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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 SevenScenes(BaseManyViewDataset):
def __init__(self, num_seq=1, num_frames=5,
min_thresh=10, max_thresh=100,
test_id=None, full_video=False,
tuple_path=None, seq_id=None,
kf_every=1, *args, ROOT, **kwargs):
self.ROOT = ROOT
super().__init__(*args, **kwargs)
self.num_seq = num_seq
self.num_frames = num_frames
self.max_thresh = max_thresh
self.min_thresh = min_thresh
self.test_id = test_id
self.full_video = full_video
self.kf_every = kf_every
self.seq_id = seq_id
# load all scenes
self.load_all_tuples(tuple_path)
self.load_all_scenes(ROOT)
def __len__(self):
if self.tuple_list is not None:
return len(self.tuple_list)
return len(self.scene_list) * self.num_seq
def load_all_tuples(self, tuple_path):
if tuple_path is not None:
with open(tuple_path) as f:
self.tuple_list = f.read().splitlines()
else:
self.tuple_list = None
def load_all_scenes(self, base_dir):
if self.tuple_list is not None:
# Use pre-defined simplerecon scene_ids
self.scene_list = ['stairs/seq-06', 'stairs/seq-02',
'pumpkin/seq-06', 'chess/seq-01',
'heads/seq-02', 'fire/seq-02',
'office/seq-03', 'pumpkin/seq-03',
'redkitchen/seq-07', 'chess/seq-02',
'office/seq-01', 'redkitchen/seq-01',
'fire/seq-01']
print(f"Found {len(self.scene_list)} sequences in split {self.split}")
return
scenes = os.listdir(base_dir)
file_split = {'train': 'TrainSplit.txt', 'test': 'TestSplit.txt'}[self.split]
self.scene_list = []
for scene in scenes:
if self.test_id is not None and scene != self.test_id:
continue
# read file split
with open(osp.join(base_dir, scene, file_split)) as f:
seq_ids = f.read().splitlines()
for seq_id in seq_ids:
# seq is string, take the int part and make it 01, 02, 03
# seq_id = 'seq-{:2d}'.format(int(seq_id))
num_part = ''.join(filter(str.isdigit, seq_id))
seq_id = f'seq-{num_part.zfill(2)}'
if self.seq_id is not None and seq_id != self.seq_id:
continue
self.scene_list.append(f"{scene}/{seq_id}")
print(f"Found {len(self.scene_list)} sequences in split {self.split}")
def _get_views(self, idx, resolution, rng):
if self.tuple_list is not None:
line = self.tuple_list[idx].split(" ")
scene_id = line[0]
img_idxs = line[1:]
else:
scene_id = self.scene_list[idx // self.num_seq]
seq_id = idx % self.num_seq
data_path = osp.join(self.ROOT, scene_id)
num_files = len([name for name in os.listdir(data_path) if 'color' in name])
img_idxs = [f'{i:06d}' for i in range(num_files)]
img_idxs = self.sample_frame_idx(img_idxs, rng, full_video=self.full_video)
# Intrinsics used in SimpleRecon
fx, fy, cx, cy = 525, 525, 320, 240
intrinsics_ = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]], dtype=np.float32)
views = []
imgs_idxs = deque(img_idxs)
while len(imgs_idxs) > 0:
im_idx = imgs_idxs.popleft()
impath = osp.join(self.ROOT, scene_id, f'frame-{im_idx}.color.png')
depthpath = osp.join(self.ROOT, scene_id, f'frame-{im_idx}.depth.proj.png')
posepath = osp.join(self.ROOT, scene_id, f'frame-{im_idx}.pose.txt')
rgb_image = imread_cv2(impath)
depthmap = imread_cv2(depthpath, cv2.IMREAD_UNCHANGED)
rgb_image = cv2.resize(rgb_image, (depthmap.shape[1], depthmap.shape[0]))
depthmap[depthmap==65535] = 0
depthmap = np.nan_to_num(depthmap.astype(np.float32), 0.0) / 1000.0
depthmap[depthmap>10] = 0
depthmap[depthmap<1e-3] = 0
camera_pose = np.loadtxt(posepath).astype(np.float32)
rgb_image, depthmap, intrinsics = self._crop_resize_if_necessary(
rgb_image, depthmap, intrinsics_, resolution, rng=rng, info=impath)
views.append(dict(
img=rgb_image,
depthmap=depthmap,
camera_pose=camera_pose,
camera_intrinsics=intrinsics,
dataset='7scenes',
label=osp.join(scene_id, im_idx),
instance=osp.split(impath)[1],
))
return views
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