Text-to-Image
Diffusers
English
controllable text-to-image generation
diffusion models
3D layout control
occlusion reasoning
Instructions to use va1bhavagrawa1/seethrough3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use va1bhavagrawa1/seethrough3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("va1bhavagrawa1/seethrough3d", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Move metadata to YAML header and add paper links
#1
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -1,18 +1,20 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
pipeline_tag:
|
| 5 |
-
|
| 6 |
-
language:
|
| 7 |
-
- en # List languages your model supports
|
| 8 |
-
license: apache-2.0 # Specify a license
|
| 9 |
datasets:
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
|
| 17 |
[](https://arxiv.org/abs/2602.23359)
|
| 18 |
[](https://seethrough3d.github.io)
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
library_name: diffusers
|
| 4 |
+
pipeline_tag: text-to-image
|
| 5 |
+
base_model: black-forest-labs/FLUX.1-dev
|
|
|
|
|
|
|
|
|
|
| 6 |
datasets:
|
| 7 |
+
- va1bhavagrawa1/seethrough3d-data
|
| 8 |
+
language:
|
| 9 |
+
- en
|
| 10 |
+
tags:
|
| 11 |
+
- controllable text-to-image generation
|
| 12 |
+
- diffusion models
|
| 13 |
+
- 3D layout control
|
| 14 |
+
- occlusion reasoning
|
| 15 |
+
---
|
| 16 |
+
|
| 17 |
+
# [CVPR-26 🎉] SeeThrough3D: Occlusion Aware 3D Control in Text-to-Image Generation
|
| 18 |
|
| 19 |
[](https://arxiv.org/abs/2602.23359)
|
| 20 |
[](https://seethrough3d.github.io)
|