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| import gradio as gr | |
| import numpy as np | |
| import plotly.graph_objects as go | |
| from pyvox.models import Vox | |
| from pyvox.writer import VoxWriter | |
| from pyvox.parser import VoxParser | |
| def load_vox_model(file_path): | |
| """Load and parse a .vox file""" | |
| try: | |
| print(f"Attempting to parse vox file: {file_path}") | |
| model = VoxParser(file_path).parse() | |
| print(f"Model parsed successfully") | |
| voxels = model.to_dense() | |
| print(f"Voxel array shape: {voxels.shape}") | |
| print(f"Number of non-zero voxels: {np.count_nonzero(voxels)}") | |
| print(f"Palette size: {len(model.palette)}") | |
| if np.count_nonzero(voxels) == 0: | |
| print("Warning: No voxels found in the model") | |
| return None, None | |
| return voxels, model.palette | |
| except Exception as e: | |
| print(f"Error in load_vox_model: {str(e)}") | |
| return None, None | |
| def create_3d_scatter(voxels, palette): | |
| """Create a 3D scatter plot from voxel data""" | |
| # Get coordinates and color indices of non-zero voxels | |
| x, y, z = np.nonzero(voxels) | |
| color_indices = voxels[x, y, z] - 1 # Subtract 1 since palette indices in .vox start at 1 | |
| # Apply rotation to orient the model correctly | |
| # Negate y coordinate to flip the model upright and rotate z to face forward | |
| y = -y | |
| temp_z = z.copy() | |
| z = -temp_z # Negate z to make the model face forward | |
| # Convert palette indices to RGB colors using direct palette indexing | |
| rgb_colors = [f'rgb({int(palette[c][0])}, {int(palette[c][1])}, {int(palette[c][2])})' | |
| if c < len(palette) else 'rgb(255, 255, 255)' for c in color_indices] | |
| # Create 3D scatter plot with improved voxel representation | |
| fig = go.Figure(data=[go.Scatter3d( | |
| x=x, y=y, z=z, | |
| mode='markers', | |
| marker=dict( | |
| size=6, # Reduced size for better visualization | |
| color=rgb_colors, | |
| opacity=1.0, | |
| symbol='square', # Using square symbol (supported by Plotly) | |
| line=dict(width=0), # Remove border lines completely | |
| sizemode='diameter', # Fixed size regardless of zoom | |
| sizeref=1.0 # Reference scale for consistent size | |
| ) | |
| )]) | |
| # Calculate center and range for better camera positioning | |
| center_x = (x.max() + x.min()) / 2 | |
| center_y = (y.max() + y.min()) / 2 | |
| center_z = (z.max() + z.min()) / 2 | |
| max_range = max(x.max() - x.min(), y.max() - y.min(), z.max() - z.min()) | |
| # Update layout for better visualization | |
| fig.update_layout( | |
| scene=dict( | |
| aspectmode='cube', # Force cubic aspect ratio | |
| camera=dict( | |
| up=dict(x=0, y=1, z=0), | |
| center=dict(x=0, y=0, z=0), | |
| eye=dict(x=1.5, y=0.9, z=0.9) # Adjusted camera position for a closer view while maintaining angle | |
| ), | |
| xaxis=dict(range=[center_x - max_range/1.5, center_x + max_range/1.5], showgrid=True, gridwidth=1, gridcolor='rgba(128, 128, 128, 0.2)'), | |
| yaxis=dict(range=[center_y - max_range/1.5, center_y + max_range/1.5], showgrid=True, gridwidth=1, gridcolor='rgba(128, 128, 128, 0.2)'), | |
| zaxis=dict(range=[center_z - max_range/1.5, center_z + max_range/1.5], showgrid=True, gridwidth=1, gridcolor='rgba(128, 128, 128, 0.2)') | |
| ), | |
| margin=dict(l=0, r=0, t=0, b=0), | |
| showlegend=False, | |
| template='plotly_dark', # Dark theme for better contrast | |
| paper_bgcolor='rgba(0,0,0,1)', # Pure black background | |
| plot_bgcolor='rgba(0,0,0,1)' | |
| ) | |
| return fig | |
| def display_vox_model(vox_file): | |
| """Main function to display the voxel model""" | |
| try: | |
| # Load the vox model | |
| if not vox_file: | |
| return "Please upload a .vox file" | |
| if not vox_file.name.endswith('.vox'): | |
| return "Please upload a valid .vox file" | |
| print(f"Loading vox file: {vox_file.name}") | |
| voxels, palette = load_vox_model(vox_file.name) | |
| if voxels is None or palette is None: | |
| return "Error: Could not load voxel data from file" | |
| if voxels.size == 0: | |
| return "Error: No voxels found in the model" | |
| print(f"Model loaded successfully. Shape: {voxels.shape}, Palette size: {len(palette)}") | |
| # Create the 3D visualization | |
| fig = create_3d_scatter(voxels, palette) | |
| return fig | |
| except Exception as e: | |
| print(f"Error details: {str(e)}") | |
| return f"Error loading model: {str(e)}" | |
| # Create Gradio interface | |
| interface = gr.Interface( | |
| fn=display_vox_model, | |
| inputs=gr.File(label="Upload .vox file"), | |
| outputs=gr.Plot(label="3D Voxel Model"), | |
| title="Voxel Model Viewer", | |
| description="Upload a .vox file to view the 3D voxelized model.", | |
| examples=[["modelo_optimizado.vox"]] | |
| ) | |
| if __name__ == "__main__": | |
| interface.launch() |