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KeyuWu-CS / MonoHair

Code of MonoHair: High-Fidelity Hair Modeling from a Monocular Video
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python prepare_data.py --yaml=configs/reconstruct/big_wavy1 crash #5

Open LaurentGarcia opened 1 month ago

LaurentGarcia commented 1 month ago

Hello I am trying to execute the first step with:

  1. cp data_processed/big_wavy1 to data/big_wavy1
  2. python prepare_data.py --yaml=configs/reconstruct/big_wavy1
  3. setting configurations... loading configs/reconstruct/base.yaml... loading configs/reconstruct/big_wavy1.yaml...
    • HairGenerate:
    • connect_dot_threshold: 0.8
    • connect_scalp: True
    • connect_segments: True
    • connect_threshold: 0.0025
    • connect_to_guide: None
    • dist_to_root: 6
    • generate_segments: True
    • grow_threshold: 0.85
    • out_ratio: 0.35
    • PMVO:
    • conf_threshold: 0.15
    • filter_point: True
    • genrate_ori_only: None
    • infer_inner: True
    • num_sample_per_grid: 4
    • optimize: True
    • patch_size: 7
    • threshold: 0.025
    • visible_threshold: 1
    • bbox_min: [-0.32, -0.32, -0.24]
    • bust_to_origin: [0.006, -1.644, 0.01]
    • camera_path: camera/calib_data/wky07-22/cam_params.json
    • check_strands: True
    • cpu: None
    • data:
    • Conf_path: conf
    • Occ3D_path: ours/Occ3D.mat
    • Ori2D_path: best_ori
    • Ori3D_path: ours/Ori3D.mat
    • bust_path: ours/bust_long_tsfm.obj
    • case: big_wavy1
    • depth_path: render_depth
    • frame_interval: 7
    • image_size: [1920, 1080]
    • mask_path: hair_mask
    • raw_points_path: ours/colmap_points.obj
    • root: data
    • scalp_path: ours/scalp_tsfm.obj
    • strands_path: ours/world_str_raw.dat
    • device: cuda:0
    • gpu: 0
    • image_camera_path: ours/cam_params.json
    • infer_inner:
    • render_data: True
    • run_mvs: True
    • name: 10-16
    • ngp:
    • marching_cubes_density_thresh: 3.0
    • output_root: output
    • prepare_data:
    • fit_bust: None
    • process_bust: True
    • process_camera: True
    • process_imgs: True
    • render_depth: True
    • run_ngp: True
    • select_images: True
    • save_path: refine
    • scalp_diffusion: None
    • seed: 0
    • segment:
    • CDGNET_ckpt: assets/CDGNet/LIP_epoch_149.pth
    • MODNET_ckpt: assets/MODNet/modnet_photographic_portrait_matting.ckpt
    • scene_path: None
    • vsize: 0.005
    • yaml: configs/reconstruct/big_wavy1 (creating new options file...) distance: 2.254131284488828 distance: 2.2541312844888277 16:49:16 SUCCESS Initialized CUDA 12.5. Active GPU is #0: NVIDIA GeForce RTX 4090 [89] 16:49:16 INFO Loading NeRF dataset from 16:49:16 WARNING data\big_wavy1\colmap\base_cam.json does not contain any frames. Skipping. 16:49:16 WARNING data\big_wavy1\colmap\base_transform.json does not contain any frames. Skipping. 16:49:16 WARNING data\big_wavy1\colmap\cam_params.json does not contain any frames. Skipping. 16:49:16 WARNING data\big_wavy1\colmap\key_frame.json does not contain any frames. Skipping. 16:49:16 INFO data\big_wavy1\colmap\transforms.json 16:49:20 SUCCESS Loaded 1189 images after 3s 16:49:20 INFO cam_aabb=[min=[-1.17578,-0.902506,-0.0814099], max=[1.78049,1.91326,1.84811]] 16:49:22 INFO Loading network snapshot from: data\big_wavy1\colmap\base.ingp 16:49:22 INFO GridEncoding: Nmin=16 b=2.43803 F=4 T=2^19 L=8 16:49:22 INFO Density model: 3--[HashGrid]-->32--[FullyFusedMLP(neurons=64,layers=3)]-->1 16:49:22 INFO Color model: 3--[Composite]-->16+16--[FullyFusedMLP(neurons=64,layers=4)]-->3 16:49:22 INFO total_encoding_params=12855296 total_network_params=10240 Screenshot transforms from data\big_wavy1\colmap/base_transform.json Generating mesh via marching cubes and saving to data\big_wavy1\colmap/base.obj. Resolution=[512,512,512], Density Threshold=3.0 16:49:22 INFO #vertices=3666953 #triangles=7305214 range(0, 16) rendering data\big_wavy1\trainning_images/capture_images\000.png rendering data\big_wavy1\trainning_images/capture_images\001.png rendering data\big_wavy1\trainning_images/capture_images\002.png rendering data\big_wavy1\trainning_images/capture_images\003.png rendering data\big_wavy1\trainning_images/capture_images\004.png rendering data\big_wavy1\trainning_images/capture_images\005.png rendering data\big_wavy1\trainning_images/capture_images\006.png rendering data\big_wavy1\trainning_images/capture_images\007.png rendering data\big_wavy1\trainning_images/capture_images\008.png rendering data\big_wavy1\trainning_images/capture_images\009.png rendering data\big_wavy1\trainning_images/capture_images\010.png rendering data\big_wavy1\trainning_images/capture_images\011.png rendering data\big_wavy1\trainning_images/capture_images\012.png rendering data\big_wavy1\trainning_images/capture_images\013.png rendering data\big_wavy1\trainning_images/capture_images\014.png rendering data\big_wavy1\trainning_images/capture_images\015.png unable to load materials from: ./bust_long_c.obj.mtl unable to load materials from: ./bust_long_c.obj.mtl unable to load materials from: material.mtl unable to load materials from: ./bust_long_c.obj.mtl Start calculating masks! 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 169/169 [00:10<00:00, 16.46it/s] Start calculating hair masks! Traceback (most recent call last): File "C:\Users\Lauren\Documents\Source\MonoHair\prepare_data.py", line 182, in calculate_mask(segment_args) File "C:\Users\Lauren\Documents\Source\MonoHair\preprocess_capture_data\calc_masks.py", line 171, in calculate_mask for key, nkey in zip(state_dict_old.keys(), state_dict.keys()): RuntimeError: OrderedDict mutated during iteration
0mil commented 1 month ago

@KeyuWu-CS I am also experiencing the above issue. I am trying to find a solution, but it is not easy. Could I get some advice on this? Thank you in advance for your help.

KeyuWu-CS commented 1 month ago

@0mil @LaurentGarcia It's wired, I don't face this problem in different machines. I guess you download different CDGNet pretrained model (Their repo have two model with same name). I uploaded the model I used on one drive, you can try again. You also can refer to the mask calculate of NeuralHairCut. We used the same method.

0mil commented 1 month ago

@KeyuWu-CS Thank you for your quick response! I'll try to resolve the issue using the method you suggested. If successful, I'll support with other similar issues. 👍👍

0mil commented 1 month ago

@KeyuWu-CS @LaurentGarcia I have tested NeuralHairCut and found no issues in the code. I think that the OrderedDict Runtime Error occurs only in Python 3.10 and can be fixed with a simple code changes(Please refer to the PR I submitted for this.). However, a new issue arise. Despite confirming that the provided CDGNet model and checkpoint are the same, the following problem persists. This might be due to library version differences. To resolve this, I have a few questions:

Providing this information will help us resolve the issue. Thank you!

Traceback (most recent call last):
  File "/workspace/prepare_data.py", line 182, in <module>
    calculate_mask(segment_args)
  File "/workspace/preprocess_capture_data/calc_masks.py", line 190, in calculate_mask
    model.load_state_dict(state_dict)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1497, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for ResNet:
        Unexpected key(s) in state_dict: "layer5.stages.0.2.weight", "layer5.stages.0.2.bias", "layer5.stages.0.2.running_mean", "layer5.stages.0.2.running_var", "layer5.stages.1.2.weight", "layer5.stages.1.2.bias",
 "layer5.stages.1.2.running_mean", "layer5.stages.1.2.running_var", "layer5.stages.2.2.weight", "layer5.stages.2.2.bias", "layer5.stages.2.2.running_mean", "layer5.stages.2.2.running_var", "layer5.stages.3.2.weight", "layer5.stages.3.2.bias", 
"layer5.stages.3.2.running_mean", "layer5.stages.3.2.running_var", "layer5.bottleneck.1.weight", "layer5.bottleneck.1.bias", "layer5.bottleneck.1.running_mean", "layer5.bottleneck.1.running_var", 
"edge_layer.conv1.1.weight", "edge_layer.conv1.1.bias", "edge_layer.conv1.1.running_mean", "edge_layer.conv1.1.running_var", "edge_layer.conv2.1.weight", "edge_layer.conv2.1.bias", "edge_layer.conv2.1.running_mean", "edge_layer.conv2.1.running_var", 
"edge_layer.conv3.1.weight", "edge_layer.conv3.1.bias", "edge_layer.conv3.1.running_mean", "edge_layer.conv3.1.running_var", "layer6.conv1.1.weight", "layer6.conv1.1.bias", "layer6.conv1.1.running_mean", 
"layer6.conv1.1.running_var", "layer6.conv2.1.weight", "layer6.conv2.1.bias", "layer6.conv2.1.running_mean", "layer6.conv2.1.running_var", "layer6.conv3.1.weight", "layer6.conv3.1.bias", "layer6.conv3.1.running_mean", "layer6.conv3.1.running_var", "layer6.conv3.3.weight", "layer6.conv3.3.bias", "layer6.conv3.3.running_mean", 
"layer6.conv3.3.running_var", "layer7.1.weight", "layer7.1.bias", "layer7.1.running_mean", "layer7.1.running_var". 
        size mismatch for layer6.conv2.0.weight: copying a param with shape torch.Size([48, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([48, 256, 3, 3]).
        size mismatch for layer6.conv3.0.weight: copying a param with shape torch.Size([256, 304, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 304, 3, 3]).
        size mismatch for layer7.0.weight: copying a param with shape torch.Size([256, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 1024, 3, 3]).
KeyuWu-CS commented 1 month ago

I just run it again, I don't face this problem. My environment is python 3.10.12 . And I print all the library here.

absl-py 2.1.0 addict 2.4.0 albumentations 1.3.1 argcomplete 3.4.0 astroid 3.2.2 asttokens 2.4.1 astunparse 1.6.3 attrs 23.2.0 autopep8 2.3.1 backcall 0.2.0 beautifulsoup4 4.12.3 bleach 6.1.0 blinker 1.8.2 certifi 2024.6.2 charset-normalizer 3.3.2 chumpy 0.70 click 8.1.7 cloudpickle 3.0.0 coloredlogs 15.0.1 colorlog 6.8.2 comm 0.2.2 commentjson 0.9.0 ConfigArgParse 1.7 contourpy 1.2.1 cycler 0.12.1 cyclonedds 0.10.5 Cython 3.0.10 dash 2.17.1 dash-core-components 2.0.0 dash-html-components 2.0.0 dash-table 5.0.0 decorator 5.1.1 defusedxml 0.7.1 dill 0.3.8 distlib 0.3.8 dm-tree 0.1.8 docker-pycreds 0.4.0 docopt 0.6.2 docutils 0.21.2 easydict 1.13 einops 0.8.0 exceptiongroup 1.2.1 executing 2.0.1 face-alignment 1.4.1 face-detection-tflite 0.6.0 fastcore 1.5.46 fastjsonschema 2.19.1 filelock 3.15.1 flake8 7.1.0 Flask 3.0.3 flatbuffers 24.3.25 fonttools 4.53.0 fvcore 0.1.5.post20220512 gast 0.5.4 ghapi 1.0.5 gitdb 4.0.11 GitPython 3.1.43 glcontext 2.5.0 google-pasta 0.2.0 graphviz 0.20.3 grpcio 1.64.1 h5py 3.11.0 humanfriendly 10.0 idna 3.7 imageio 2.34.1 importlib_metadata 7.1.0 iniconfig 2.0.0 insightface 0.7.3 iopath 0.1.10 ipdb 0.13.13 ipython 8.12.3 ipywidgets 8.1.3 isort 5.13.2 itsdangerous 2.2.0 jedi 0.19.1 Jinja2 3.1.4 joblib 1.4.2 jsonschema 4.22.0 jsonschema-specifications 2023.12.1 jupyter_client 8.6.2 jupyter_core 5.7.2 jupyterlab_pygments 0.3.0 jupyterlab_widgets 3.0.11 keras 3.3.3 kiwisolver 1.4.5 kornia 0.7.2 kornia_rs 0.1.3 lark-parser 0.7.8 lazy_loader 0.4 libclang 18.1.1 lightning-utilities 0.11.2 llvmlite 0.43.0 loguru 0.7.2 lpips 0.1.4 Markdown 3.6 markdown-it-py 3.0.0 MarkupSafe 2.1.5 matplotlib 3.9.0 matplotlib-inline 0.1.7 mccabe 0.7.0 mdurl 0.1.2 mistune 3.0.2 ml-dtypes 0.3.2 moderngl 5.10.0 mpmath 1.3.0 namex 0.0.8 nbclient 0.10.0 nbconvert 7.16.4 nbformat 5.10.4 nest-asyncio 1.6.0 networkx 3.3 nox 2024.4.15 numba 0.60.0 numpy 1.23.5 nvidia-cublas-cu11 11.10.3.66 nvidia-cuda-nvrtc-cu11 11.7.99 nvidia-cuda-runtime-cu11 11.7.99 nvidia-cudnn-cu11 8.5.0.96 onnx 1.16.1 onnxruntime 1.18.0 open3d 0.18.0 opencv-python 4.10.0.82 opencv-python-headless 4.10.0.82 opt-einsum 3.3.0 optree 0.11.0 packaging 24.1 pandas 2.2.2 pandocfilters 1.5.1 parso 0.8.4 pexpect 4.9.0 pickleshare 0.7.5 pillow 10.3.0 pip 24.0 pipreqs 0.5.0 platformdirs 4.2.2 plotly 5.22.0 pluggy 1.5.0 portalocker 2.8.2 prettytable 3.10.0 prompt_toolkit 3.0.47 protobuf 4.25.3 psutil 5.9.8 ptyprocess 0.7.0 pure-eval 0.2.2 pycodestyle 2.12.0 pyflakes 3.2.0 Pygments 2.18.0 pylint 3.2.3 pyntcloud 0.3.1 pyparsing 3.1.2 pyquaternion 0.9.9 pytest 8.2.2 python-dateutil 2.9.0.post0 pytorch3d 0.7.2 pytz 2024.1 PyYAML 6.0.1 pyzmq 26.0.3 qudida 0.0.4 referencing 0.35.1 requests 2.32.3 retrying 1.3.4 rich 13.7.1 rich-click 1.8.3 rpds-py 0.18.1 scikit-image 0.23.2 scikit-learn 1.5.0 scipy 1.13.1 sentry-sdk 2.5.1 setproctitle 1.3.3 setuptools 59.6.0 six 1.16.0 smmap 5.0.1 soupsieve 2.5 stack-data 0.6.3 sympy 1.12.1 tabulate 0.9.0 tenacity 8.3.0 tensorboard 2.16.2 tensorboard-data-server 0.7.2 tensorboardX 2.6.2.2 tensorflow 2.16.1 tensorflow-io-gcs-filesystem 0.37.0 tensorflow-probability 0.24.0 termcolor 2.4.0 threadpoolctl 3.5.0 tifffile 2024.5.22 tinycss2 1.3.0 tinycudann 1.7 tomli 2.0.1 tomlkit 0.12.4 torch 1.11.0+cu113 torchaudio 0.11.0+cu113 torchmetrics 1.4.0.post0 torchvision 0.12.0+cu113 torchviz 0.0.2 tornado 6.4.1 tqdm 4.66.4 traitlets 5.14.3 trimesh 3.12.6 typing_extensions 4.10.0 tzdata 2024.1 urllib3 2.2.1 virtualenv 20.26.2 wandb 0.17.1 wcwidth 0.2.13 webencodings 0.5.1 Werkzeug 3.0.3 wheel 0.43.0 widgetsnbextension 4.0.11 wrapt 1.16.0 yacs 0.1.8 yarg 0.1.9 zipp 3.19.2

LaurentGarcia commented 1 month ago

This is my one:

Name Version Build Channel

absl-py 2.1.0 pypi_0 pypi albumentations 1.3.1 pypi_0 pypi argcomplete 3.4.0 pypi_0 pypi asttokens 2.4.1 pypi_0 pypi astunparse 1.6.3 pypi_0 pypi attrs 23.2.0 pypi_0 pypi backcall 0.2.0 pypi_0 pypi blinker 1.8.2 pypi_0 pypi bzip2 1.0.8 h2bbff1b_6 ca-certificates 2024.7.2 haa95532_0 certifi 2024.7.4 pypi_0 pypi charset-normalizer 3.3.2 pypi_0 pypi chumpy 0.70 pypi_0 pypi click 8.1.7 pypi_0 pypi cloudpickle 3.0.0 pypi_0 pypi cmake 3.30.1 pypi_0 pypi colorama 0.4.6 pypi_0 pypi coloredlogs 15.0.1 pypi_0 pypi colorlog 6.8.2 pypi_0 pypi comm 0.2.2 pypi_0 pypi commentjson 0.9.0 pypi_0 pypi configargparse 1.7 pypi_0 pypi contourpy 1.2.1 pypi_0 pypi cycler 0.12.1 pypi_0 pypi cyclonedds 0.10.5 pypi_0 pypi cython 3.0.10 pypi_0 pypi dash 2.17.1 pypi_0 pypi dash-core-components 2.0.0 pypi_0 pypi dash-html-components 2.0.0 pypi_0 pypi dash-table 5.0.0 pypi_0 pypi decorator 5.1.1 pypi_0 pypi distlib 0.3.8 pypi_0 pypi dm-tree 0.1.8 pypi_0 pypi docker-pycreds 0.4.0 pypi_0 pypi docutils 0.21.2 pypi_0 pypi easydict 1.13 pypi_0 pypi einops 0.8.0 pypi_0 pypi exceptiongroup 1.2.2 pypi_0 pypi executing 2.0.1 pypi_0 pypi face-alignment 1.4.1 pypi_0 pypi face-detection-tflite 0.6.0 pypi_0 pypi fastcore 1.5.54 pypi_0 pypi fastjsonschema 2.20.0 pypi_0 pypi filelock 3.15.4 pypi_0 pypi flask 3.0.3 pypi_0 pypi flatbuffers 24.3.25 pypi_0 pypi fonttools 4.53.1 pypi_0 pypi fvcore 0.1.5.post20220512 pypi_0 pypi gast 0.6.0 pypi_0 pypi ghapi 1.0.5 pypi_0 pypi gitdb 4.0.11 pypi_0 pypi gitpython 3.1.43 pypi_0 pypi glcontext 2.5.0 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.65.1 pypi_0 pypi h5py 3.11.0 pypi_0 pypi humanfriendly 10.0 pypi_0 pypi idna 3.7 pypi_0 pypi imageio 2.34.1 pypi_0 pypi importlib-metadata 8.1.0 pypi_0 pypi iniconfig 2.0.0 pypi_0 pypi insightface 0.7.3 pypi_0 pypi iopath 0.1.10 pypi_0 pypi ipdb 0.13.13 pypi_0 pypi ipython 8.12.3 pypi_0 pypi ipywidgets 8.1.3 pypi_0 pypi itsdangerous 2.2.0 pypi_0 pypi jedi 0.19.1 pypi_0 pypi jinja2 3.1.4 pypi_0 pypi joblib 1.4.2 pypi_0 pypi jsonschema 4.23.0 pypi_0 pypi jsonschema-specifications 2023.12.1 pypi_0 pypi jupyter-core 5.7.2 pypi_0 pypi jupyterlab-widgets 3.0.11 pypi_0 pypi keras 3.4.1 pypi_0 pypi kiwisolver 1.4.5 pypi_0 pypi kornia 0.7.2 pypi_0 pypi kornia-rs 0.1.5 pypi_0 pypi lark-parser 0.7.8 pypi_0 pypi lazy-loader 0.4 pypi_0 pypi libclang 18.1.1 pypi_0 pypi libffi 3.4.4 hd77b12b_1 lightning-utilities 0.11.6 pypi_0 pypi llvmlite 0.43.0 pypi_0 pypi loguru 0.7.2 pypi_0 pypi lpips 0.1.4 pypi_0 pypi markdown 3.6 pypi_0 pypi markdown-it-py 3.0.0 pypi_0 pypi markupsafe 2.1.5 pypi_0 pypi matplotlib 3.9.0 pypi_0 pypi matplotlib-inline 0.1.7 pypi_0 pypi mdurl 0.1.2 pypi_0 pypi ml-dtypes 0.3.2 pypi_0 pypi moderngl 5.10.0 pypi_0 pypi mpmath 1.3.0 pypi_0 pypi namex 0.0.8 pypi_0 pypi nbformat 5.10.4 pypi_0 pypi nest-asyncio 1.6.0 pypi_0 pypi networkx 3.3 pypi_0 pypi nox 2024.4.15 pypi_0 pypi numba 0.60.0 pypi_0 pypi numpy 1.23.5 pypi_0 pypi onnx 1.16.1 pypi_0 pypi onnxruntime 1.18.0 pypi_0 pypi open3d 0.18.0 pypi_0 pypi opencv-python 4.10.0.82 pypi_0 pypi opencv-python-headless 4.10.0.84 pypi_0 pypi openssl 3.0.14 h827c3e9_0 opt-einsum 3.3.0 pypi_0 pypi optree 0.12.1 pypi_0 pypi packaging 24.1 pypi_0 pypi pandas 2.2.2 pypi_0 pypi parso 0.8.4 pypi_0 pypi pickleshare 0.7.5 pypi_0 pypi pillow 10.3.0 pypi_0 pypi pip 24.0 py310haa95532_0 platformdirs 4.2.2 pypi_0 pypi plotly 5.23.0 pypi_0 pypi pluggy 1.5.0 pypi_0 pypi portalocker 2.10.1 pypi_0 pypi prettytable 3.10.2 pypi_0 pypi prompt-toolkit 3.0.47 pypi_0 pypi protobuf 4.25.3 pypi_0 pypi psutil 6.0.0 pypi_0 pypi pure-eval 0.2.3 pypi_0 pypi pygments 2.18.0 pypi_0 pypi pyntcloud 0.3.1 pypi_0 pypi pyparsing 3.1.2 pypi_0 pypi pyquaternion 0.9.9 pypi_0 pypi pyreadline3 3.4.1 pypi_0 pypi pytest 8.2.2 pypi_0 pypi python 3.10.12 he1021f5_0 python-dateutil 2.9.0.post0 pypi_0 pypi python-graphviz 0.20.3 pypi_0 pypi pytorch3d 0.7.7 pypi_0 pypi pytz 2024.1 pypi_0 pypi pywin32 306 pypi_0 pypi pyyaml 6.0.1 pypi_0 pypi qudida 0.0.4 pypi_0 pypi referencing 0.35.1 pypi_0 pypi requests 2.32.3 pypi_0 pypi retrying 1.3.4 pypi_0 pypi rich 13.7.1 pypi_0 pypi rich-click 1.8.3 pypi_0 pypi rpds-py 0.19.0 pypi_0 pypi scikit-image 0.23.2 pypi_0 pypi scikit-learn 1.5.1 pypi_0 pypi scipy 1.13.1 pypi_0 pypi sentry-sdk 2.10.0 pypi_0 pypi setproctitle 1.3.3 pypi_0 pypi setuptools 59.6.0 pypi_0 pypi six 1.16.0 pypi_0 pypi smmap 5.0.1 pypi_0 pypi sqlite 3.45.3 h2bbff1b_0 stack-data 0.6.3 pypi_0 pypi sympy 1.12.1 pypi_0 pypi tabulate 0.9.0 pypi_0 pypi tenacity 8.5.0 pypi_0 pypi tensorboard 2.16.2 pypi_0 pypi tensorboard-data-server 0.7.2 pypi_0 pypi tensorboardx 2.6.2.2 pypi_0 pypi tensorflow 2.16.1 pypi_0 pypi tensorflow-intel 2.16.1 pypi_0 pypi tensorflow-io-gcs-filesystem 0.31.0 pypi_0 pypi tensorflow-probability 0.24.0 pypi_0 pypi termcolor 2.4.0 pypi_0 pypi threadpoolctl 3.5.0 pypi_0 pypi tifffile 2024.7.21 pypi_0 pypi tinycudann 1.7 pypi_0 pypi tk 8.6.14 h0416ee5_0 tomli 2.0.1 pypi_0 pypi torch 1.11.0+cu113 pypi_0 pypi torchaudio 0.11.0+cu113 pypi_0 pypi torchmetrics 1.4.0.post0 pypi_0 pypi torchvision 0.12.0+cu113 pypi_0 pypi torchviz 0.0.2 pypi_0 pypi tqdm 4.66.4 pypi_0 pypi traitlets 5.14.3 pypi_0 pypi trimesh 3.12.6 pypi_0 pypi typing-extensions 4.12.2 pypi_0 pypi tzdata 2024.1 pypi_0 pypi urllib3 2.2.2 pypi_0 pypi vc 14.2 h2eaa2aa_4 virtualenv 20.26.3 pypi_0 pypi vs2015_runtime 14.29.30133 h43f2093_4 wandb 0.17.1 pypi_0 pypi wcwidth 0.2.13 pypi_0 pypi werkzeug 3.0.3 pypi_0 pypi wheel 0.43.0 py310haa95532_0 widgetsnbextension 4.0.11 pypi_0 pypi win32-setctime 1.1.0 pypi_0 pypi wrapt 1.16.0 pypi_0 pypi xz 5.4.6 h8cc25b3_1 yacs 0.1.8 pypi_0 pypi zipp 3.19.2 pypi_0 pypi zlib 1.2.13 h8cc25b3_1

LaurentGarcia commented 1 month ago

Hello @KeyuWu-CS I can confirm than it's working! Download your CDGNet made the magic.

0mil commented 1 month ago

@0mil @LaurentGarcia It's wired, I don't face this problem in different machines. I guess you download different CDGNet pretrained model (Their repo have two model with same name). I uploaded the model I used on one drive, you can try again. You also can refer to the mask calculate of NeuralHairCut. We used the same method.

@KeyuWu-CS You are right. prepare_data.py works perfectly on big_wavy1 case. This is really impressive research!