Depth Estimation
Diffusers
Safetensors
English
MarigoldDepthPipeline
depth estimation
image analysis
computer vision
in-the-wild
zero-shot
Instructions to use prs-eth/marigold-depth-v1-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prs-eth/marigold-depth-v1-1 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-v1-1", 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
File size: 534 Bytes
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"_class_name": "MarigoldDepthPipeline",
"_diffusers_version": "0.24.0",
"prediction_type": "depth",
"scale_invariant": true,
"shift_invariant": true,
"default_denoising_steps": 4,
"default_processing_resolution": 768,
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
],
"scheduler": [
"diffusers",
"DDIMScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
]
} |