Files
Dobidop-ComfyStereo/__init__.py
T
DobidopandClaude c2b3bb5a50 Merge ComfyStereoViewer and StereoscopeGenerator into unified ComfyStereo
Combines three powerful stereoscopic tools into one comprehensive package:

1. Core Stereo Generation
   - Depth-based stereo conversion with GPU acceleration
   - Advanced fill techniques (Polylines, GPU Warp, Hybrid Edge, etc.)
   - Edge-aware depth blurring for artifact reduction
   - Side-by-Side, Top-Bottom, and Red-Cyan Anaglyph output formats

2. Native VR Viewing (Optional - requires PyOpenXR)
   - Auto-launch directly into VR headset without browser
   - Support for all VR headsets (Quest, Vive, Index, WMR)
   - Multiple projection types (Flat, Curved, 180° Dome, 360° Sphere)
   - Image and video playback support

3. StereoDiffusion AI (Optional - requires diffusers)
   - AI-powered stereo generation using diffusion models
   - DDIM inversion with null-text optimization
   - Bilateral Neighbor Attention for stereo consistency
   - Works with ComfyUI MODEL/CLIP/VAE or HuggingFace models

Changes:
- Added native_viewer/ module with PyOpenXR implementation
- Added native_nodes.py with 3 VR viewer nodes
- Added stereodiffusion_nodes.py with AI stereo generation
- Added supporting modules: model_wrappers, model_loader, inversion,
  stereo_utils, diffusion_utils
- Updated __init__.py with graceful optional dependency handling
- Consolidated all requirements into single requirements.txt
- Comprehensive README with setup guides and troubleshooting
- Added NOTICE and licenses/ for proper attribution

The package now offers 6+ nodes total with modular installation options.
Users can install just the base, or add VR viewing and/or AI generation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-25 22:10:56 +01:00

73 lines
2.5 KiB
Python

"""
ComfyStereo - Comprehensive Stereoscopic 3D toolkit for ComfyUI
Combines three powerful stereo tools:
1. Stereo Image Generation - Depth-based stereo conversion with GPU acceleration
2. VR Viewing - Native PyOpenXR viewer for direct VR headset viewing
3. StereoDiffusion - AI-powered stereo generation using diffusion models
"""
# Import base stereo generation nodes (always available)
from .GenerateStereo import NODE_CLASS_MAPPINGS as STEREO_NODES
from .GenerateStereo import NODE_DISPLAY_NAME_MAPPINGS as STEREO_NAMES
# Import native VR viewer nodes (optional, requires PyOpenXR)
try:
from .native_nodes import NODE_CLASS_MAPPINGS as NATIVE_NODES
from .native_nodes import NODE_DISPLAY_NAME_MAPPINGS as NATIVE_NAMES
NATIVE_AVAILABLE = True
except ImportError as e:
NATIVE_NODES = {}
NATIVE_NAMES = {}
NATIVE_AVAILABLE = False
print("\n" + "="*60)
print("PyOpenXR not available. Native VR viewer nodes disabled.")
print("To enable native VR viewing:")
print(" pip install -r requirements-native.txt")
print("="*60 + "\n")
# Import StereoDiffusion nodes (optional, requires diffusers)
try:
from .stereodiffusion_nodes import NODE_CLASS_MAPPINGS as DIFFUSION_NODES
from .stereodiffusion_nodes import NODE_DISPLAY_NAME_MAPPINGS as DIFFUSION_NAMES
DIFFUSION_AVAILABLE = True
except ImportError as e:
DIFFUSION_NODES = {}
DIFFUSION_NAMES = {}
DIFFUSION_AVAILABLE = False
print("\n" + "="*60)
print("StereoDiffusion dependencies not available. AI stereo generation disabled.")
print("To enable StereoDiffusion:")
print(" pip install diffusers transformers accelerate einops tqdm scikit-image")
print("="*60 + "\n")
# Combine all node mappings
NODE_CLASS_MAPPINGS = {
**STEREO_NODES,
**NATIVE_NODES,
**DIFFUSION_NODES,
}
NODE_DISPLAY_NAME_MAPPINGS = {
**STEREO_NAMES,
**NATIVE_NAMES,
**DIFFUSION_NAMES,
}
# Print status
print("\n" + "="*60)
print("ComfyStereo - Loaded Modules:")
print("="*60)
print(f"✓ Stereo Image Generation ({len(STEREO_NODES)} nodes)")
if NATIVE_AVAILABLE:
print(f"✓ Native VR Viewer ({len(NATIVE_NODES)} nodes)")
else:
print(f"✗ Native VR Viewer (not available)")
if DIFFUSION_AVAILABLE:
print(f"✓ StereoDiffusion ({len(DIFFUSION_NODES)} nodes)")
else:
print(f"✗ StereoDiffusion (not available)")
print(f"\nTotal: {len(NODE_CLASS_MAPPINGS)} nodes loaded")
print("="*60 + "\n")
__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']