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| from model.rotation2xyz import Rotation2xyz | |
| import numpy as np | |
| from trimesh import Trimesh | |
| import os | |
| import torch | |
| from visualize.simplify_loc2rot import joints2smpl | |
| class npy2obj: | |
| def __init__(self, npy_path, sample_idx, rep_idx, device=0, cuda=True): | |
| self.npy_path = npy_path | |
| self.motions = np.load(self.npy_path, allow_pickle=True) | |
| if self.npy_path.endswith('.npz'): | |
| self.motions = self.motions['arr_0'] | |
| self.motions = self.motions[None][0] | |
| self.rot2xyz = Rotation2xyz(device='cpu') | |
| self.faces = self.rot2xyz.smpl_model.faces | |
| self.bs, self.njoints, self.nfeats, self.nframes = self.motions['motion'].shape | |
| self.opt_cache = {} | |
| self.sample_idx = sample_idx | |
| self.total_num_samples = self.motions['num_samples'] | |
| self.rep_idx = rep_idx | |
| self.absl_idx = self.rep_idx*self.total_num_samples + self.sample_idx | |
| self.num_frames = self.motions['motion'][self.absl_idx].shape[-1] | |
| self.j2s = joints2smpl(num_frames=self.num_frames, device_id=device, cuda=cuda) | |
| if self.nfeats == 3: | |
| print(f'Running SMPLify For sample [{sample_idx}], repetition [{rep_idx}], it may take a few minutes.') | |
| motion_tensor, opt_dict = self.j2s.joint2smpl(self.motions['motion'][self.absl_idx].transpose(2, 0, 1)) # [nframes, njoints, 3] | |
| self.motions['motion'] = motion_tensor.cpu().numpy() | |
| elif self.nfeats == 6: | |
| self.motions['motion'] = self.motions['motion'][[self.absl_idx]] | |
| self.bs, self.njoints, self.nfeats, self.nframes = self.motions['motion'].shape | |
| self.real_num_frames = self.motions['lengths'][self.absl_idx] | |
| self.vertices = self.rot2xyz(torch.tensor(self.motions['motion']), mask=None, | |
| pose_rep='rot6d', translation=True, glob=True, | |
| jointstype='vertices', | |
| # jointstype='smpl', # for joint locations | |
| vertstrans=True) | |
| self.root_loc = self.motions['motion'][:, -1, :3, :].reshape(1, 1, 3, -1) | |
| self.vertices += self.root_loc | |
| def get_vertices(self, sample_i, frame_i): | |
| return self.vertices[sample_i, :, :, frame_i].squeeze().tolist() | |
| def get_trimesh(self, sample_i, frame_i): | |
| return Trimesh(vertices=self.get_vertices(sample_i, frame_i), | |
| faces=self.faces) | |
| def save_obj(self, save_path, frame_i): | |
| mesh = self.get_trimesh(0, frame_i) | |
| with open(save_path, 'w') as fw: | |
| mesh.export(fw, 'obj') | |
| return save_path | |
| def save_npy(self, save_path): | |
| data_dict = { | |
| 'motion': self.motions['motion'][0, :, :, :self.real_num_frames], | |
| 'thetas': self.motions['motion'][0, :-1, :, :self.real_num_frames], | |
| 'root_translation': self.motions['motion'][0, -1, :3, :self.real_num_frames], | |
| 'faces': self.faces, | |
| 'vertices': self.vertices[0, :, :, :self.real_num_frames], | |
| 'text': self.motions['text'][0], | |
| 'length': self.real_num_frames, | |
| } | |
| np.save(save_path, data_dict) | |