This is a wrapper node for Marigold depth estimation: https://github.com/prs-eth/Marigold

Join us at the Banodoco Discord for discussion on the use and node development: https://discord.com/channels/1076117621407223829/1184863853096484865

What I know of the parameters so far:

denoise_steps: steps per depth map, increase for accuracy in exchange of processing time

n_repeat: amount of iterations to be ensembled into single depth map, increase for accuracy in exchange of processing time

n_repeat_batch_size: how many of the n_repeats are processed as a batch, if you have the VRAM this can match the n_repeats for faster processing

invert: marigold by default produces depth map where black is front, for controlnets etc. we want the opposite

regularizer_strength, reduction_method, max_iter, tol (tolerance) are settings for the ensembling process, don't fully know how to use them yet.

It can pretty memory hungry, and slow, fp16 halves the memory use. Marigold is meant to be run around 768p resolution so resizing is recommended, at higher res your mileage may wary. I added a remap node to see the full range better, and OpenEXR node to save the full range, works wonders compared to default png when used in VFX/3D modeling software.

Recommended way:

Use the ComfyUI manager (search for "marigold")

Manual install:

Clone this repo to ComfyUI/custom_nodes Install requirements: pip install -r requirements.txt

Get the model:

Currently using the same diffusers pipeline as in the original implementation, so in addition to the custom node, you need the model in diffusers format.

If the model is not found, it should autodownload with hugginface_hub. Alternatively get it manually from: https://huggingface.co/Bingxin/Marigold (or do git clone https://huggingface.co/Bingxin/Marigold/) in either of these folders:

ComfyUI\custom_nodes\ComfyUI-Marigold\checkpoints or ComfyUI\models\diffusers