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ComfyUI Extension: Marigold depth estimation in ComfyUI

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kijai (Account age: 2184 days)
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How to Install Marigold depth estimation in ComfyUI

Install this extension via the ComfyUI Manager by searching for  Marigold depth estimation in ComfyUI
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter Marigold depth estimation in ComfyUI in the search bar
After installation, click the  Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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Marigold depth estimation in ComfyUI Description

Marigold depth estimation in ComfyUI is a wrapper node utilizing the same diffusers pipeline as the original Marigold implementation. It requires a model in diffusers format to function effectively within ComfyUI.

Marigold depth estimation in ComfyUI Introduction

ComfyUI-Marigold is an extension designed to integrate the powerful Marigold depth estimation model into the ComfyUI environment. This extension allows AI artists to generate high-quality depth maps from monocular images, leveraging the advanced capabilities of diffusion-based image generators. By using ComfyUI-Marigold, you can enhance your visual projects with accurate depth information, which is particularly useful for 3D modeling, visual effects (VFX), and other creative applications.

How Marigold depth estimation in ComfyUI Works

ComfyUI-Marigold works by wrapping the Marigold depth estimation model into a user-friendly node within the ComfyUI framework. The Marigold model, originally designed for monocular depth estimation, repurposes the visual knowledge stored in modern generative image models to predict depth information from a single image. This process involves several steps:

  1. Image Input: You provide a single image to the ComfyUI-Marigold node.
  2. Depth Estimation: The Marigold model processes the image using a diffusion-based approach to estimate the depth map.
  3. Output: The resulting depth map is outputted, which can be used in various applications like 3D rendering or VFX. The extension simplifies this complex process, making it accessible to users without deep technical knowledge.

Marigold depth estimation in ComfyUI Features

ComfyUI-Marigold offers several features to customize and optimize the depth estimation process:

  • Denoise Steps (denoise_steps): This parameter controls the number of steps taken to refine the depth map. Increasing the number of steps can improve accuracy but will also increase processing time.
  • Repeat Iterations (n_repeat): This determines how many times the depth estimation process is repeated and ensembled into a single depth map. More iterations can lead to better accuracy at the cost of longer processing times.
  • Batch Size (n_repeat_batch_size): This sets how many iterations are processed simultaneously. If you have sufficient VRAM, matching this to the number of repeats can speed up processing.
  • Invert: By default, Marigold produces a depth map where black represents the foreground. This option allows you to invert the depth map, making it compatible with tools like ControlNet.
  • Regularizer Strength, Reduction Method, Max Iter, Tolerance: These advanced settings control the ensembling process, allowing for fine-tuning of the depth estimation.

Marigold depth estimation in ComfyUI Models

ComfyUI-Marigold uses the Marigold model, which is available in different versions optimized for various performance needs:

  • Standard Marigold Model: This version is designed for high accuracy and is suitable for detailed depth estimation tasks.
  • LCM (Lightweight Checkpoint Model): This version is optimized for faster inference, making it ideal for real-time applications or when working with limited computational resources. You can choose the model that best fits your needs based on the trade-off between accuracy and processing speed.

What's New with Marigold depth estimation in ComfyUI

The extension is regularly updated to improve performance and add new features. Here are some recent updates:

  • Improved Accuracy: Enhancements in the depth estimation algorithm for more precise results.
  • Faster Processing: Optimizations to reduce processing time, especially with the LCM model.
  • New Parameters: Additional settings for better control over the depth estimation process. These updates ensure that ComfyUI-Marigold remains a powerful and efficient tool for AI artists.

Troubleshooting Marigold depth estimation in ComfyUI

Here are some common issues and their solutions:

  • Memory Usage: If you encounter memory issues, try reducing the n_repeat or n_repeat_batch_size parameters. Using the fp16 option can also help by halving the memory usage.
  • Slow Processing: Increase the denoise_steps and n_repeat parameters gradually to find a balance between accuracy and processing time.
  • Inverted Depth Map: Use the invert option if the depth map appears inverted for your application.

Frequently Asked Questions

  • What is the optimal resolution for input images? Marigold performs best at a resolution of around 768p. Resizing your images to this resolution before processing can yield better results.

  • How can I save the depth map in a high-quality format? Use the OpenEXR node to save the depth map, as it preserves the full range of depth information, which is beneficial for VFX and 3D modeling.

Learn More about Marigold depth estimation in ComfyUI

For additional resources, tutorials, and community support, you can visit the following links:

  • These resources provide comprehensive information and support to help you get the most out of ComfyUI-Marigold.

Marigold depth estimation in ComfyUI Related Nodes


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