samsunglabs / neuralhaircut Goto Github PK

Now I'm receiving this error and now I really don know what to do.

Hi, thanks for your work and the code, the results are very impressive!

I'm new in the realm of hair reconstruction and modeling. I noticed in the Related Work Section the paper says:

Non-uniform lighting and low effective resolution of the real-world data lead to orientation maps having excessive noise levels or lacking details.

How does NeuralHaircut solve this problem?

In my understanding, the neural hair growth field may alleviate this problem to some extent, as it aggregates information across multi-views; thus, the noise may be reduced. In addition, the use of the prior model would also alleviate this problem as it constrains the resulting hair model to be within a valid space.

What about your opinion? Thanks in advance.

Hello,

My colleagues and I are having trouble creating the enviroment with conda, we all have the same error using different machines.

In my case, I am using Ubuntu 22.04 --also tried on Windows 10-- with the latest conda version and 30 series NVIDIA GPUs. In all of these cases I get the same error from the console: conda is unable to create the enviroment due to an extraordinary amount of version errors, most of them related to Pytorch and CUDA.

I attached a txt containing the error trace from the console :
error.txt

As I said, I'm not the only one having this problem, my colleagues are experimenting just the same, with very similar --if not equal-- error traces, and some of them are using PIP.

Right now I'm trying these steps, but I don't think that'll solve anything:

1. Install Pytorch and Pytorch 3D versions that match the dependencies one.
2. Check for all imports on code files and take out the version number of these packages on yaml.
3. Take out prequisites of anything that is not directly use on code.

No luck for now.

Hi, can someone help me to solve this error?

I run this command
python run_geometry_reconstruction.py --case person_0 --conf ./configs/example_config/neural_strands-monocular.yaml --exp_name first_stage_person_0

Error

Hello Wooden
False
upload transform {'translation': array([0.37335169, 2.34675772, 2.03221262]), 'scale': 2.368383848250081} ./implicit-hair-data/data/monocular/person_0/scale.pickle
Number of views: 66
Traceback (most recent call last):
  File "C:\Users\ADMIN\Desktop\NeuralHaircut\run_geometry_reconstruction.py", line 842, in <module>
    runner = Runner(args.conf, args.mode, args.case, args.is_continue, checkpoint_name=args.checkpoint, exp_name=args.exp_name,  train_cameras=args.train_cameras)
  File "C:\Users\ADMIN\Desktop\NeuralHaircut\run_geometry_reconstruction.py", line 72, in __init__
    self.dataset = MonocularDataset(self.conf['dataset'])
  File "C:\Users\ADMIN\Desktop\NeuralHaircut\src\models\dataset.py", line 361, in __init__
    self.orientations_np = np.stack([cv.imread(im_name) for im_name in self.orientations_lis]) / float(self.num_bins) * math.pi
numpy.core._exceptions._ArrayMemoryError: Unable to allocate 6.88 GiB for an array with shape (66, 2160, 2160, 3) and data type float64

Hello, I'm trying to test using the provided that, but it returns with the following error

index 66 is out of bounds for axis 0 with size 66

I'm trying to debug but somthing is strange and I cant understadwhat is.
Can someone give me a help? thanks

I followed the instructions in ./example/readme.md, and as a result, the model was generated with strands in a disconnected form. Is there a way to change this to a connected form, similar to a Bezier curve?

What is the correct procedure for the random sampling of hair strands as shown in the paper (Figure. 7 of the Appendix)?

Hi. Thanks for your great work.
Has someone run the example code (https://github.com/SamsungLabs/NeuralHaircut/blob/main/example) and met this problem?
I followed the step to build my environment and I used v100 to run the example code. I ran 100000 steps in stage one and then started stage two. However one of the results in pred_hair_strands of stage two is as followed and I think it's vague:

Does anyone know how to solve this problem?

Thanks.

Can someone successfully create the environment? There are a lot of conflicts in the .yaml and conda couldn't solve.

hi, can someone help me to solve this error?
i try to train the second stage using the data you provide(because the memory limitation, i use 40 images ), and the loss isn't decreasing.

How can I obtain pretrained models/stand-prior/strand_ckpt. pth

Hi,
I have a question about can I use my own 2D single image (Front image) ?

Thank you.

I am trying to pre-process custom data, by following your indications. For simplicity, i am using the monocular data provided by you in /monocular/person_0_image. I get an error when executing the command:

python preprocess_custom_data/calc_masks.py --scene_path ./implicit-hair-data/data/SCENE_TYPE/CASE/ --MODNET_ckpt path_to_modnet --CDGNET_ckpt path_to_cdgnet

calc_masks.py", line 159, in main
for key, nkey in zip(state_dict_old.keys(), state_dict.keys()):
RuntimeError: OrderedDict mutated during iteration

I tried to find a workaround by rewriting the lines from 156 to 164 like this (following the discussion here: https://github.com/pytorch/pytorch/issues/40859

current_model_dict = model.state_dict()
loaded_state_dict = torch.load(args.CDGNET_ckpt, map_location='cpu')
new_state_dict={k:v if v.size()==current_model_dict[k].size()  else  current_model_dict[k] for k,v in zip(current_model_dict.keys(), loaded_state_dict.values())}
model.load_state_dict(new_state_dict, strict=False)

and then the images are generated, but they are all black. So what am i missing?
By contrast, mask images via MODnet are generated succesfully.

I already donwloaded PIXIE and it's dependencies, but I still can not find out the way to generate initialization_pixie file. Could you give me any tips on that?

The experiment folder cannot be created when launching
python run_geometry_reconstruction.py --case person_0 --conf ./configs/example_config/neural_strands-monocular.yaml --exp_name first_stage_person_0
due to colons in the file path.
Error:
OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect: 'exps_first_stage\\first_stage_person_0\\person_0\\neural_strands-monocular\\2023-07-25_20:08:00'

I went around that by adding the line in the run_geometry_reconstruction.py
time = time.replace(':','_')

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Thanks for your great work.
I am reproducing your work with h3ds dataset. But I am facing one problem in multi-view optimization (https://github.com/SamsungLabs/NeuralHaircut/tree/main/src/multiview_optimization) : it says that we need an initialization with PIXIE for shape, pose parameters and save it as a dict in initialization_pixie file.

When I go to PIXIE repository, I am wondering which single image can be used for the initialization or all the multi-view images have to be used. Also, how to get initialization_pixie file is unclear. Thank you!

Best,
Mike

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I saw the videos, impressive but it's going to fail with black afro, small curled hairs, right ? ^^
Can we see that or you don't consider it at all