EricGuo5513/momask-codes

A mean and std computation and use question

Opened this issue · 2 comments

RobinWitch commented

Hello, what a good work!
While I have a question when I retrain rvqvae, it quite diffuse me a lot.
Why in this place we need to recalculate std?

momask-codes/data/t2m_dataset.py

Lines 41 to 68 in d4d3412

if opt.is_train:
# root_rot_velocity (B, seq_len, 1)
std[0:1] = std[0:1] / opt.feat_bias
# root_linear_velocity (B, seq_len, 2)
std[1:3] = std[1:3] / opt.feat_bias
# root_y (B, seq_len, 1)
std[3:4] = std[3:4] / opt.feat_bias
# ric_data (B, seq_len, (joint_num - 1)*3)
std[4: 4 + (joints_num - 1) * 3] = std[4: 4 + (joints_num - 1) * 3] / 1.0
# rot_data (B, seq_len, (joint_num - 1)*6)
std[4 + (joints_num - 1) * 3: 4 + (joints_num - 1) * 9] = std[4 + (joints_num - 1) * 3: 4 + (
joints_num - 1) * 9] / 1.0
# local_velocity (B, seq_len, joint_num*3)
std[4 + (joints_num - 1) * 9: 4 + (joints_num - 1) * 9 + joints_num * 3] = std[
4 + (joints_num - 1) * 9: 4 + (
joints_num - 1) * 9 + joints_num * 3] / 1.0
# foot contact (B, seq_len, 4)
std[4 + (joints_num - 1) * 9 + joints_num * 3:] = std[
4 + (
joints_num - 1) * 9 + joints_num * 3:] / opt.feat_bias
assert 4 + (joints_num - 1) * 9 + joints_num * 3 + 4 == mean.shape[-1]
np.save(pjoin(opt.meta_dir, 'mean.npy'), mean)
np.save(pjoin(opt.meta_dir, 'std.npy'), std)
self.mean = mean
self.std = std
print("Total number of motions {}, snippets {}".format(len(self.data), self.cumsum[-1]))

EricGuo5513 commented
RobinWitch commented

In intuitive, I think amplifying the importance of certain motion features we should plus opt.feat_bias instead of dividing? The default value of opt.feat_bias is 5.