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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 | |
import re | |
def extract_number(filename): | |
match = re.search(r"\d+", filename) | |
if match: | |
return int(match.group()) | |
return 0 | |
class UASOL_Multi(BaseMultiViewDataset): | |
def __init__(self, *args, ROOT, **kwargs): | |
self.ROOT = ROOT | |
self.video = True | |
self.is_metric = True | |
self.max_interval = 40 | |
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=extract_number, | |
) | |
num_imgs = len(basenames) | |
img_ids = list(np.arange(num_imgs) + offset) | |
# start_img_ids_ = img_ids[:-self.num_views+1] | |
cut_off = ( | |
self.num_views if not self.allow_repeat else max(self.num_views // 3, 3) | |
) | |
start_img_ids_ = img_ids[: num_imgs - cut_off + 1] | |
if num_imgs < cut_off: | |
print(f"Skipping {scene}") | |
continue | |
start_img_ids.extend(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 | |
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): | |
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, | |
video_prob=0.75, | |
fix_interval_prob=0.75, | |
) | |
image_idxs = np.array(all_image_ids)[pos] | |
views = [] | |
for v, view_idx in enumerate(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") | |
depth_dir = osp.join(scene_dir, "depth") | |
cam_dir = osp.join(scene_dir, "cam") | |
basename = self.images[view_idx] | |
# Load RGB image | |
rgb_image = imread_cv2(osp.join(rgb_dir, basename + ".png")) | |
# Load depthmap | |
depthmap = np.load(osp.join(depth_dir, basename + ".npy")) | |
depthmap[~np.isfinite(depthmap)] = 0 # invalid | |
depthmap[depthmap >= 20] = 0 # invalid | |
cam = np.load(osp.join(cam_dir, basename + ".npz")) | |
camera_pose = cam["pose"] | |
intrinsics = cam["intrinsics"] | |
rgb_image, depthmap, intrinsics = self._crop_resize_if_necessary( | |
rgb_image, depthmap, intrinsics, resolution, rng=rng, info=view_idx | |
) | |
# generate img mask and raymap mask | |
img_mask, ray_mask = self.get_img_and_ray_masks( | |
self.is_metric, v, rng, p=[0.75, 0.2, 0.05] | |
) | |
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="UASOL", | |
label=self.scenes[scene_id] + "_" + basename, | |
instance=osp.join(rgb_dir, basename + ".png"), | |
is_metric=self.is_metric, | |
is_video=ordered_video, | |
quantile=np.array(0.9, dtype=np.float32), | |
img_mask=img_mask, | |
ray_mask=ray_mask, | |
camera_only=False, | |
depth_only=False, | |
single_view=False, | |
reset=False, | |
) | |
) | |
assert len(views) == num_views | |
return views | |