Update app.py
Browse files
app.py
CHANGED
@@ -242,7 +242,7 @@ with block:
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gr.Markdown("## Canny Edge")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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low_threshold = gr.Slider(label="low_threshold", minimum=1, maximum=255, value=100, step=1)
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high_threshold = gr.Slider(label="high_threshold", minimum=1, maximum=255, value=200, step=1)
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@@ -276,7 +276,7 @@ with block:
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gr.Markdown("## HED Edge "SoftEdge"")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -290,7 +290,7 @@ with block:
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gr.Markdown("## Pidi Edge "SoftEdge"")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -305,7 +305,7 @@ with block:
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gr.Markdown("## MLSD Edge")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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value_threshold = gr.Slider(label="value_threshold", minimum=0.01, maximum=2.0, value=0.1, step=0.01)
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distance_threshold = gr.Slider(label="distance_threshold", minimum=0.01, maximum=20.0, value=0.1, step=0.01)
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@@ -322,7 +322,7 @@ with block:
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gr.Markdown("## MIDAS Depth")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
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run_button = gr.Button("Run")
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@@ -338,7 +338,7 @@ with block:
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gr.Markdown("## Zoe Depth")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -353,7 +353,7 @@ with block:
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gr.Markdown("## Normal Bae")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -368,7 +368,7 @@ with block:
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gr.Markdown("## DWPose")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -383,7 +383,7 @@ with block:
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gr.Markdown("## Openpose")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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hand_and_face = gr.Checkbox(label='Hand and Face', value=False)
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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@@ -399,7 +399,7 @@ with block:
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gr.Markdown("## Lineart Anime \n<p>Check Invert to use with Mochi Diffusion.")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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invert = gr.Checkbox(label='Invert', value=True)
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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@@ -415,7 +415,7 @@ with block:
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gr.Markdown("## Lineart \n<p>Check Invert to use with Mochi Diffusion. Inverted image can also be created here for use with ControlNet Scribble.")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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coarse = gr.Checkbox(label='Using coarse model', value=False)
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invert = gr.Checkbox(label='Invert', value=True)
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@@ -443,7 +443,7 @@ with block:
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gr.Markdown("## Oneformer COCO Segmentation")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -458,7 +458,7 @@ with block:
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gr.Markdown("## Oneformer ADE20K Segmentation")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=640, step=64)
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run_button = gr.Button("Run")
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@@ -472,7 +472,7 @@ with block:
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gr.Markdown("## Content Shuffle")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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@@ -487,7 +487,7 @@ with block:
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gr.Markdown("## Color Shuffle")
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with gr.Row():
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with gr.Column():
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-
input_image = gr.Image
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Canny Edge")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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low_threshold = gr.Slider(label="low_threshold", minimum=1, maximum=255, value=100, step=1)
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high_threshold = gr.Slider(label="high_threshold", minimum=1, maximum=255, value=200, step=1)
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gr.Markdown("## HED Edge "SoftEdge"")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Pidi Edge "SoftEdge"")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## MLSD Edge")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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value_threshold = gr.Slider(label="value_threshold", minimum=0.01, maximum=2.0, value=0.1, step=0.01)
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distance_threshold = gr.Slider(label="distance_threshold", minimum=0.01, maximum=20.0, value=0.1, step=0.01)
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gr.Markdown("## MIDAS Depth")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Zoe Depth")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Normal Bae")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## DWPose")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Openpose")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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hand_and_face = gr.Checkbox(label='Hand and Face', value=False)
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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gr.Markdown("## Lineart Anime \n<p>Check Invert to use with Mochi Diffusion.")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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invert = gr.Checkbox(label='Invert', value=True)
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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gr.Markdown("## Lineart \n<p>Check Invert to use with Mochi Diffusion. Inverted image can also be created here for use with ControlNet Scribble.")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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coarse = gr.Checkbox(label='Using coarse model', value=False)
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invert = gr.Checkbox(label='Invert', value=True)
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gr.Markdown("## Oneformer COCO Segmentation")
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with gr.Row():
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with gr.Column():
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input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Oneformer ADE20K Segmentation")
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with gr.Row():
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with gr.Column():
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+
input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=640, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Content Shuffle")
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with gr.Row():
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with gr.Column():
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+
input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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gr.Markdown("## Color Shuffle")
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with gr.Row():
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with gr.Column():
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+
input_image = gr.Image(label="Input Image", type="numpy", height=480)
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# input_image = gr.Image(source='upload', type="numpy")
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resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
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run_button = gr.Button("Run")
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