DepthFM is an unofficial implementation designed for ComfyUI that focuses on depth estimation for both images and videos. This tool leverages the DepthFM model, offering users advanced capabilities in generating depth maps efficiently.
- Supports depth estimation for both single images and video content.
- Allows users to adjust parameters like steps and ensemble size for optimized results.
- Requires image dimensions to be multiples of 64 for accurate processing.
Context
This tool serves as an unofficial integration of the DepthFM model into ComfyUI, enhancing its functionality by providing efficient and versatile depth estimation capabilities. Its primary purpose is to allow users to generate depth maps from both static images and video sequences, thereby expanding the creative possibilities within the ComfyUI framework.
Key Features & Benefits
DepthFM offers practical features such as the ability to perform depth estimation on both images and videos, which is crucial for users looking to add depth information to their projects. Users can fine-tune the depth estimation process by adjusting parameters like the number of steps for processing and the ensemble size, which directly impacts the accuracy of the depth maps generated.
Advanced Functionalities
The tool includes an ensemble feature that allows users to select the number of models used in the depth estimation process, thereby improving the accuracy of the results. Additionally, it supports both single image and iterative video processing, making it versatile for different types of visual content. Users are advised to maintain specific image dimensions for optimal functionality.
Practical Benefits
By integrating DepthFM into ComfyUI, users can significantly enhance their workflow, gaining better control over depth estimation processes. This leads to improved quality of depth maps and greater efficiency in handling both images and videos, ultimately facilitating more sophisticated visual projects.
Credits/Acknowledgments
This implementation is based on the original DepthFM model developed by CompVis. Acknowledgments are also due to contributors involved in the creation and maintenance of this repository.