hello I am using your wonderful dataset for Bundle Adjustment Experiment.
This is the part of my code to make point cloud from Pytorch 3D and I used CO3D dataset.
sequence_dataset = torch.utils.data.Subset(dataset, sequence_entries)
# load the required part of the dataset
loader = torch.utils.data.DataLoader(
sequence_dataset,
batch_size=1,
shuffle=False,
num_workers=10,
collate_fn=dataset.frame_data_type.collate,
)
image_path=[]
depth_path=[]
R_T_lst=[]
K_lst=[]
for frame_data in loader:
image_path.append(frame_data.image_path[0])
depth_path.append(frame_data.depth_path[0])
R,T,K=opencv_from_cameras_projection(frame_data.camera, frame_data.image_size_hw)
point_cloud=get_rgbd_point_cloud(frame_data.camera,frame_data.image_rgb,frame_data.depth_map)
After I make Point cloud I measure the mean value of Z (the depth) But I got 4 or 5 so on. Is that real depth distance (m?) If the depth is not correct, I can't use your dataset for research.
Hi. The depth maps are outputs of SfM reconstruction and, as such, cannot be in metric units ( meters). Regardless they are perfectly correct but not in human units.
hello I am using your wonderful dataset for Bundle Adjustment Experiment.
This is the part of my code to make point cloud from Pytorch 3D and I used CO3D dataset.
After I make Point cloud I measure the mean value of Z (the depth) But I got 4 or 5 so on. Is that real depth distance (m?) If the depth is not correct, I can't use your dataset for research.