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License: MIT License
Implementation of Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis
License: MIT License
Is the skeleton (standard.bvh) that is used to generate euclidean points based on a subject in the CMU dataset?
@papagina Hello, I am very interested in your work. But I have a question here when reading your code. Could you kindly explain how the augment_train_data function works below?
def get_train_data(bvh_filename):
data=parse_frames(bvh_filename)
train_data=get_training_format_data(data, non_end_bones,skeleton)
center=get_motion_center(train_data) #get the avg position of the hip
center[1]=0.0 #don't center the height
new_train_data=augment_train_data(train_data, -center, [0,1,0, 0.0])
return new_train_data
Thank you for your great work.
If I would like to use arbitrary bvh dataset, what should I do?
I already tried to convert not only CMU but also another bvh dataset, but When I converted another bvh dataset, it seems can not parse correctly.
When I visualize it, it seems strange moving. It's not only predicted result but also ground truth.
sorry maybe this is just my misundersood.
please delete this issue.
Hi,
the fix_feet.py doesnt seem to run of the shelf, has unitialized and unused variables.
can you provide comments for the code. its hard to understand.
Thanks,
I think the network consists three fc layers in paper while in your code, there is only one fc layer but 3 LSTM layers.
Hi
When I convert and restore BVH file, the area around End Site of restored motion is different.
Restored motion tremble.
The code is following:
from read_bvh import get_train_data, write_traindata_to_bvh
xyz_data = get_train_data("../train_data_bvh/indian/05.bvh")
write_traindata_to_bvh("restored_05.bvh", xyz_data)
How to solve this problem?
Hi I got an error when I run the file pytorch_train_aclstm.py
<ipython-input-13-4f37744e12e2> in train_one_iteraton(real_seq_np, model, optimizer, iteration, save_dance_folder, print_loss, save_bvh_motion)
140 if(print_loss==True):
141 print ("###########"+"iter %07d"%iteration +"######################")
--> 142 print ("loss: "+str(loss.data.tolist()[0]))
143
144
TypeError: 'float' object is not subscriptable
Hello, I have been training the model in different data and when is time to write the bvh animation I get the following error from
rotation2xyz.py script:
"-->assert np.allclose(np.linalg.norm(children_xyz[i, :]), np.linalg.norm(children_orig[i, :]))
Assertion Error"
since there is no comment explaining this code I am having a really hard time figuring out how to solve it. I am using a small animation of shape:
[5,60,171]
Nice work!
I have a question~
The joint points in the data generated by training model are rotated. The joint of the original BVH data is not rotated, but when the original BVH data is converted to NPY and after the training is transferred out of the BVH, the joints begin to rotate. How to avoid this problem?
thank you!
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