Instructions to use LinxiaoShi/Magicbokeh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LinxiaoShi/Magicbokeh 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("LinxiaoShi/Magicbokeh", 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
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This repository contains the model and code for **Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework**, as presented in the paper:
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**Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework**
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## Abstract
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This repository contains the model and code for **Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework**, as presented in the paper:
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[**Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework**](https://arxiv.org/abs/2605.07429)
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## Abstract
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