A specialized custom node for ComfyUI, this tool generates anaglyph 3D images by utilizing color and depth map inputs. It is engineered for high-speed performance, particularly in converting videos to anaglyph format with CUDA GPU acceleration.
- Supports batch processing, allowing for efficient handling of multiple video frames simultaneously.
- Features adjustable parallax and depth settings, providing control over the 3D effect's strength and focal plane.
- Includes a real-time depth map inversion option, enhancing flexibility in depth map usage.
Context
This tool is a custom node developed for ComfyUI, aimed at creating anaglyph 3D images from both color images and corresponding depth maps. Its primary purpose is to facilitate the fast conversion of video content into the anaglyph format, which is essential for 3D viewing experiences.
Key Features & Benefits
The tool leverages CUDA GPU acceleration to significantly enhance processing speeds, making it ideal for video-to-anaglyph conversion. Users can process multiple frames in batches, which greatly improves efficiency, especially when working with lengthy video files. The adjustable settings for parallax and depth allow users to fine-tune the 3D effect to meet specific visual requirements.
Advanced Functionalities
Among its advanced capabilities, the node offers real-time depth map inversion, which allows users to toggle the depth map orientation dynamically. This feature can be particularly useful when working with complex scenes where depth perception needs to be adjusted on the fly. Additionally, the ability to control the divergence and zero parallax depth provides users with enhanced creative control over the final output.
Practical Benefits
This tool streamlines the workflow for users by allowing quick processing of video frames into anaglyph images, thereby saving time and improving productivity. The ability to adjust depth and parallax settings means that artists and creators can achieve higher-quality 3D visuals, resulting in a more immersive viewing experience. The batch processing capability further enhances efficiency, enabling users to maximize their hardware's performance.
Credits/Acknowledgments
The development of this tool is credited to the original authors and contributors, with special acknowledgment to mikeymcfish for his foundational work on related projects that inspired this tool's creation. The project is licensed under CC BY-NC-SA 4.0, allowing for non-commercial sharing and adaptation.