wondervictor commited on
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1 Parent(s): 627dbc0

Update app.py

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Files changed (1) hide show
  1. app.py +15 -14
app.py CHANGED
@@ -13,6 +13,21 @@ import os
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  # filename='depth_MR.safetensors',
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  # local_dir='./checkpoints/')
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  # # hf_hub_download('google/flan-t5-xl', cache_dir='./checkpoints/')
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  DESCRIPTION = "# [ControlAR: Controllable Image Generation with Autoregressive Models](https://arxiv.org/abs/2410.02705) \n ### The first row in outputs is the input image and condition. The second row is the images generated by ControlAR. \n ### You can run locally by following the instruction on our [Github Repo](https://github.com/hustvl/ControlAR)."
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  SHOW_DUPLICATE_BUTTON = os.getenv("SHOW_DUPLICATE_BUTTON") == "1"
@@ -33,18 +48,4 @@ with gr.Blocks(css="style.css") as demo:
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  create_demo_canny(model.process_canny)
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  if __name__ == "__main__":
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- ckpt_folder = './checkpoints'
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- t5_folder = os.path.join(ckpt_folder, "flan-t5-xl/flan-t5-xl")
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="config.json", local_dir=t5_folder)
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model-00001-of-00002.bin", local_dir=t5_folder)
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model-00002-of-00002.bin", local_dir=t5_folder)
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model.bin.index.json", local_dir=t5_folder)
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="special_tokens_map.json", local_dir=t5_folder)
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="spiece.model", local_dir=t5_folder)
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- hf_hub_download(repo_id="google/flan-t5-xl", filename="tokenizer_config.json", local_dir=t5_folder)
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-
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- hf_hub_download(repo_id="lllyasviel/Annotators", filename="dpt_hybrid-midas-501f0c75.pt", local_dir=ckpt_folder)
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-
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- hf_hub_download(repo_id="wondervictor/ControlAR", filename="canny_MR.safetensors", local_dir=ckpt_folder)
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- hf_hub_download(repo_id="wondervictor/ControlAR", filename="depth_MR.safetensors", local_dir=ckpt_folder)
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  demo.launch(share=False)
 
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  # filename='depth_MR.safetensors',
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  # local_dir='./checkpoints/')
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  # # hf_hub_download('google/flan-t5-xl', cache_dir='./checkpoints/')
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+ ckpt_folder = './checkpoints'
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+ t5_folder = os.path.join(ckpt_folder, "flan-t5-xl/flan-t5-xl")
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="config.json", local_dir=t5_folder)
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model-00001-of-00002.bin", local_dir=t5_folder)
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model-00002-of-00002.bin", local_dir=t5_folder)
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="pytorch_model.bin.index.json", local_dir=t5_folder)
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="special_tokens_map.json", local_dir=t5_folder)
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="spiece.model", local_dir=t5_folder)
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+ hf_hub_download(repo_id="google/flan-t5-xl", filename="tokenizer_config.json", local_dir=t5_folder)
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+
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+ hf_hub_download(repo_id="lllyasviel/Annotators", filename="dpt_hybrid-midas-501f0c75.pt", local_dir=ckpt_folder)
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+
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+ hf_hub_download(repo_id="wondervictor/ControlAR", filename="canny_MR.safetensors", local_dir=ckpt_folder)
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+ hf_hub_download(repo_id="wondervictor/ControlAR", filename="depth_MR.safetensors", local_dir=ckpt_folder)
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+
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  DESCRIPTION = "# [ControlAR: Controllable Image Generation with Autoregressive Models](https://arxiv.org/abs/2410.02705) \n ### The first row in outputs is the input image and condition. The second row is the images generated by ControlAR. \n ### You can run locally by following the instruction on our [Github Repo](https://github.com/hustvl/ControlAR)."
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  SHOW_DUPLICATE_BUTTON = os.getenv("SHOW_DUPLICATE_BUTTON") == "1"
 
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  create_demo_canny(model.process_canny)
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  if __name__ == "__main__":
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  demo.launch(share=False)