")
cam_params_path = osp.join(self.ROOT, data, scene, f"{seq_id:08}_{im_idx}_camera_params.json")
if not osp.exists(impath):
new_idx = rng.integers(0, self.__len__()-1)
return self._get_views(new_idx, resolution, rng)
rgb_image = imread_cv2(impath)
depthmap = imread_cv2(depthpath, cv2.IMREAD_UNCHANGED)
cam_params = json.load(open(cam_params_path, 'r'))
intrinsics_ = np.array(cam_params['camera_intrinsics'], dtype=np.float32)
# cam_r: [3, 3], cam_t: [3, ]
cam_r = np.array(cam_params['R_cam2world'], dtype=np.float32)
cam_t = np.array(cam_params['t_cam2world'], dtype=np.float32)
# camera_pose: [4, 4]
camera_pose = np.eye(4).astype(np.float32)
camera_pose[:3, :3] = cam_r
camera_pose[:3, 3] = cam_t
rgb_image, depthmap, intrinsics = self._crop_resize_if_necessary(
rgb_image, depthmap, intrinsics_, resolution, rng=rng, info=impath)
num_valid = (depthmap > 0.0).sum()
if num_valid == 0 or (not np.isfinite(camera_pose).all()):
if attempts >= 5:
new_idx = rng.integers(0, self.__len__()-1)
return self._get_views(new_idx, resolution, rng)
return self._get_views(idx, resolution, rng, attempts+1)
views.append(dict(
img=rgb_image,
depthmap=depthmap,
camera_pose=camera_pose,
camera_intrinsics=intrinsics,
dataset='habitat',
label=osp.join(data, scene),
instance=osp.split(impath)[1],
))
return views
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