Wenzheng Chang commited on
Commit
a186246
·
1 Parent(s): 85c6af9

update warning pos

Browse files
Files changed (1) hide show
  1. app.py +14 -15
app.py CHANGED
@@ -1377,6 +1377,20 @@ with gr.Blocks(
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  with gr.Row(elem_classes=["main-interface"]):
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  with gr.Column(elem_classes=["input-column"]):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  with gr.Group(elem_classes=["task-selector"]):
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  task = gr.Radio(
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  ["reconstruction", "prediction", "planning"],
@@ -1384,21 +1398,6 @@ with gr.Blocks(
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  value="reconstruction",
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  info="Choose the task you want to perform",
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  )
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- gpu_time_warning = gr.Markdown(
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- """
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- <div class="warning-box">
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- <strong>⚠️ Warning:</strong><br>
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- Due to HuggingFace Spaces ZERO GPU quota limitations, only short video reconstruction tasks (less than 100 frames) can be completed online.
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-
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- <strong>💻 Recommendation:</strong><br>
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- We strongly encourage you to deploy Aether locally for:
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- • Processing longer video reconstruction tasks
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- • Better performance and full access to prediction and planning tasks
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- Visit our <a href="https://github.com/OpenRobotLab/Aether" target="_blank">GitHub repository</a> for local deployment instructions.
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- </div>
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- """,
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- visible=True,
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- )
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  with gr.Group(elem_classes=["input-section"]):
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  gr.Markdown("## 📥 Input", elem_classes=["task-header"])
 
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  with gr.Row(elem_classes=["main-interface"]):
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  with gr.Column(elem_classes=["input-column"]):
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+ gpu_time_warning = gr.Markdown(
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+ """
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+ <div class="warning-box">
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+ <strong>⚠️ Warning:</strong><br>
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+ Due to HuggingFace Spaces ZERO GPU quota limitations, only short video reconstruction tasks (less than 100 frames) can be completed online.
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+
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+ <strong>💻 Recommendation:</strong><br>
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+ We strongly encourage you to deploy Aether locally for:
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+ • Processing longer video reconstruction tasks
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+ • Better performance and full access to prediction and planning tasks
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+ Visit our <a href="https://github.com/OpenRobotLab/Aether" target="_blank">GitHub repository</a> for local deployment instructions.
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+ </div>
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+ """,
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+ )
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  with gr.Group(elem_classes=["task-selector"]):
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  task = gr.Radio(
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  ["reconstruction", "prediction", "planning"],
 
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  value="reconstruction",
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  info="Choose the task you want to perform",
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  )
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  with gr.Group(elem_classes=["input-section"]):
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  gr.Markdown("## 📥 Input", elem_classes=["task-header"])