if custom dataset, have trouble,then ...

[yuedajiong]

I have generated my dataset from video, and reconstruted a mesh successfully.
any question, feel free ask me, i will try my best to answer you, IFF our 19reborn is busy. :-)

surface quality optimizing ...

[FeiiYin]

Hi, I want to ask about the dataset preprocessing. I use a synthesize dataset from sapien, which can run on threestudio. It cannot run here, raise Nerf training generated 0 samples, Aborting training.

And I follow #26 (comment)
to preprocess the dataset, it raise the bellow error. It seems that my input data (camera or mask) is not right.
My input camera is proj_mtx_new, mask is extracted from the alpha of a png.
Thanks in advance!

c2w = transform[:3, :4] # transform is a synthesized parameters
mv = torch.linalg.inv(transform)
fovy =  np.random.uniform(self.fovy_range_min, self.fovy_range_max)
self.resolution = [512, 512]
K = np.array([
                [fovy, 0, self.resolution[0] / 2, 0],
                [0, fovy, self.resolution[1] / 2, 0],
                [0, 0, 1, 0],
                [0, 0, 0, 1]
            ])
K = torch.from_numpy(K).float()
proj_mtx_new = K @ mv

Number of points:0
/mnt/petrelfs/wangtengfei/code/NeuS2/tools/preprocess_cameras.py:220: RuntimeWarning: Mean of empty slice.
  centroid = np.array(all_Xs).mean(axis=0)
/opt/conda/lib/python3.9/site-packages/numpy/core/_methods.py:192: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/opt/conda/lib/python3.9/site-packages/numpy/core/_methods.py:269: RuntimeWarning: Degrees of freedom <= 0 for slice
  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,
/opt/conda/lib/python3.9/site-packages/numpy/core/_methods.py:226: RuntimeWarning: invalid value encountered in divide
  arrmean = um.true_divide(arrmean, div, out=arrmean,
/opt/conda/lib/python3.9/site-packages/numpy/core/_methods.py:261: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
Traceback (most recent call last):
  File "/mnt/petrelfs/wangtengfei/code/NeuS2/tools/preprocess_cameras.py", line 312, in <module>
    get_normalization(opt.source_dir, opt.use_linear_init, dataset)
  File "/mnt/petrelfs/wangtengfei/code/NeuS2/tools/preprocess_cameras.py", line 266, in get_normalization
    normalization, all_Xs = get_normalization_function(Ps, mask_points_all, number_of_normalization_points, number_of_cameras,masks_all)
  File "/mnt/petrelfs/wangtengfei/code/NeuS2/tools/preprocess_cameras.py", line 225, in get_normalization_function
    centroid,scale,all_Xs = refine_visual_hull(masks_all, Ps, scale, centroid)
  File "/mnt/petrelfs/wangtengfei/code/NeuS2/tools/preprocess_cameras.py", line 151, in refine_visual_hull
    points = points + center[:, np.newaxis]
IndexError: invalid index to scalar variable.

[zkx11919369933]

I shot it with my phone
ValueError: operands could not be broadcast together with shapes (1920,1080,4) (1920,1080,3)
what should I do？

[MikeJPelton]

Something similar happened to me - I think it's expecting your input images and/or masks to be 4 bytes per pixel, not 3, (i.e. RGB + Alpha, not just RGB). You can probably convert them with imagemagick, or in code using OpenCV. Hope it helps!

[txyugood]

How can I improve the quality of the reconstruction result? It looks a bit damaged.

[Start1er]

Hi:
I use custom dataset and run https://github.com/NVlabs/instant-ngp/blob/master/scripts/colmap2nerf.py to get a transforms.json, and run NeuS2 but seems like what ever I set aabb-scale, the "fog" exsit in cube which can made the object mesh not successfully export. So I'm here to ask does it need some pre-processing in custom data to let the SDF only consentrate on object not with "fog":
because I'm hard to get the object like your result without the "fog" in cube.: