32 lines
1.0 KiB
Plaintext
32 lines
1.0 KiB
Plaintext
# HandFlow V1 — inference + render deps (no training deps)
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# One-line install: pip install -r requirements.txt
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# Or use setup_env.sh to create a conda environment
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--extra-index-url https://download.pytorch.org/whl/cu128
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# -- PyTorch (CUDA 12.8; matches the ViPE environment, see setup_vipe_env.sh) --
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torch==2.7.0+cu128
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torchvision==0.22.0+cu128
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# -- Inference core --
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numpy
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scipy
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omegaconf
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tqdm
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# -- Hand detection + MANO FK --
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ultralytics # YOLO detection (detector.pt weights from WiLoR, see README)
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manopth # MANO forward kinematics
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# -- Rendering (demo.py -> mp4, pytorch3d Phong shading) --
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# pytorch3d must match the torch/CUDA above; no prebuilt wheel for torch 2.7+cu128, so build from source:
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# pip install "git+https://github.com/facebookresearch/pytorch3d.git@v0.7.8"
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pytorch3d
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opencv-python
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imageio[ffmpeg]
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matplotlib
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# The following two are installed separately as submodules:
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# HaMeR backbone: pip install -e third_party/hamer
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# ViPE SLAM (optional): see setup_vipe_env.sh (standalone environment)
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