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Create app.py

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  1. app.py +172 -0
app.py ADDED
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+ import gradio as gr
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+ import torch
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+ import trimesh
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+ import os
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+ import sys
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+ import tempfile
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+ import shutil
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+
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+ # Add UniRig source directory to Python path
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+ # Assuming UniRig files are in a subdirectory named 'UniRig_src'
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+ sys.path.append(os.path.join(os.path.dirname(__file__), 'UniRig_src'))
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+
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+ # Conditional import for AutoRigger and setup_source_mesh
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+ # This helps in providing a clearer error if UniRig_src is not found
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+ try:
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+ from autorig import AutoRigger
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+ from utils import setup_source_mesh
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+ except ImportError as e:
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+ print("Error importing from UniRig_src. Make sure the UniRig source files are in the 'UniRig_src' directory.")
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+ print(f"Details: {e}")
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+ # Define dummy functions if import fails, so Gradio can still load with an error message
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+ def AutoRigger(*args, **kwargs):
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+ raise RuntimeError("UniRig AutoRigger could not be loaded. Check UniRig_src setup.")
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+ def setup_source_mesh(mesh, *args, **kwargs):
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+ raise RuntimeError("UniRig setup_source_mesh could not be loaded. Check UniRig_src setup.")
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+
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+ # --- Configuration ---
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+ # Define paths to the UniRig model files
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+ # These files should be placed in the 'model_files' directory in your Hugging Face Space
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+ MODEL_DIR = os.path.join(os.path.dirname(__file__), "model_files")
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+ SMPL_SKELETON_PATH = os.path.join(MODEL_DIR, "smpl_skeleton.pkl")
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+ SKIN_KPS_PREDICTOR_PATH = os.path.join(MODEL_DIR, "skin_kps_predictor.pkl")
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+
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+ # Check if model files exist
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+ if not os.path.exists(SMPL_SKELETON_PATH) or not os.path.exists(SKIN_KPS_PREDICTOR_PATH):
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+ print(f"Warning: Model files not found at {MODEL_DIR}. Please ensure smpl_skeleton.pkl and skin_kps_predictor.pkl are present.")
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+
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+ # Determine processing device (CUDA if available, otherwise CPU)
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+ # ZeroGPU on Hugging Face Spaces should provide CUDA
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+ DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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+ print(f"Using device: {DEVICE}")
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+ if DEVICE.type == 'cuda':
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+ print(f"CUDA Device Name: {torch.cuda.get_device_name(0)}")
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+ print(f"CUDA Version: {torch.version.cuda}")
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+ else:
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+ print("CUDA not available, UniRig performance will be significantly slower on CPU.")
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+
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+
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+ # --- Core Rigging Function ---
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+ def rig_glb_mesh(input_glb_file):
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+ """
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+ Takes an input GLB file, rigs it using UniRig, and returns the path to the rigged GLB file.
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+ """
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+ if input_glb_file is None:
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+ raise gr.Error("No input file provided. Please upload a .glb mesh.")
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+
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+ input_glb_path = input_glb_file.name # Get the path of the uploaded file
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+
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+ # Ensure UniRig components are loaded (they might be dummy if import failed)
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+ if not callable(getattr(AutoRigger, '__init__', None)) or not callable(setup_source_mesh):
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+ raise gr.Error("UniRig components are not correctly loaded. Please check the server logs and UniRig_src setup.")
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+
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+ try:
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+ # Create a temporary directory for output
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+ temp_dir = tempfile.mkdtemp()
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+ output_glb_filename = "rigged_output.glb"
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+ output_glb_path = os.path.join(temp_dir, output_glb_filename)
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+
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+ # 1. Load the mesh using trimesh
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+ print(f"Loading mesh from: {input_glb_path}")
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+ mesh = trimesh.load_mesh(input_glb_path, force='mesh', process=False)
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+
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+ if not isinstance(mesh, trimesh.Trimesh):
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+ # If it's a Scene object, try to get a single geometry
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+ if isinstance(mesh, trimesh.Scene):
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+ if len(mesh.geometry) == 0:
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+ raise gr.Error("Input GLB file contains no mesh geometry.")
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+ # Concatenate all meshes in the scene into a single mesh
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+ # This is a common approach, but might not be ideal for all GLB files
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+ print(f"Input is a scene with {len(mesh.geometry)} geometries. Attempting to merge.")
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+ mesh = trimesh.util.concatenate(list(mesh.geometry.values()))
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+ if not isinstance(mesh, trimesh.Trimesh):
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+ raise gr.Error(f"Could not extract a valid mesh from the GLB scene. Found type: {type(mesh)}")
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+ else:
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+ raise gr.Error(f"Failed to load a valid mesh from the input file. Loaded type: {type(mesh)}")
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+
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+ print("Mesh loaded successfully.")
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+
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+ # 2. Preprocess the mesh (as per UniRig's example)
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+ # This step is crucial for UniRig to work correctly.
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+ # It involves canonicalization and remeshing.
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+ print("Preprocessing mesh...")
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+ mesh = setup_source_mesh(mesh, device=DEVICE)
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+ print("Mesh preprocessing complete.")
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+
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+ # 3. Initialize the AutoRigger
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+ # Ensure model files are accessible
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+ if not os.path.exists(SMPL_SKELETON_PATH) or not os.path.exists(SKIN_KPS_PREDICTOR_PATH):
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+ raise gr.Error(f"UniRig model files not found. Searched in {MODEL_DIR}. Please check your Space's file structure.")
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+
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+ print("Initializing AutoRigger...")
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+ autorigger = AutoRigger(SMPL_SKELETON_PATH, SKIN_KPS_PREDICTOR_PATH, device=DEVICE)
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+ print("AutoRigger initialized.")
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+
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+ # 4. Perform rigging
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+ print("Starting rigging process...")
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+ # The `rig` method might require specific verts, faces, and normals if not handled by `setup_source_mesh`
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+ # Assuming `setup_source_mesh` prepares it adequately.
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+ output_dict = autorigger.rig(mesh)
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+ print("Rigging process complete.")
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+
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+ # 5. Extract the rigged mesh
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+ rigged_mesh = output_dict['rigged_mesh'] # This should be a trimesh.Trimesh object
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+ print("Rigged mesh extracted.")
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+
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+ # 6. Export the rigged mesh to GLB format
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+ print(f"Exporting rigged mesh to: {output_glb_path}")
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+ rigged_mesh.export(output_glb_path)
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+ print("Export complete.")
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+
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+ return output_glb_path
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+
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+ except Exception as e:
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+ print(f"Error during rigging: {e}")
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+ # Clean up temp dir in case of error
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+ if 'temp_dir' in locals() and os.path.exists(temp_dir):
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+ shutil.rmtree(temp_dir)
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+ # Re-raise as Gradio error to display to user
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+ raise gr.Error(f"An error occurred during processing: {str(e)}")
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+ # No finally block for shutil.rmtree(temp_dir) here,
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+ # because Gradio needs the file path to serve it.
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+ # Gradio handles cleanup of temporary files created by gr.File.
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+
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+ # --- Gradio Interface ---
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+ # Define a custom theme (Blue and Charcoal Gray)
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+ # Using Soft theme with sky blue and slate gray
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+ theme = gr.themes.Soft(
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+ primary_hue=gr.themes.colors.sky, # A nice blue
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+ secondary_hue=gr.themes.colors.blue, # Can be same as primary or a complementary blue
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+ neutral_hue=gr.themes.colors.slate, # Charcoal gray
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+ font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui", "sans-serif"],
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+ ).set(
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+ # Further fine-tuning if needed
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+ # button_primary_background_fill="*primary_500",
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+ # button_primary_text_color="white",
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+ )
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+
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+ # Interface definition
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+ iface = gr.Interface(
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+ fn=rig_glb_mesh,
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+ inputs=gr.File(label="Upload .glb Mesh File", type="file"), # 'file' gives a NamedTemporaryFile object
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+ outputs=gr.Model3D(label="Rigged 3D Model (.glb)", clear_color=[0.8, 0.8, 0.8, 1.0]), # Model3D can display .glb
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+ title="UniRig Auto-Rigger for 3D Meshes",
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+ description=(
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+ "Upload a 3D mesh in `.glb` format. This application uses UniRig to automatically rig the mesh.\n"
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+ "The process may take a few minutes, especially for complex meshes. Ensure your GLB has clean geometry.\n"
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+ f"Running on: {str(DEVICE).upper()}. Model files expected in '{MODEL_DIR}'.\n"
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+ f"UniRig Source: https://github.com/VAST-AI-Research/UniRig"
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+ ),
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+ examples=[
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+ # Add paths to example GLB files if you include them in your Space
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+ # e.g., [os.path.join(os.path.dirname(__file__), "examples/sample_mesh.glb")]
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+ ],
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+ cache_examples=False, # Set to True if you have static examples and want to pre-process them
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+ theme=theme,
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+ allow_flagging="never"
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+ )
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+
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+ if __name__ == "__main__":
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+ if not os.path.exists(os.path.join(os.path.dirname(__file__), 'UniRig_src')):
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+ print("CRITICAL: 'UniRig_src' directory not found. Please ensure UniRig source files are correctly placed.")
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+ iface.launch()