Image-to-Image
Diffusers
reflection-removal
reflection-separation
image-restoration
diffusion
stable-diffusion
cvpr2026
Instructions to use Brian9999/diff-reflection-separation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Brian9999/diff-reflection-separation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Brian9999/diff-reflection-separation", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Beian
#2
by Devintryan - opened
Brian. This is good work. Im currently building a video diffusion system that predicts engagement + edits before rendering. Looking for someone who has trained or fine-tuned diffusion/video transformers. Do you consult? If so Devin@PineappleHi.com