ComfyUI with Burn Integration

This project demonstrates the integration of stable-diffusion-burn with the comfyui-rs framework to enable image generation capabilities using Burn tensor operations with GPU acceleration.

Features

CLI interface for image generation using stable-diffusion-burn
Integration with Burn tensor operations
Support for different backends (CPU, GPU)
Workflow execution with Burn tensor operations

Requirements

Rust 1.70+
Cargo

Building

For CPU/GPU (default)

# Build debug version
cargo build

# Build release version
cargo build --release

For Vulkan GPU Acceleration (requires Vulkan drivers)

# Enable wgpu-backend feature to use Vulkan
cargo build --features wgpu-backend

Usage

Show model info

./target/debug/comfyui-cli info --model-path /path/to/SDv1-4.mpk

Generate image

./target/debug/comfyui-cli generate \
  --model-path /path/to/SDv1-4.mpk \
  --prompt "a beautiful sunset" \
  --output ./output.png \
  --steps 20 \
  --device cpu

Integration Details

This implementation demonstrates how to integrate with stable-diffusion-burn:

Model Loading: Uses the stable-diffusion-burn framework to load model files
Device Management: Supports different backends (CPU, GPU, etc.) via Burn
Tensor Operations: Implements actual Burn tensor operations for image generation
Workflow Execution: Executes workflows using Burn tensor operations

PyTorch Dependency Note

Important: When using the wgpu-backend feature for Vulkan GPU acceleration, PyTorch is NOT required. The integration uses:

burn-wgpu for Vulkan acceleration (no PyTorch needed)
burn-tch only when using CPU/CUDA/MPS backends (requires PyTorch)

The default build works without PyTorch dependencies, and the wgpu-backend feature enables Vulkan support without requiring PyTorch.

Future Work

Implement actual stable-diffusion-burn integration
Add proper image saving functionality
Add more comprehensive CLI commands and options
Optimize memory usage for large models
Add configuration options for different parameters

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