Spaces:
Running
on
Zero
Running
on
Zero
Wenzheng Chang
commited on
Commit
·
a186246
1
Parent(s):
85c6af9
update warning pos
Browse files
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"],
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@@ -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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<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"])
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