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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 |
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import torch |
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from visualize.simplify_loc2rot import joints2smpl |
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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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} |
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np.save(save_path, data_dict) |
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