算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
deep-motion-editing【设计与创意】Guides DeepMotionEditing BVH animation, skeleton-aware motion retargeting, motion style transfer, and Blender visualization workflows for research use.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this repo skill when a task names Deep Motion Editing, BVH motion editing,
skeleton-aware retargeting, unpaired motion style transfer, OpenPose motion
style, Mixamo BVHs, or Blender rendering/skinning. It is a script-oriented
research checkout, not a conventional installable Python package. Read
references/repo-provenance.md before
assuming the skill matches a new checkout.
This source snapshot has no setup.py, pyproject.toml, requirements file, or
console entry point; do not invent pip install deep-motion-editing. For the
selected Python workflows, install only the route dependencies in a disposable
environment, for example:
python -m pip install "numpy<2" scipy pyyaml tqdm torch
# Add these only for training/logging/probe work:
python -m pip install tensorboardX tensorboard matplotlib scikit-learn
Use Python 3.7+ as documented by the project. CUDA is recommended for model
inference/training; CPU is useful for format checks but is only a partial
neural substitute. Use Blender 2.80-era or a tested newer Blender for bpy
workflows; ordinary Python cannot import bpy. Keep datasets, checkpoints,
OpenPose outputs, FBX assets, and generated results outside the skill tree. Do
not download or overwrite them implicitly. Run the read-only environment probe
scripts/check_environment.py before a new
task. Read references/troubleshooting.md
for legacy imports, paths, optional dependencies, and backend failures.
| User intent | Read next |
|---|---|
| BVH parsing/writing, topology, JSON validation, kinematics, cleanup | sub-skills/animation-data/SKILL.md |
| Mixamo/custom data, intra/cross retargeting, evaluation, training | sub-skills/motion-retargeting/SKILL.md |
| 3D/2D style transfer, normalization, Xia/BFA preparation, training | sub-skills/motion-style-transfer/SKILL.md |
| Blender BVH load/render, FBX skinning or conversion | sub-skills/blender-visualization/SKILL.md |
The central cross-workflow contract is: validate BVH hierarchy and frame data first, preserve source inputs, write new outputs, then validate the result before neural comparison or rendering. Sibling routes link to each other when a task crosses that boundary.
A parser/help check does not reproduce a paper result. Meaningful neural runs need the correct pretrained checkpoints, normalization files, dataset layout, model configuration, and a suitable backend. Blender routes additionally need a Blender executable and compatible FBX assets. This generated skill was built from a 2021 source snapshot and intentionally omits large binaries and external data; those limitations are recorded in the references and external verification artifacts, not hidden.