Update requirements.txt

requirements.txt

@@ -1,45 +1,33 @@
-# PyTorch (UniRig: >=2.3.1)
-torch>=2.3.1
-torchvision>=0.18.1 # Compatible with torch 2.3.1
+   # 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
+   # PyTorch Geometric libraries (for CUDA 12.1, matching PyTorch 2.3.1)
+   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
+   # Spconv (for CUDA 12.1)
+   spconv-cu121
 
-# Numpy (UniRig: 1.26.4)
-numpy==1.26.4
+   # Numpy (UniRig: 1.26.4)
+   numpy==1.26.4
 
-# Gradio
-gradio>=4.29.0,<5.0.0 # Using a recent Gradio 4.x version
+   # Gradio (Updated to 5.29.0)
+   gradio>=5.29.0,<5.30.0 
 
-# 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`.
+   # Dependencies from UniRig's official requirements.txt
+   trimesh
+   scipy
+   smplx
+   pyrender
+   chumpy
+   opencv-python 
+   Pillow
+   pyquaternion
+   pytorch-lightning 
+   hydra-core      
+   rich            
+   distinctipy
+   scikit-image
+   mediapipe
+