Comments (1)
m-niemeyer
commented on August 27, 2024
2
Please have a look at the readme on how to train a new model.
Our data structure has the format:
[ds_folder]
[class_0]
[class_1]
...
[class_n]
[obj_0]
[0bj_1]
...
[obj_m]
Each "obj_m" folder contains "camera.npz" and the subfolders "image", "mask", "visual_hull_depth" and/or "depth". You can see how the data is loaded and processed in the main image field.
Good luck with your research!
from differentiable_volumetric_rendering.
Related Issues (20)
- check_ray_intersection_with_unit_cube HOT 1
- How to prepare data for the model? HOT 3
- create dataset.
- Is it possible to have a scene-general model for multi-view reconstruction? HOT 1
- p_freespace in get_freespace_loss_points() and p_occupancy in get_occupancy_loss_points()？
- Why is the focal length different in your rendering and img_choy2016? HOT 4
- How to evaluate the chamfer distance for the DTU dataset? HOT 1
- Evaluation scores very low HOT 1
- Scale of point clouds in DTU datasets? HOT 1
- Test in ShapeNet with multi-view inputs
- check_ray_intersection_with_unit_cube bottlenecking CPU HOT 2
- Normalize ray_vector?
- A question about the 3.2Section of the paper HOT 1
- How to generate cameras.npz and pcl.npz for custom datasets? HOT 1
- download the data.
- Error generating mesh jpg when run demo
- Error in setup.py HOT 1
- size mismatch for decoder
- Where to download the pretrained models?
- How to get gif like your readme from a ply file? HOT 1
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from differentiable_volumetric_rendering.