Hi Thank you again for this research work. So I could train perfectly using default parameters. Now when I run test to create mesh, I am getting this error:

Traceback (most recent call last):
  File "onSurPrior.py", line 833, in <module>
    vertices, triangles, _, _ = marching_cubes_lewiner(vox, thresh)
  File "/usr/local/lib/python3.7/dist-packages/skimage/measure/_marching_cubes_lewiner.py", line 135, in marching_cubes_lewiner
    raise ValueError("Surface level must be within volume data range.")
ValueError: Surface level must be within volume data range.

How do I fix this? Thank you in advance.

So, I am trying to convert my point cloud to a mesh using your code. There seems to be some problem in the implementation i think

here's my point cloud: test_100k.ply.zip

I've run your code with

python onSurPrior.py --data_dir ./data/ --out_dir ./train_net/ --CUDA 0 --INPUT_NUM 102906 --epoch 30000 --input_ply_file test_100k.ply --train

epoch: 25000 epoch loss: 6.665881e-05 loss_sdf: 2.4980092e-05 move loss: 0.0002083936
epoch: 25500 epoch loss: 0.000111603404 loss_sdf: 2.5077257e-05 move loss: 0.00043263074
epoch: 26000 epoch loss: 0.00020120309 loss_sdf: 2.490602e-05 move loss: 0.0008814853
epoch: 26500 epoch loss: 0.00021180889 loss_sdf: 2.4966e-05 move loss: 0.00093421445
epoch: 27000 epoch loss: 5.7760502e-05 loss_sdf: 2.4734798e-05 move loss: 0.00016512853
epoch: 27500 epoch loss: 4.7512913e-05 loss_sdf: 2.4716563e-05 move loss: 0.00011398175
epoch: 28000 epoch loss: 0.00021200601 loss_sdf: 2.4922432e-05 move loss: 0.00093541783
epoch: 28500 epoch loss: 0.00020918738 loss_sdf: 2.4982723e-05 move loss: 0.0009210232
epoch: 29000 epoch loss: 6.323241e-05 loss_sdf: 2.4784342e-05 move loss: 0.00019224035
epoch: 29500 epoch loss: 4.3345903e-05 loss_sdf: 2.486095e-05 move loss: 9.242476e-05
save model
run_time: 4451.92893910408

it seems to train file with loss decreasing

but the mesh output is not good

i've run the test part with

python onSurPrior.py --data_dir ./data/ --out_dir ./train_net/ --CUDA 0 --INPUT_NUM 102906 --epoch 30000 --input_ply_file test_100k.ply --test

but there is an error

g_points_knn: Tensor("GatherV2_1:0", shape=(1, 4096, 50, 3), dtype=float32)
g_points_knn: Tensor("Reshape_12:0", shape=(4096, 50, 3), dtype=float32)
rotate_p: Tensor("Tile_1:0", shape=(4096, 50, 3), dtype=float32)
feature_f: Tensor("pointnet_1/Relu:0", shape=(4096, 512), dtype=float32)
pointnet: Tensor("pointnet_1/dense_1/BiasAdd:0", shape=(4096, 512), dtype=float32)
feature_f: Tensor("pointnet_2/Relu:0", shape=(4096, 512), dtype=float32)
pointnet: Tensor("pointnet_2/dense_1/BiasAdd:0", shape=(4096, 512), dtype=float32)
feature_bs: (2000, 2000)
test start
256
[1.05      1.4866935 0.773277 ]
[-0.05 -0.05 -0.05]
max_min: 0.00043043494 -0.0009069443 3.9753166e-05
0 16777216
Traceback (most recent call last):
  File "onSurPrior.py", line 832, in <module>
    vertices, triangles, _, _ = marching_cubes_lewiner(vox, thresh)
  File "/home/ubuntu/anaconda3/envs/tensorflow2_p38/lib/python3.8/site-packages/skimage/measure/_marching_cubes_lewiner.py", line 135, in marching_cubes_lewiner
    raise ValueError("Surface level must be within volume data range.")
ValueError: Surface level must be within volume data range.

i believe this is due to the output being larger than the voxel specified, so i made the following change

bd_max  = np.asarray(bd_max) + 0.05 * 20
bd_min = np.asarray(bd_min) - 0.05 * 20

this does not give the surface level must be within volume data range error, but the output is wrong

So i removed the bd_max and bd_min change, and set voxel size to 128 and run on a different system. and this was the output, still its not good.

also i tried to change the voxel size from 128 to 256, but that doesn't help

I'm not sure what i am doing wrong. could there be some issue with my GPU ? I'm using a V100 (32GB) , i tried on a RTX 3090, but that had different issues:

(/job:localhost/replica:0/task:0/device:GPU:0 with 22255 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:06:00.0, compute capability: 8.6)
feature_bs: (2000, 2000)
train start
2022-05-15 11:09:50.715829: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2022-05-15 11:11:18.078192: E tensorflow/stream_executor/cuda/cuda_blas.cc:428] failed to run cuBLAS routine: CUBLAS_STATUS_EXECUTION_FAILED
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
    return fn(*args)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(4096, 3), b.shape=(3, 512), m=4096, n=512, k=3
	 [[{{node global/dense_1/MatMul}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "onSurPrior.py", line 746, in <module>
    sess.run([loss_optim],feed_dict={input_points_3d:input_points_2d_bs,feature_object:feature_bs_t,points_target_sparse:knn_bs})
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
    run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(4096, 3), b.shape=(3, 512), m=4096, n=512, k=3
	 [[node global/dense_1/MatMul (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]

NOTE: I'm using the same conda environment tf.yml

After fixing this issue: https://github.com/mabaorui/OnSurfacePrior/issues/2 I got nan on epoch: epoch: 0 epoch loss: nan loss_sdf: nan move loss: nan I even reduced the learning rate but didn't help. What am I missing? Thank you in advance @mabaorui.

Hi I would like to thank the author for this great research. I am trying this repository on my point cloud data (in .ply format).

I am getting error while training:

Traceback (most recent call last):
  File “onSurPrior.py”, line 747, in <module>
    index_fine = np.random.choice(SP_NUM//10, POINT_NUM, replace = True)
  File “mtrand.pyx”, line 902, in numpy.random.mtrand.RandomState.choice
ValueError: a must be greater than 0 unless no samples are taken 

When I check SP_NUM then it showing 0 Here is the header of my point cloud file:

ply
format binary_little_endian 1.0
element vertex 2524937
property float x
property float y
property float z
property float nx
property float ny
property float nz
property uchar red
property uchar green
property uchar blue
property uchar views
end_header

Can you help me why I am getting this error? Thank you in advance. I really appreciate for it.

My PC env: Ubuntu 20.04 GPU: GeForce RTX3090 24GB

I am trying to run the pretrained model on a .ply file with the --test command, and I am getting the error:

ValueError: The passed save_path is not a valid checkpoint: /home/user/COMP0132/workspace/surfaceReconmodel-0

when running

python onSurPrior.py --data_dir ~/COMP0132/Mesh/data --out_dir ~/COMP0132/workspace/surfaceRecon --CUDA 0 --INPUT_NUM   189470 --epoch 30000 --input_ply_file  ~/COMP0132/brighton_text/Mesh/data/brighton.ply --test

--data_dir is the directory with input.ply (brighton.ply) --out_dir is the empty directory you want output in --input_ply_file brighton.ply (with or without full path?)
Is this correct? I am a little confused as to the parsed arguments and which should be which.

System Ubuntu 18.04 No GPU

i use my data input, but get a bad mesh, should i change other params in the code ? --data_dir ./data/ --out_dir ./train_net/ --CUDA 0 --INPUT_NUM 71642 --epoch 30000 --input_ply_file laser_71642.ply --train