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