Spaces:
Running
on
Zero
Running
on
Zero
Commit
Β·
cb6f2d9
1
Parent(s):
1fc7110
adjust duration
Browse files
README.md
CHANGED
@@ -1,8 +1,8 @@
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---
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-
title:
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emoji: π
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colorFrom: purple
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-
colorTo:
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sdk: gradio
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sdk_version: 5.15.0
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app_file: app.py
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---
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title: MoD ControlNet Tile Upscaler SDXL
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emoji: π
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colorFrom: purple
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colorTo: red
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sdk: gradio
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sdk_version: 5.15.0
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app_file: app.py
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app.py
CHANGED
@@ -36,7 +36,7 @@ pipe.enable_vae_tiling() # << Enable this if you have limited VRAM
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pipe.enable_vae_slicing() # << Enable this if you have limited VRAM
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# region functions
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@spaces.GPU
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def predict(
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image,
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prompt,
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@@ -245,7 +245,7 @@ with gr.Blocks(css=css, theme=Platinum(), title="MoD ControlNet Tile Upscaler")
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with gr.Row(elem_id="parameters_row"):
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gr.Markdown("### General parameters")
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tile_weighting_method = gr.Dropdown(
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label="Tile Weighting
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)
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tile_gaussian_sigma = gr.Slider(label="Gaussian Sigma", minimum=0.05, maximum=1.0, step=0.01, value=0.3, visible=False)
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max_tile_size = gr.Dropdown(label="Max. Tile Size", choices=[1024, 1280], value=1024)
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pipe.enable_vae_slicing() # << Enable this if you have limited VRAM
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# region functions
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@spaces.GPU(duration=600)
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def predict(
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image,
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prompt,
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with gr.Row(elem_id="parameters_row"):
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gr.Markdown("### General parameters")
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tile_weighting_method = gr.Dropdown(
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label="Tile Weighting Method", choices=["Cosine", "Gaussian"], value="Cosine"
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)
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tile_gaussian_sigma = gr.Slider(label="Gaussian Sigma", minimum=0.05, maximum=1.0, step=0.01, value=0.3, visible=False)
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max_tile_size = gr.Dropdown(label="Max. Tile Size", choices=[1024, 1280], value=1024)
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