i. JddlmZddlZddlmZ d dededeededef d Zy) )ListN)Tensor vertices_pred vertices_gt mouth_map validate_argsreturnc|r|jdk7s|jdk7r&td|jd|jd|jdd|jddk7r&td|jd|jd|s td t||jdk\r(td t|d |jddt |jd |jd }|d|}|d|}|dd|ddf|dd|ddfz }t j |d zd}t j|dj}t j|S)aCompute Lip Vertex Error (LVE) for 3D talking head evaluation. The Lip Vertex Error (LVE) metric evaluates the quality of lip synchronization in 3D facial animations by measuring the maximum Euclidean distance (L2 error) between corresponding lip vertices of the generated and ground truth meshes for each frame. The metric is defined as: .. math:: \text{LVE} = \frac{1}{N} \sum_{i=1}^{N} \max_{v \in \text{lip}} \|x_{i,v} - \hat{x}_{i,v}\|_2^2 where :math:`N` is the number of frames, :math:`x_{i,v}` represents the 3D coordinates of vertex :math:`v` in the lip region of the ground truth frame :math:`i`, and :math:`\hat{x}_{i,v}` represents the corresponding vertex in the predicted frame. The metric computes the maximum squared L2 distance between corresponding lip vertices for each frame and averages across all frames. A lower LVE value indicates better lip synchronization quality. Args: vertices_pred: Predicted vertices tensor of shape (T, V, 3) where T is number of frames, V is number of vertices, and 3 represents XYZ coordinates vertices_gt: Ground truth vertices tensor of shape (T', V, 3) where T' can be different from T mouth_map: List of vertex indices corresponding to the mouth region validate_args: bool indicating if input arguments and tensors should be validated for correctness. Set to ``False`` for faster computations. Returns: torch.Tensor: Scalar tensor containing the mean LVE value across all frames Raises: ValueError: If the number of dimensions of `vertices_pred` or `vertices_gt` is not 3. If vertex dimensions (V) or coordinate dimensions (3) don't match If ``mouth_map`` is empty or contains invalid indices Example: >>> import torch >>> from torchmetrics.functional.multimodal import lip_vertex_error >>> vertices_pred = torch.randn(10, 100, 3, generator=torch.manual_seed(42)) >>> vertices_gt = torch.randn(10, 100, 3, generator=torch.manual_seed(43)) >>> mouth_map = [0, 1, 2, 3, 4] >>> lip_vertex_error(vertices_pred, vertices_gt, mouth_map) tensor(12.7688) zIExpected both vertices_pred and vertices_gt to have 3 dimensions but got z and z dimensions respectively.NzdExpected vertices_pred and vertices_gt to have same vertex and coordinate dimensions but got shapes .zmouth_map cannot be empty.z5mouth_map contains invalid vertex indices. Max index z# is larger than number of vertices r)dim) ndim ValueErrorshapemaxmintorchsumvaluesmean)rrrr min_framesdiffsq_dist max_per_frames {/Volumes/fast/ai/experiments/voice-extract-mac/.venv/lib/python3.12/site-packages/torchmetrics/functional/multimodal/lve.pylip_vertex_errorrs^    "k&6&6!&;[ %%&eK,<,<+==VX    qr "k&7&7&; ;'--.eK4E4E3FaI 9: : y>]003 3GIGWX&&3&9&9!&<%=Q@  ]((+[->->q-ABJ!+:.Mkz*K q)Q '-9a*H HDiiaR(GIIg1-44M ::m $$)T)typingrrrintboolrr rr%sR  I%I%I%CyI% I%  I%r