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Parent(s):
38df813
Update app.py
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app.py
CHANGED
@@ -14,8 +14,8 @@ sys.path.append("diffusion-point-cloud")
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from models.vae_gaussian import *
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from models.vae_flow import *
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airplane=
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chair=
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device='cuda' if torch.cuda.is_available() else 'cpu'
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@@ -99,10 +99,21 @@ def generate(seed,value):
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markdown=f'''
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# Diffusion Probabilistic Models for 3D Point Cloud Generation
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[
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It is running on {device}
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'''
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with gr.Blocks() as demo:
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with gr.Column():
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from models.vae_gaussian import *
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from models.vae_flow import *
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airplane=hf_hub_download("SerdarHelli/diffusion-point-cloud", filename="GEN_airplane.pt",revision="main")
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chair="./GEN_chair.pt"
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device='cuda' if torch.cuda.is_available() else 'cpu'
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markdown=f'''
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# Diffusion Probabilistic Models for 3D Point Cloud Generation
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[The space demo for the CVPR 2021 paper "Diffusion Probabilistic Models for 3D Point Cloud Generation".](https://arxiv.org/abs/2103.01458)
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[For the official implementation.](https://github.com/luost26/diffusion-point-cloud)
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It is running on {device}
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### Citation By
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@inproceedings{luo2021diffusion,
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author = {Luo, Shitong and Hu, Wei},
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title = {Diffusion Probabilistic Models for 3D Point Cloud Generation},
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booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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month = {June},
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year = {2021}
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}
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'''
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with gr.Blocks() as demo:
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with gr.Column():
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