ComfyUI Node: Depth Estimation by Marigold (experimental) 🧅

Depth Estimation by Marigold (experimental) 🧅:

NegiTools_DepthEstimationByMarigold is a powerful node designed to estimate depth from images using the Marigold model. This node leverages advanced machine learning techniques to generate depth maps, which can be used in various applications such as 3D rendering, augmented reality, and image enhancement. By converting 2D images into depth maps, it provides a new dimension of information that can significantly enhance the visual and functional quality of your projects. The node is designed to be user-friendly, allowing you to adjust parameters like inference passes, denoise steps, and depth exponent to fine-tune the output according to your needs. Whether you are looking to create more realistic scenes or add depth effects to your images, this node offers a robust solution.

Depth Estimation by Marigold (experimental) 🧅 Input Parameters:

image

This parameter accepts an image input that you want to process for depth estimation. The image should be in a compatible format that the node can read and process.

infer_passes

This parameter controls the number of inference passes the model will perform. More passes can lead to more accurate depth estimation but will take longer to process. The default value is 10, with a minimum of 1 and a maximum of 40.

denoise_steps

This parameter determines the number of denoise steps applied during the depth estimation process. Higher values can result in cleaner depth maps but may increase processing time. The default value is 10, with a minimum of 1 and a maximum of 40.

seed

This parameter sets the seed for random number generation, ensuring reproducibility of results. The default value is 0, and it can range from 0 to 0xffffffff.

runtime

This parameter allows you to choose the runtime environment for executing the depth estimation. Options include bare (recommended) and venv (if "bare" doesn't work). The bare option is recommended for most users, while venv can be used if there are compatibility issues.

depth_exponent

This parameter adjusts the exponent applied to the depth values, allowing you to control the contrast and intensity of the depth map. The default value is 1.0, with a range from 0.1 to 3.0, adjustable in steps of 0.1.

invert

This boolean parameter allows you to invert the depth map, making closer objects appear farther and vice versa. The default value is False.

Depth Estimation by Marigold (experimental) 🧅 Output Parameters:

DEPTH_IMAGE

This output parameter provides the resulting depth map as an image. The depth map is a grayscale image where the intensity of each pixel represents the estimated depth. This output can be used in various applications such as 3D modeling, augmented reality, and image enhancement to add depth information to your projects.

Depth Estimation by Marigold (experimental) 🧅 Usage Tips:

• For more accurate depth maps, increase the infer_passes parameter, but be aware that this will also increase processing time.
• Use the denoise_steps parameter to reduce noise in the depth map, especially if the input image is noisy.
• Adjust the depth_exponent to fine-tune the contrast and intensity of the depth map according to your specific needs.
• If the depth map appears inverted, use the invert parameter to correct it.
• If you encounter compatibility issues, try switching the runtime parameter to venv.

Depth Estimation by Marigold (experimental) 🧅 Common Errors and Solutions:

"Marigold repository not found or connection error"

• Explanation: This error occurs when the Marigold repository cannot be cloned due to a connection issue or the repository not being available.
• Solution: Check your internet connection and ensure that the repository URL is correct. Retry the operation after verifying these conditions.

"Failed to setup venv for Marigold"

• Explanation: This error indicates that the virtual environment setup for Marigold failed.
• Solution: Ensure that you have the necessary permissions and dependencies to create a virtual environment. Retry the setup process.

"Image processing failed"

• Explanation: This error occurs when the input image cannot be processed, possibly due to an incompatible format or corrupted file.
• Solution: Verify that the input image is in a compatible format and not corrupted. Use a different image if necessary.

"Depth map generation failed"

• Explanation: This error indicates that the depth map could not be generated, possibly due to incorrect parameter settings or insufficient resources.
• Solution: Check the parameter settings and ensure that your system has enough resources to perform the depth estimation. Adjust the parameters if needed and retry.