Open AmoghTiwari opened 11 months ago
AmoghTiwari
commented
11 months ago @Jeff-sjtu : Please have a look at the environment setup instructions. If they work across a few other machiens, you can update the README accordingly. Also check out the Directory Structure section. Adding those to the README might also be helpful
Echolink50
commented
11 months ago Checking in. Windows 10, Xeon E3 V5, 16GB ram, RTX 3060 Ti. About a week ago I was trying to run hybrik with no luck. I figured out that I needed to run python 3.9 and got pytorch3d installed. Did the numpy thing as well. Kept getting the opencv error so I tried uninstalling openCV and reinstalling several different versions. Still didn't get it to work. The thing I missed that this guy helped me with was to delete openCV from the setup file. That enabled it to work.
The main difference that I had in the setup was that I ran CUDA 11.7. Installing CUDA 11.6 would get stuck at solving. Also the cub install couldn't be found but CUDA 11.7 doesn't need cub. I used this command.
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
And this for pytorch3d
pip install "git+https://github.com/facebookresearch/pytorch3d.git@stable"
Thanks for the help. Anybody know about running Hybrik-X? I tried and get an error about a .pk file or something. Also, What is the difference? Is Hybrik-X faster and uses GPU or better results or what?
AmoghTiwari
commented
11 months ago Glad that it helped. Thanks for sharing your suggestions also.
Regarding your query about Hybrik-X - Hybrik-X regresses smpl-x parameters, while Hybrik regresses smpl parameters. smpl-x was a follow up work to smpl with information for more joints specifically, for the hand and face. You can read about smpl-x here
Echolink50
commented
11 months ago Ok. Are you able to run hybrik-x? I get an error about save.pk. What needs to be changed to run hybrik-x? Thanks
Dipankar1997161
commented
8 months ago Glad that it helped. Thanks for sharing your suggestions also.
Regarding your query about Hybrik-X - Hybrik-X regresses smpl-x parameters, while Hybrik regresses smpl parameters. smpl-x was a follow up work to smpl with information for more joints specifically, for the hand and face. You can read about smpl-x here
Hey Amogh, thank you for such a prompt explanation for the setup. 😁
It would be great if you can clarify a question of mine regarding the dataset.
I wish to train HyBrik on my custom dataset but I need to setup the annotation files in a correct structure and have to include the necessary things to avoid any failed trainings.
Could you maybe quickly brief on the things which are necessary.
Currently I have the following: SMPL Paramters (poses, betas, 3d Joints, 2d joints, Camera paramters) Is there anything else needed ??
Also how should the annotation structure be in case you know this. it will be wonderful since the 3 processed dataset given in this repo, follow different structure. So am confused which one to follow.
Hope to hear from you soon
sebastianopazo1
commented
8 months ago I faced some trouble while trying to setup the environment to run the code. Specially, with pytorch3d. So I am sharing the steps using which I was able to finally set up the code. Note that, till now I have only tried out the demo code. So I still can't confirm if the below steps will be sufficient for running the training code also. Also, if this doesn't work, please be sure to look at other comments also (for example, it worked for me with cuda 11.6, while someone else has shared there suggestions below that it worked for them with cuda 11.7).
System Details: Ubuntu 18.04 with 4 Nvidia 2080 Ti (Remote server)
Environment Setup
Note: Steps: 1-4 did not work for me. So you might want to directly jump to step-5
1. Try following the repo's official [installation instructions](https://github.com/Jeff-sjtu/HybrIK#installation-instructions). If they work, great! 2. If you face an issue in step-5, when running `python setup.py develop`, try using `pip install -e .` (from the root directory) instead. The latter works for me. The former doesn't 3. If you face an issue in step-2 (pytorch installation), look up the following link: https://pytorch.org/get-started/previous-versions/ and try installing the the version applicable to you. (Note the installation command for OSX/Linux/Windows might vary. So be careful to choose the right command). 4. If you face an issue in step-3 (pytorch3d installation), Check if pytorch got installed succesfully: `python -c "import torch`; If this doesn't run, it means torch is not installed properly. If this runs, try this - `python -c "import torch; print(torch.cuda.is_available())"`. If you have a gpu based system, and want to use a gpu, this should print "True" on your terminal. If you do not have a gpu, then it should print false. If you have a gpu and it still prints false (and assuming your gpu is working properly), then it means that even though pytorch is installed, only its cpu version is installed. In that case, try installing the gpu enabled version of pytorch (refer step-3) B. If pytorch is installed properly, but pytorch3d isn't you can try installing pytorch3d with pip or conda `pip install pytorch3d` / `conda install -c pytorch3d pytorch3d` . However, if none of these work (which happenned to be the case for me, see step-5 5. You might want to try following the repo's official instructions first (see steps 1-4) before coming to this step. But if following the repo's official instructions does not work (which happenned to be the case for me), then below are the steps which finally worked out for me. Note - there will be some deviation from the repo's official instructions in the below steps A. Install pytorch3d by following their official instructions: https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md . Specifically, I did the following:conda create -n hybrik python=3.9 conda activate hybrik conda install pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia conda install -c fvcore -c iopath -c conda-forge fvcore iopath conda install -c bottler nvidiacub # Anaconda Cloud conda install pytorch3d -c pytorch3dB. `pip install -e .` (from the root directory) C. If you get an error while installing openCV after the above command, open the `setup.py` file, go to line 124, and from the `install_requires` list, remove the `opencv-python==4.1.2.30` part, install openCV separately using `pip install opencv-python` and then again run `pip install -e .` (from the root directory) And hope that it gets built properly I was able to solve the environment related issues using the above steps D. Assuming that the above works, now, if you get some error while running the demo code, the most likely culprits are: (i) Improperly installed pytorch and pytorch3d. To check this, first check if pytorch is installed properly (see step-4 for details on how you can check this). Then, check if pytorch3d is installed properly by using `python -c "import pytorch3d"`; (ii) Numpy version error (Check #184 for a fix). (iii) Some missing pretrained models/files, check the next section for this;Directory structure
The directory structure looks like this
├── assets ├── colab.sh ├── configs ├── examples ├── fetch_data.sh ├── hybrik ├── hybrik.egg-info ├── LICENSE ├── model_files ├── pretrained_models ├── README.md ├── res_dance ├── res_dance_safe ├── res_dance_safe2 ├── scripts └── setup.pyWithin this,
pretrained_modelsdirectory looks like this├── hybrik_hrnet48_w3dpw.pth ├── hybrik_hrnet48_wo3dpw.pth ├── hybrik_hrnet.pth -> /data/amogh/projects/HybrIK/pretrained_models/hybrik_hrnet48_w3dpw.pth ├── hybrik_res34_w3dpw.pth ├── hybrikx_hrnet.pth └── hybrikx_rle_hrnet.pthThe above pretrained models can be downloaded from here as suggested in the installation instructions. After downloading the models, I create a symlink named
hybrik_hrnet.pthwhich links it tohybrik_hrnet48_w3dpw.pth. I did this because the code expects a file namedhybrik_hrnet.pthbut that wasn't available in the downloaded pretrained files. Hence I created this symlink and it worked. (If you are not familiar with symlinks, you can just renamehybrik_hrnet48_w3dpw.pthtohybrik_hrnet.pth). Please refer to #185 for more discussion on this.The
model_filesdirectory looks like this├── basicModel_neutral_lbs_10_207_0_v1.0.0.pkl ├── h36m_mean_beta.npy ├── J_regressor_h36m.npy ├── smplx │ ├── SMPLX_FEMALE.npz │ ├── SMPLX_FEMALE.pkl │ ├── SMPLX_MALE.npz │ ├── SMPLX_MALE.pkl │ ├── SMPLX_NEUTRAL.npz │ └── SMPLX_NEUTRAL.pkl └── smplx_kid_template.npyHere, the smplx files were downloaded from smpl-x's website, the
basicModel_neutral_lbs_10_207_0_v1.0.0.pklfrom smplify's website, thesmplx_kid_template.npyfrom agora's websiteFor
J_regressor_h36m.npyandh36m_mean_beta.npy, I first downloaded the necessary files using this script, following SPEC's instructions. (Note this downloads some extra files. We only needJ_regressor_h36m.npyandsmpl_mean_params.npzfrom this.The script shared above, downloads
smpl_mean_params.npzwhile this repo needsh36m_mean_beta.npy. To geth36m_mean_beta.npyfromsmpl_mean_params.npz, I got the mean betas from thesmpl_mean_params.npzfile and dumped it as anpyfile in themodel_filesdirectory. This can be done as followsx=np.load("smpl_mean_params.npz") \#provide the correct path to the mean_params file print(x.files) \# To see the contents of the file print(x['shape']) \# To see the contents of the mean shapes (betas) np.save("h36m_mean_beta.npy", x['shape']) \# save the mean beta parameters.After this, move the
h36m_mean_beta.npyto the right location inside themodel_filesdirectory.After this, I ran
python scripts/demo_video.py --video-name examples/dance.mp4 --out-dir res_dance --save-pk --save-imgas suggested in the official instructions, and it worked for me. Hope it works for you too. Best of luck!
Hi, I followed the instructions to set the environment and install pytorch3d, but when I try to install it using conda I get conflicts. Could you help me solve this problem? What do you recommend me in this case? Thanks!
The following specifications were found to be incompatible with your system:
Your installed version is: 2.31
Dipankar1997161
commented
8 months ago I faced some trouble while trying to setup the environment to run the code. Specially, with pytorch3d. So I am sharing the steps using which I was able to finally set up the code. Note that, till now I have only tried out the demo code. So I still can't confirm if the below steps will be sufficient for running the training code also. Also, if this doesn't work, please be sure to look at other comments also (for example, it worked for me with cuda 11.6, while someone else has shared there suggestions below that it worked for them with cuda 11.7). System Details: Ubuntu 18.04 with 4 Nvidia 2080 Ti (Remote server)
Environment Setup
Note: Steps: 1-4 did not work for me. So you might want to directly jump to step-5
1. Try following the repo's official [installation instructions](https://github.com/Jeff-sjtu/HybrIK#installation-instructions). If they work, great! 2. If you face an issue in step-5, when running `python setup.py develop`, try using `pip install -e .` (from the root directory) instead. The latter works for me. The former doesn't 3. If you face an issue in step-2 (pytorch installation), look up the following link: https://pytorch.org/get-started/previous-versions/ and try installing the the version applicable to you. (Note the installation command for OSX/Linux/Windows might vary. So be careful to choose the right command). 4. If you face an issue in step-3 (pytorch3d installation), Check if pytorch got installed succesfully: `python -c "import torch`; If this doesn't run, it means torch is not installed properly. If this runs, try this - `python -c "import torch; print(torch.cuda.is_available())"`. If you have a gpu based system, and want to use a gpu, this should print "True" on your terminal. If you do not have a gpu, then it should print false. If you have a gpu and it still prints false (and assuming your gpu is working properly), then it means that even though pytorch is installed, only its cpu version is installed. In that case, try installing the gpu enabled version of pytorch (refer step-3) B. If pytorch is installed properly, but pytorch3d isn't you can try installing pytorch3d with pip or conda `pip install pytorch3d` / `conda install -c pytorch3d pytorch3d` . However, if none of these work (which happenned to be the case for me, see step-5 5. You might want to try following the repo's official instructions first (see steps 1-4) before coming to this step. But if following the repo's official instructions does not work (which happenned to be the case for me), then below are the steps which finally worked out for me. Note - there will be some deviation from the repo's official instructions in the below steps A. Install pytorch3d by following their official instructions: https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md . Specifically, I did the following:conda create -n hybrik python=3.9 conda activate hybrik conda install pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia conda install -c fvcore -c iopath -c conda-forge fvcore iopath conda install -c bottler nvidiacub # Anaconda Cloud conda install pytorch3d -c pytorch3dB. `pip install -e .` (from the root directory) C. If you get an error while installing openCV after the above command, open the `setup.py` file, go to line 124, and from the `install_requires` list, remove the `opencv-python==4.1.2.30` part, install openCV separately using `pip install opencv-python` and then again run `pip install -e .` (from the root directory) And hope that it gets built properly I was able to solve the environment related issues using the above steps D. Assuming that the above works, now, if you get some error while running the demo code, the most likely culprits are: (i) Improperly installed pytorch and pytorch3d. To check this, first check if pytorch is installed properly (see step-4 for details on how you can check this). Then, check if pytorch3d is installed properly by using `python -c "import pytorch3d"`; (ii) Numpy version error (Check #184 for a fix). (iii) Some missing pretrained models/files, check the next section for this;Directory structure
The directory structure looks like this
├── assets ├── colab.sh ├── configs ├── examples ├── fetch_data.sh ├── hybrik ├── hybrik.egg-info ├── LICENSE ├── model_files ├── pretrained_models ├── README.md ├── res_dance ├── res_dance_safe ├── res_dance_safe2 ├── scripts └── setup.pyWithin this,
pretrained_modelsdirectory looks like this├── hybrik_hrnet48_w3dpw.pth ├── hybrik_hrnet48_wo3dpw.pth ├── hybrik_hrnet.pth -> /data/amogh/projects/HybrIK/pretrained_models/hybrik_hrnet48_w3dpw.pth ├── hybrik_res34_w3dpw.pth ├── hybrikx_hrnet.pth └── hybrikx_rle_hrnet.pthThe above pretrained models can be downloaded from here as suggested in the installation instructions. After downloading the models, I create a symlink named
hybrik_hrnet.pthwhich links it tohybrik_hrnet48_w3dpw.pth. I did this because the code expects a file namedhybrik_hrnet.pthbut that wasn't available in the downloaded pretrained files. Hence I created this symlink and it worked. (If you are not familiar with symlinks, you can just renamehybrik_hrnet48_w3dpw.pthtohybrik_hrnet.pth). Please refer to #185 for more discussion on this. Themodel_filesdirectory looks like this├── basicModel_neutral_lbs_10_207_0_v1.0.0.pkl ├── h36m_mean_beta.npy ├── J_regressor_h36m.npy ├── smplx │ ├── SMPLX_FEMALE.npz │ ├── SMPLX_FEMALE.pkl │ ├── SMPLX_MALE.npz │ ├── SMPLX_MALE.pkl │ ├── SMPLX_NEUTRAL.npz │ └── SMPLX_NEUTRAL.pkl └── smplx_kid_template.npyHere, the smplx files were downloaded from smpl-x's website, the
basicModel_neutral_lbs_10_207_0_v1.0.0.pklfrom smplify's website, thesmplx_kid_template.npyfrom agora's website ForJ_regressor_h36m.npyandh36m_mean_beta.npy, I first downloaded the necessary files using this script, following SPEC's instructions. (Note this downloads some extra files. We only needJ_regressor_h36m.npyandsmpl_mean_params.npzfrom this. The script shared above, downloadssmpl_mean_params.npzwhile this repo needsh36m_mean_beta.npy. To geth36m_mean_beta.npyfromsmpl_mean_params.npz, I got the mean betas from thesmpl_mean_params.npzfile and dumped it as anpyfile in themodel_filesdirectory. This can be done as followsx=np.load("smpl_mean_params.npz") \#provide the correct path to the mean_params file print(x.files) \# To see the contents of the file print(x['shape']) \# To see the contents of the mean shapes (betas) np.save("h36m_mean_beta.npy", x['shape']) \# save the mean beta parameters.After this, move the
h36m_mean_beta.npyto the right location inside themodel_filesdirectory. After this, I ranpython scripts/demo_video.py --video-name examples/dance.mp4 --out-dir res_dance --save-pk --save-imgas suggested in the official instructions, and it worked for me. Hope it works for you too. Best of luck!Hi, I followed the instructions to set the environment and install pytorch3d, but when I try to install it using conda I get conflicts. Could you help me solve this problem? What do you recommend me in this case? Thanks!
The following specifications were found to be incompatible with your system:
- feature:/linux-64::__cuda==11.8=0
- feature:/linux-64::__glibc==2.31=0
- feature:|@/linux-64::__cuda==11.8=0
- feature:|@/linux-64::__glibc==2.31=0
- brotli-python -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- cffi -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- cryptography -> libgcc-ng -> __glibc[version='>=2.17']
- freetype -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- giflib -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- intel-openmp -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- jpeg -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- lcms2 -> libgcc-ng[version='>=7.3.0'] -> __glibc[version='>=2.17']
- lerc -> libgcc-ng[version='>=7.5.0'] -> __glibc[version='>=2.17']
- libdeflate -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- libffi -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- libgcc-ng -> __glibc[version='>=2.17']
- libpng -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- libstdcxx-ng -> __glibc[version='>=2.17']
- libtiff -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- libwebp -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- libwebp-base -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- lz4-c -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- mkl -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- mkl-service -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- mkl_random -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- ncurses -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- numpy -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- numpy-base -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- openjpeg -> libgcc-ng[version='>=7.5.0'] -> __glibc[version='>=2.17']
- openssl -> libgcc-ng[version='>=7.5.0'] -> __glibc[version='>=2.17']
- pillow -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- python=3.9 -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- pytorch3d -> pytorch==2.0.1 -> __cuda[version='>=11.8']
- pytorch3d -> torchvision[version='>=0.5'] -> __glibc[version='>=2.17,<3.0.a0']
- pyyaml -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- readline -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- sqlite -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- tbb -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- tk -> libgcc-ng[version='>=7.5.0'] -> __glibc[version='>=2.17']
- torchvision -> __glibc[version='>=2.17,<3.0.a0']
- torchvision -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- torchvision -> pytorch -> __cuda[version='>=11.8']
- xz -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- yaml -> libgcc-ng[version='>=9.4.0'] -> __glibc[version='>=2.17']
- zlib -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
- zstd -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
Your installed version is: 2.31
Thank you for the response, I got another question. May I know how many 3d keypoints where detected and smpl joints after you run the demo? Since it used the j_regressor from h36m. Is it 17 keypoints only??
I have my own data and wish to train hybrik but it has 18-25 joints like openpose 😅 so kinda in the mid state if hybrik is the right choice.
Could you inform me @sebastianopazo1
Ulf3000
commented
7 months ago conda install pytorch3d -c pytorch3d .. which channel is this on ?
Dipankar1997161
commented
7 months ago conda install pytorch3d -c pytorch3d .. which channel is this on ?
Get the latest one, mostly from forge.
Or install via pip
Ulf3000
commented
7 months ago i used pip install "git+https://github.com/facebookresearch/pytorch3d.git@stable"
instead of ssh . that worked
I faced some trouble while trying to setup the environment to run the code. Specially, with pytorch3d. So I am sharing the steps using which I was able to finally set up the code. Note that, till now I have only tried out the demo code. So I still can't confirm if the below steps will be sufficient for running the training code also. Also, if this doesn't work, please be sure to look at other comments also (for example, it worked for me with cuda 11.6, while someone else has shared there suggestions below that it worked for them with cuda 11.7).
System Details: Ubuntu 18.04 with 4 Nvidia 2080 Ti (Remote server)
Environment Setup
Note: Steps: 1-4 did not work for me. So you might want to directly jump to step-5
Try following the repo's official installation instructions. If they work, great!
If you face an issue in step-5, when running
python setup.py develop, try usingpip install -e .(from the root directory) instead. The latter works for me. The former doesn'tIf you face an issue in step-2 (pytorch installation), look up the following link: https://pytorch.org/get-started/previous-versions/ and try installing the the version applicable to you. (Note the installation command for OSX/Linux/Windows might vary. So be careful to choose the right command).
If you face an issue in step-3 (pytorch3d installation), Check if pytorch got installed succesfully:
python -c "import torch; If this doesn't run, it means torch is not installed properly. If this runs, try this -python -c "import torch; print(torch.cuda.is_available())". If you have a gpu based system, and want to use a gpu, this should print "True" on your terminal. If you do not have a gpu, then it should print false. If you have a gpu and it still prints false (and assuming your gpu is working properly), then it means that even though pytorch is installed, only its cpu version is installed. In that case, try installing the gpu enabled version of pytorch (refer step-3) B. If pytorch is installed properly, but pytorch3d isn't you can try installing pytorch3d with pip or condapip install pytorch3d/conda install -c pytorch3d pytorch3d. However, if none of these work (which happenned to be the case for me, see step-5You might want to try following the repo's official instructions first (see steps 1-4) before coming to this step. But if following the repo's official instructions does not work (which happenned to be the case for me), then below are the steps which finally worked out for me. Note - there will be some deviation from the repo's official instructions in the below steps
A. Install pytorch3d by following their official instructions: https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md . Specifically, I did the following:
B.
pip install -e .(from the root directory) C. If you get an error while installing openCV after the above command, open thesetup.pyfile, go to line 124, and from theinstall_requireslist, remove theopencv-python==4.1.2.30part, install openCV separately usingpip install opencv-pythonand then again runpip install -e .(from the root directory) And hope that it gets built properly I was able to solve the environment related issues using the above steps D. Assuming that the above works, now, if you get some error while running the demo code, the most likely culprits are: (i) Improperly installed pytorch and pytorch3d. To check this, first check if pytorch is installed properly (see step-4 for details on how you can check this). Then, check if pytorch3d is installed properly by usingpython -c "import pytorch3d"; (ii) Numpy version error (Check #184 for a fix). (iii) Some missing pretrained models/files, check the next section for this;Directory structure
The directory structure looks like this
Within this,
pretrained_modelsdirectory looks like thisThe above pretrained models can be downloaded from here as suggested in the installation instructions. After downloading the models, I create a symlink named
hybrik_hrnet.pthwhich links it tohybrik_hrnet48_w3dpw.pth. I did this because the code expects a file namedhybrik_hrnet.pthbut that wasn't available in the downloaded pretrained files. Hence I created this symlink and it worked. (If you are not familiar with symlinks, you can just renamehybrik_hrnet48_w3dpw.pthtohybrik_hrnet.pth). Please refer to #185 for more discussion on this.The
model_filesdirectory looks like thisHere, the smplx files were downloaded from smpl-x's website, the
basicModel_neutral_lbs_10_207_0_v1.0.0.pklfrom smplify's website, thesmplx_kid_template.npyfrom agora's websiteFor
J_regressor_h36m.npyandh36m_mean_beta.npy, I first downloaded the necessary files using this script, following SPEC's instructions. (Note this downloads some extra files. We only needJ_regressor_h36m.npyandsmpl_mean_params.npzfrom this.The script shared above, downloads
smpl_mean_params.npzwhile this repo needsh36m_mean_beta.npy. To geth36m_mean_beta.npyfromsmpl_mean_params.npz, I got the mean betas from thesmpl_mean_params.npzfile and dumped it as anpyfile in themodel_filesdirectory. This can be done as followsAfter this, move the
h36m_mean_beta.npyto the right location inside themodel_filesdirectory.After this, I ran
python scripts/demo_video.py --video-name examples/dance.mp4 --out-dir res_dance --save-pk --save-imgas suggested in the official instructions, and it worked for me. Hope it works for you too. Best of luck!