### Install SMPL-X from Source Source: https://github.com/vchoutas/smplx/blob/main/README.md Clones the SMPL-X repository and installs it locally using the setup.py script. ```shell git clone https://github.com/vchoutas/smplx python setup.py install ``` -------------------------------- ### Install SMPL-X from PyPi Source: https://github.com/vchoutas/smplx/blob/main/README.md Installs the SMPL-X library with all optional dependencies using pip. ```shell pip install smplx[all] ``` -------------------------------- ### SMPL-H Setup for AMASS Source: https://github.com/vchoutas/smplx/blob/main/tools/README.md Instructions for setting up SMPL-H models for use with AMASS, including downloading specific versions and merging parameters. This process involves cloning the smplx repository, downloading SMPL-H and MANO models, merging them using a provided script, and copying the final model to the correct location. ```bash - Download the zip folder from "Models & Code" and extract it to get the folder `mano_v1_2` - Download the zip folder from "Extended SMPL+H model" and extract it to get the folder `smplh` $ git clone https://github.com/vchoutas/smplx.git $ cd smplx $ python tools/merge_smplh_mano.py \ --smplh-fn /path/to/smplh/female/model.npz \ --mano-left-fn /path/to/mano_v1_2/models/MANO_LEFT.pkl \ --mano-right-fn /path/to/mano_v1_2/models/MANO_RIGHT.pkl \ --output-folder /path/to/smplh/merged cp /path/to/smplh/merged/model.pkl /path/to/smplx_models/smplh/SMPLH_FEMALE.pkl ``` -------------------------------- ### Run SMPLX Demo Source: https://github.com/vchoutas/smplx/blob/main/README.md Example command to run the SMPLX demo script for visualizing results. Requires the model folder and optionally specifies joint plotting and gender. ```bash python examples/demo.py --model-folder $SMPLX_FOLDER --plot-joints=True --gender="neutral" ``` -------------------------------- ### Clone SMPL-X Repository Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Clones the SMPL-X repository from GitHub to your local machine. This is the first step to get the project files. ```Shell git clone https://github.com/vchoutas/smplx.git ``` -------------------------------- ### Install SMPL-X Requirements Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Installs all necessary Python packages required for the SMPL-X project using the requirements.txt file. ```Shell pip install -r requirements.txt ``` -------------------------------- ### Remove Chumpy Objects Source: https://github.com/vchoutas/smplx/blob/main/tools/README.md Removes Chumpy objects from model data using a Python script. Requires Chumpy to be installed in a Python 2 virtual environment. Specify input model files and an output folder. ```bash python tools/clean_ch.py --input-models path-to-models/*.pkl --output-folder output-folder ``` -------------------------------- ### Model Loading Structure Source: https://github.com/vchoutas/smplx/blob/main/README.md Illustrates the expected directory structure for storing SMPL, SMPL+H, MANO, and SMPL-X model parameters. ```bash models ├── smpl │ ├── SMPL_FEMALE.pkl │ └── SMPL_MALE.pkl │ └── SMPL_NEUTRAL.pkl ├── smplh │ ├── SMPLH_FEMALE.pkl │ └── SMPLH_MALE.pkl ├── mano | ├── MANO_RIGHT.pkl | └── MANO_LEFT.pkl └── smplx ├── SMPLX_FEMALE.npz ├── SMPLX_FEMALE.pkl ├── SMPLX_MALE.npz ├── SMPLX_MALE.pkl ├── SMPLX_NEUTRAL.npz └── SMPLX_NEUTRAL.pkl ``` -------------------------------- ### Visualize MANO Correspondences Source: https://github.com/vchoutas/smplx/blob/main/README.md Command to visualize vertex correspondences between MANO and SMPL-X models. Requires the model folder and a correspondence file. ```bash python examples/vis_mano_vertices.py --model-folder $SMPLX_FOLDER --corr-fname correspondences/MANO_SMPLX_vertex_ids.pkl ``` -------------------------------- ### Visualize FLAME Correspondences Source: https://github.com/vchoutas/smplx/blob/main/README.md Command to visualize vertex correspondences between FLAME and SMPL-X models. Requires the model folder and a correspondence file. ```bash python examples/vis_flame_vertices.py --model-folder $SMPLX_FOLDER --corr-fname correspondences/SMPL-X__FLAME_vertex_ids.npy ``` -------------------------------- ### Model Loading and Switching Source: https://github.com/vchoutas/smplx/blob/main/README.md Demonstrates how to load and switch between different SMPL models (SMPL-X, SMPL+H, SMPL, MANO) by changing model path or type parameters. It also mentions pre-processing steps for SMPL and SMPL+H models. ```python # Example of loading SMPL-X # smplx_model = SMPLX(model_path='path/to/smplx/model', model_type='smplx') # Example of loading SMPL+H # smplh_model = SMPLX(model_path='path/to/smplh/model', model_type='smplh') # Example of loading SMPL # smpl_model = SMPLX(model_path='path/to/smpl/model', model_type='smpl') # Note: Before using SMPL and SMPL+H, follow instructions in tools/README.md # to remove Chumpy objects and merge MANO parameters with SMPL+H. ``` -------------------------------- ### Merge SMPL-H and MANO Parameters Source: https://github.com/vchoutas/smplx/blob/main/tools/README.md Merges SMPL-H and MANO parameters into a single file for use with the PyTorch SMPL-H module. Requires agreeing to licenses and downloading models. Specify paths to SMPL-H and MANO files, and an output folder. ```bash python tools/merge_smplh_mano.py --smplh-fn SMPLH_FOLDER/SMPLH_GENDER.pkl \ --mano-left-fn MANO_FOLDER/MANO_LEFT.pkl \ --mano-right-fn MANO_FOLDER/MANO_RIGHT.pkl \ --output-folder OUTPUT_FOLDER ``` -------------------------------- ### Visualize Correspondences Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Visualizes correspondences between SMPL and SMPL-X models. Points with similar colors indicate correspondence. Requires specifying the path to SMPL colors. ```Shell python vis_correspondences.py --exp-cfg configs/smpl2smplx.yaml --exp-opts colors_path PATH_TO_SMPL_COLORS ``` -------------------------------- ### Transferring Models within SMPL Family Source: https://github.com/vchoutas/smplx/blob/main/README.md Provides information on code released for transferring between models in the SMPL family. Details on the code and extraction of mappings are available in separate README files. ```shell # Refer to ./transfer_model/README.md for code details. # Refer to ./transfer_model/docs/transfer.md for mapping explanations. ``` -------------------------------- ### SMPL-X Citation Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Citation for the SMPL-X model. ```BibTeX @inproceedings{SMPL-X:2019, title = {Expressive Body Capture: 3D Hands, Face, and Body from a Single Image}, author = {Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.}, booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)}, year = {2019} } ``` -------------------------------- ### MANO Citation Source: https://github.com/vchoutas/smplx/blob/main/README.md BibTeX entry for citing the MANO model and its associated research. ```bibtex @article{MANO:SIGGRAPHASIA:2017, title = {Embodied Hands: Modeling and Capturing Hands and Bodies Together}, author = {Romero, Javier and Tzionas, Dimitrios and Black, Michael J.}, journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)}, volume = {36}, number = {6}, series = {245:1--245:17}, month = nov, year = {2017}, month_numeric = {11} } ``` -------------------------------- ### Transfer Model Parameters (SMPL-H to SMPL-X) Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Executes the model parameter transfer from SMPL-H to SMPL-X using a specified configuration file. This is a core command for converting between model types. ```Python python -m transfer_model --exp-cfg config_files/smplh2smplx_as.yaml ``` -------------------------------- ### SMPL-X Citation Source: https://github.com/vchoutas/smplx/blob/main/README.md BibTeX entry for citing the SMPL-X model and its associated research. ```bibtex @inproceedings{SMPL-X:2019, title = {Expressive Body Capture: 3D Hands, Face, and Body from a Single Image}, author = {Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.}, booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)}, year = {2019} } ``` -------------------------------- ### SMPL-X Vertex Calculation from SMPL Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/docs/transfer.md This snippet demonstrates how to compute a vertex in the SMPL-X topology using barycentric coordinates and vertex indices from a corresponding SMPL triangle. It assumes pre-computed correspondences and SMPL vertex data. ```python def compute_smplx_vertex(smpl_triangle_indices, smpl_vertices, barycentric_coords, vertex_mask): # smpl_triangle_indices: indices of the 3 vertices forming the SMPL triangle # smpl_vertices: array of SMPL vertices # barycentric_coords: [a_i, b_i, c_i] for the SMPL-X vertex # vertex_mask: mask indicating if the vertex correspondence is valid if not vertex_mask: return None v0_smpl = smpl_vertices[smpl_triangle_indices[0]] v1_smpl = smpl_vertices[smpl_triangle_indices[1]] v2_smpl = smpl_vertices[smpl_triangle_indices[2]] a, b, c = barycentric_coords v_smplx = a * v0_smpl + b * v1_smpl + c * v2_smpl return v_smplx ``` -------------------------------- ### SMPL Citation Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Citation for the SMPL model. ```BibTeX @article{SMPL:2015, author = {Loper, Matthew and Mahmood, Naureen and Romero, Javier and Pons-Moll, Gerard and Black, Michael J.}, title = {{SMPL}: A Skinned Multi-Person Linear Model}, journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)}, month = oct, number = {6}, pages = {248:1--248:16}, publisher = {ACM}, volume = {34}, year = {2015} } ``` -------------------------------- ### SMPL-X to SMPL Parameter Optimization Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/docs/transfer.md This section outlines the optimization process for recovering SMPL-X parameters (pose, shape, expression, translation) by fitting the SMPL-X model to SMPL annotations. It includes loss functions for pose, translation, and overall fit. ```APIDOC SMPL-X Parameter Optimization: Objective: Recover SMPL-X parameters (pose $\theta$, shape $\beta$, expression $\psi$, translation $\gamma$) that best fit SMPL annotations. Process: 1. Establish correspondences between SMPL and SMPL-X meshes. 2. Compute SMPL-X vertices ($v_i^{SMPL-X}$) based on SMPL topology and correspondences. 3. Iteratively optimize parameters using the following loss functions: - Pose Optimization (3D edge term): $L_1(\theta) = \sum_{(i, j) \in \mathcal{E}} m_i m_j \left\lVert(v_i - v_j) - (\hat{v}_i - \hat{v}_j) \right\rVert_2^2$ - $\mathcal{E}$: Set of valid edges (both endpoints valid). - $m_i, m_j$: Validity masks for vertices i and j. - $v_i, v_j$: SMPL-X vertices corresponding to SMPL edge endpoints. - $\hat{v}_i, \hat{v}_j$: SMPL vertices forming the edge. - Translation Optimization: $L_2({\gamma}) = \sum_{i} m_i \left\lVert v_i - \hat{v}_i \right\rVert$ - $v_i$: SMPL-X vertex. - $\hat{v}_i$: Corresponding SMPL vertex. - $m_i$: Validity mask for vertex i. - Full Parameter Optimization: $L_3((\theta, \beta, \psi, \gamma)) = \sum_{i} m_i \left\lVert v_i - \hat{v}_i \right\rVert_2^2$ - Minimizes the difference between SMPL-X vertices and corresponding SMPL vertices across all valid points. ``` -------------------------------- ### SMPL Citation Source: https://github.com/vchoutas/smplx/blob/main/README.md BibTeX entry for citing the SMPL model and its associated research. ```bibtex @article{SMPL:2015, author = {Loper, Matthew and Mahmood, Naureen and Romero, Javier and Pons-Moll, Gerard and Black, Michael J.}, title = {{SMPL}: A Skinned Multi-Person Linear Model}, journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)}, month = oct, number = {6}, pages = {248:1--248:16}, publisher = {ACM}, volume = {34}, year = {2015} } ``` -------------------------------- ### MANO Citation Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Citation for the MANO (Embodied Hands) model. ```BibTeX @article{MANO:SIGGRAPHASIA:2017, title = {Embodied Hands: Modeling and Capturing Hands and Bodies Together}, author = {Romero, Javier and Tzionas, Dimitrios and Black, Michael J.}, journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)}, volume = {36}, number = {6}, pages = {245:1--245:17}, series = {245:1--245:17}, publisher = {ACM}, month = nov, year = {2017}, url = {http://doi.acm.org/10.1145/3130800.3130883}, month_numeric = {11} } ``` -------------------------------- ### Generate OBJ Files from Motion Data Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts motion data (e.g., from AMASS npz files) into a series of OBJ files, which are used as input for the transfer process. Requires specifying model and motion file locations. ```Python python write_obj.py --model-folder ../models/ --motion-file ../transfer_data/support_data/github_data/amass_sample.npz --output-folder ../transfer_data/meshes/amass_sample/ ``` -------------------------------- ### Merge Output OBJ Files into Motion Sequence Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Merges individual OBJ files (output from the transfer process) into a single motion sequence file, compatible with SMPL-X AMASS archives. Requires specifying the output directory. ```Python python merge_output.py --gender neutral ../output ``` -------------------------------- ### Transfer Model Parameters (SMPL to SMPL-X) Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts SMPL model parameters to SMPL-X parameters. This command utilizes a YAML configuration file to specify input and output paths for the conversion. ```Python python -m transfer_model --exp-cfg config_files/smpl2smplx.yaml ``` -------------------------------- ### Convert SMPL+H to SMPL Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts SMPL+H meshes to SMPL parameters. Requires meshes in ply or obj format. Hand information will be lost during this conversion. ```Shell python -m transfer_model --exp-cfg config_files/smplh2smpl.yaml ``` -------------------------------- ### Convert SMPL+H to SMPL-X Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts SMPL+H meshes to SMPL-X parameters. Requires meshes in ply or obj format. This conversion includes hand and face parameters. ```Shell python -m transfer_model --exp-cfg config_files/smplh2smplx.yaml ``` -------------------------------- ### Convert SMPL-X to SMPL Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts SMPL-X meshes to SMPL parameters. Requires meshes in ply or obj format. Note that hand and face parameters are lost in this conversion. ```Shell python main.py --exp-cfg config_files/smplx2smpl.yaml ``` -------------------------------- ### Convert SMPL to SMPL+H Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts SMPL meshes to SMPL+H parameters. Requires meshes in ply or obj format. This process adds hand information. ```Shell python -m transfer_model --exp-cfg config_files/smpl2smplh.yaml ``` -------------------------------- ### Convert SMPL-X to SMPL+H Source: https://github.com/vchoutas/smplx/blob/main/transfer_model/README.md Converts SMPL-X meshes to SMPL+H parameters. Requires meshes in ply or obj format. Jaw pose and expression parameters should not be used when generating the input meshes. ```Shell python -m transfer_model --exp-cfg config_files/smplx2smplh.yaml ``` === COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.