Update requirements.txt

requirements.txt

@@ -1,16 +1,45 @@
---find-links https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py39_cu113_pyt1121/download.html
-torch==1.12.1+cu113
-torchvision==0.13.1+cu113
-pytorch3d==0.7.2
-gradio>=4.20.0,<5.0.0 
-trimesh==3.15.2
-numpy==1.23.1
-scipy==1.9.1
-joblib==1.2.0
-smplx==0.1.28
-pyrender==0.1.45
-chumpy==0.70
-tqdm==4.64.0
-scikit-image==0.19.3
-opencv-python-headless # For cv2, a dependency of UniRig's utils
-Pillow # For PIL.Image, used in UniRig's utils
+# PyTorch (UniRig: >=2.3.1)
+torch>=2.3.1
+torchvision>=0.18.1 # Compatible with torch 2.3.1
+
+# PyTorch Geometric libraries (for CUDA 12.1, matching PyTorch 2.3.1)
+# Ensure the URL is correct and accessible at build time.
+# Pip will use this link to find the wheels.
+# --find-links is an alternative way to specify this if direct install fails.
+torch-scatter -f https://data.pyg.org/whl/torch-2.3.1+cu121.html
+torch-cluster -f https://data.pyg.org/whl/torch-2.3.1+cu121.html
+
+# Spconv (for CUDA 12.1)
+# UniRig's instructions: python -m pip install spconv-{you-cuda-version}
+# This translates to the package name spconv-cu121 for pip.
+spconv-cu121
+
+# Numpy (UniRig: 1.26.4)
+numpy==1.26.4
+
+# Gradio
+gradio>=4.29.0,<5.0.0 # Using a recent Gradio 4.x version
+
+# Dependencies from UniRig's official requirements.txt
+# (https://github.com/VAST-AI-Research/UniRig/blob/main/requirements.txt)
+trimesh
+scipy
+smplx
+pyrender
+chumpy
+opencv-python # UniRig uses this; not headless. Ensure Xvfb etc. from packages.txt are present.
+Pillow
+pyquaternion
+pytorch-lightning # May mostly be for training, but included for UniRig compatibility
+hydra-core      # Crucial for running UniRig's scripts/modules
+# wandb           # For experiment tracking, likely not essential for deployed app, can be commented if causing issues
+rich            # For nice console outputs, used by UniRig scripts
+distinctipy
+scikit-image
+mediapipe
+
+# Add UniRig itself if installing from a local clone within the Space
+# If you place the UniRig cloned repo in the root of your space,
+# you can install it in editable mode or add its path.
+# For simplicity with Hugging Face Spaces, we'll add its path in app.py
+# and rely on its scripts being callable via `python -m`.