liyang
ae28d55f81
Source: RGB-D -> Dyn-HaMR -> L20 retargeting -> FoundationPose -> reference repair -> SPIDER, documented in docs/PIPELINE_LATEST.md and docs/SETUP_AND_WEIGHTS.md. Adds FoundationPose and nvdiffrast upstream snapshots, requirements/pipeline_venv.txt and the FoundationPose weight manifest/downloader. Assets (Git LFS): weights/ (WiLoR detector, HandFlow denoiser, UniDepth-L), FoundationPose checkpoints, HaMeR checkpoint, Dyn-HaMR HMP model and BMC constraints, L20 URDF/meshes, the 20260915_171525 D405 recording and the two box CADs. MANO models are not redistributed (third_party/hamer/_DATA/data/mano/README.txt). Environments, caches and run outputs excluded. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
18 lines
444 B
YAML
18 lines
444 B
YAML
# Conda-only dependencies (compilers, CMake, Eigen, Boost, pybind11).
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# After creating the env, install PyTorch and GPU extensions as described in readme.md
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# (PyTorch index URL may need to match your CUDA driver), then:
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# pip install -r requirements.txt
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# bash build_all_conda.sh
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name: foundationpose
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channels:
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- conda-forge
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dependencies:
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- python=3.11
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- pip
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- cmake
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- ninja
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- eigen
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- boost-cpp
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- pybind11
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- cxx-compiler
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