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Running
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Zero
guangkaixu
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Browse files- README.md +1 -1
- app.py +2 -1
- genpercept/genpercept_pipeline.py +1 -1
README.md
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@@ -17,7 +17,7 @@ If you find it useful, please cite our paper:
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```
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@article{xu2024diffusion,
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title={
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author={Xu, Guangkai and Ge, Yongtao and Liu, Mingyu and Fan, Chengxiang and Xie, Kangyang and Zhao, Zhiyue and Chen, Hao and Shen, Chunhua},
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journal={arXiv preprint arXiv:2403.06090},
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year={2024}
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```
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@article{xu2024diffusion,
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title={What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?},
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author={Xu, Guangkai and Ge, Yongtao and Liu, Mingyu and Fan, Chengxiang and Xie, Kangyang and Zhao, Zhiyue and Chen, Hao and Shen, Chunhua},
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journal={arXiv preprint arXiv:2403.06090},
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year={2024}
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app.py
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@@ -253,7 +253,8 @@ def run_demo_server(pipe_depth, pipe_normal, pipe_dis, pipe_matting, pipe_seg, p
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gr.Markdown(
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"""
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#
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<p align="center">
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<a title="arXiv" href="https://arxiv.org/abs/2403.06090" target="_blank" rel="noopener noreferrer"
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style="display: inline-block;">
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gr.Markdown(
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"""
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# What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?
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# (GenPercept: Diffusion Models Trained with Large Data Are Transferable Visual Models)
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<p align="center">
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<a title="arXiv" href="https://arxiv.org/abs/2403.06090" target="_blank" rel="noopener noreferrer"
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style="display: inline-block;">
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genpercept/genpercept_pipeline.py
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@@ -149,7 +149,7 @@ class GenPerceptPipeline(DiffusionPipeline):
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resample_method: str = "bilinear",
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batch_size: int = 0,
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generator: Union[torch.Generator, None] = None,
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-
color_map: str =
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show_progress_bar: bool = True,
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ensemble_kwargs: Dict = None,
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mode = None,
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resample_method: str = "bilinear",
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batch_size: int = 0,
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generator: Union[torch.Generator, None] = None,
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color_map: Union[str, None] = None,
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show_progress_bar: bool = True,
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ensemble_kwargs: Dict = None,
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mode = None,
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