Comments (4)
Hi, I'm sorry but the current code is still quite entangled with the training dataset we use. For example, the number of channels in some layers should be in accordance with the number of joints of the training skeleton. (Now they're hardcoded in config.py.) Furthermore, the scripts to generate the dataset from BVH files should also be accustomed to each dataset. You can see in data_proc/export_train.py that we process xia and bfa differently. Since xia's data happens to have content labels, we use that as a reference to do the train-test split. That's what content_test_cnt
is for.
In our next update, we'll further refactor the code to support training with customized data & release relevant details.
from deep-motion-editing.
Thank you very much.
I've retargeted our bvh to the skeleton of the code processing.
But some definitions of the overall data structure are still incorrect, resulting in errors in the label correspondence.
I also process our data in the way of bfa, but we have too few frames in our data, so I change the parameter window_size and
window_step
If I change this parameter, does the rest of the code need to be changed again?
from deep-motion-editing.
Regarding the label correspondence, now we read the style label of the data from the BVH filename. You can change the related code (line 219~211) in generate_database_bfa to make sure it's compatible with your BVH filenames. Also if you are working with many small BVH files, you may want to modify generate_database_bfa's code to do the train-test split in a different way (use some BVH files for testing). Our bfa BVHs are very long so we have to take window * 2 frames for testing from every window * 20 frames, which kind of requires the BVH to be as least window * 20 frames in the first place.
A window size of 16 might be a bit small? But let's see how the training goes.
(Oh, and please note we assume our input BVH files are of 120 fps. If yours are not you may want to change the downsample parameter.)
Hope this would help!
from deep-motion-editing.
thanks a lot!
from deep-motion-editing.
Related Issues (20)
- 代码与原论文有所出入 HOT 3
- How the the skining work? HOT 1
- 处理过手指的重定向吗? HOT 3
- Retargeting retraining on customized dataset HOT 3
- 非标准躯干数据集的可能性 HOT 8
- Use a new dataset in style transfer HOT 1
- 使用额外bvh文件进行retargeting HOT 6
- style transfer任务的pretrained模型和提供config不符
- BVH_mod HOT 1
- Error in forward kinematics HOT 2
- 请问作者有没有尝试过面向3d坐标的异构重定向?
- Error: No module named 'option_parser'
- Error: No module named 'datasets'
- Error: No such file or directory: './datasets/Mixamo/Malcolm_m.npy'
- 使用新骨架进行重定向后,出现模型维度不匹配的问题 HOT 1
- 您好,我现在面临在经过Preprocessing处理之后,在训练的时候数据打开verbose选项,看到数据都是Nan,请问这可能是什么原因造成的呢 HOT 1
- the src.bvh and dst.bvh must be the same Skeletal hierarchy ?
- retarget a bvh file to use it in style transfer HOT 1
- What is the equivalent for batch overfitting for such a training scheme?
- 关于其它bvh文件retargeting的几个问题?
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