Depth Estimation
Diffusers
Safetensors
English
MarigoldDepthPipeline
depth estimation
latent consistency model
image analysis
computer vision
in-the-wild
zero-shot
Instructions to use prs-eth/marigold-depth-lcm-v1-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prs-eth/marigold-depth-lcm-v1-0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("prs-eth/marigold-depth-lcm-v1-0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add github link, general pipeline tag
#6
by nielsr HF Staff - opened
This PR ensures people can find your code at https://github.com/prs-eth/marigold. It also changes the pipeline tag to image-to-image as it's more generic,
since the model takes an image as input and produces an image (depth map) as output.
toshas changed pull request status to merged