Comments (5)
Colmap is little tricky. If it says that it cannot do things... is is usualy your fault. Datasets need to be prepared in specific ways that help colmap and don't disturb it. Not knowing how to take pictures is first sin. :)
This is not that hard.
About your dataset.
- Sharp images (picture size with full HD and above will be ok)
- Sharp images with great image depth
- Sharp images... ok ok :)
- Do not remove background - any surface with lots of details give more points to trace
(also this help if your object is 'thin' at one axis) - Do few more orbits with your objects with different heights and angle.
- 15-20 degree picture to picture is ok (as you take in your dataset)
Usualy 50 pic is at low end to make something, above 400 introduce noise and it can be diffictult cus GPU VRAM limitations.
Learn your lessons, be smart and GL.
from gaussian-splatting.
Colmap is little tricky. If it says that it cannot do things... is is usualy your fault. Datasets need to be prepared in specific ways that help colmap and don't disturb it. Not knowing how to take pictures is first sin. :)
This is not that hard.
About your dataset.
- Sharp images (picture size with full HD and above will be ok)
- Sharp images with great image depth
- Sharp images... ok ok :)
- Do not remove background - any surface with lots of details give more points to trace
(also this help if your object is 'thin' at one axis)- Do few more orbits with your objects with different heights and angle.
- 15-20 degree picture to picture is ok (as you take in your dataset)
Usualy 50 pic is at low end to make something, above 400 introduce noise and it can be diffictult cus GPU VRAM limitations.
Learn your lessons, be smart and GL.
Thank you for your answer! I will try according to your suggestion. I also have a problem, that is, the back and side of the teddy bear I generated appear this error
"=> Could not register, trying another image."
Is it because there are too few feature points to collect on the back? It is difficult for me to increase the feature points on the back.Do you have a solution to this problem?
from gaussian-splatting.
AI images have flaws. They don't have consistency in the tiny details and colmap need this for catching what is going there. So... bad luck for now.
But if you know photoshop(something) and 3D software like Blender there can still be a way.
Some work is included ;)
- Make alpha chanell on your images (at photosomething)
- Put simple scene in 3D software
- at centre your image
- at bottom any high detailed texture or reference points (this will be main horse for colmap)
- set camera that corespond to you image
- Make render, change image, set camera and repeat ;) (you simulate turn table)
Now colmap should have a lot of solid data to proceed with your new renders.
GL
from gaussian-splatting.
AI images have flaws. They don't have consistency in the tiny details and colmap need this for catching what is going there. So... bad luck for now. But if you know photoshop(something) and 3D software like Blender there can still be a way. Some work is included ;)
- Make alpha chanell on your images (at photosomething)
- Put simple scene in 3D software
- at centre your image
- at bottom any high detailed texture or reference points (this will be main horse for colmap)
- set camera that corespond to you image
- Make render, change image, set camera and repeat ;) (you simulate turn table)
Now colmap should have a lot of solid data to proceed with your new renders. GL
This is the second time you have helped me. Thank you very much! You are really professional and enthusiastic. I will try according to what you said. :)
from gaussian-splatting.
from gaussian-splatting.
Related Issues (20)
- Question About Convert.py and CPU Offloading HOT 4
- GSplat Point Cloud Only Trained from 3 images HOT 2
- fatal error: torch/extension.h: 没有那个文件或目录 HOT 2
- Issue on local setup HOT 1
- How do we get association between image and a splat? HOT 1
- Training with mask HOT 1
- Question about 3D covariance matrix calculation HOT 6
- Any example to support fp16 in GS?
- About your paper HOT 1
- How to get the lpips?
- about SIBR_Viewer question
- difference between "padded_grad" and "torch.norm(grads, dim=-1)" when perform densification HOT 2
- Rasterization - radii meaning HOT 1
- Question About Discontinuous Color HOT 1
- Questions on Installation of simple_knn HOT 5
- ask for 啊
- ask for a generated ply file HOT 3
- Question about the result of: dSigma_dM = 2 * M HOT 3
- why colmap version is 3.0.14 and i can't run pyhton convert.py -s code HOT 3
- Question about dL_dmean in backward.cu HOT 2
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from gaussian-splatting.