Instructions to use manycore-research/SpatialGen-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use manycore-research/SpatialGen-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("manycore-research/SpatialGen-1.0", 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
There is no complete text2scene pipeline.
#4
by nikitavovch - opened
You cannot generate just from the text description + GT layout, as it says. You'll always need atleast RGB images to inference the text 2 scene pipeline. I dont get it, why you haven't made all in one script. I mean generation of rgb, depth, normal and etc. images to inference the full text to scene pipeline in one click. To inference your own generation from only a GT layout, first of all you need to run the preprocessing script, then you need to generate rgb's by yourself, with their flux wireframe model, and etc etc etc...