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Running on Zero
Running on Zero
Update app.py
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app.py
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@@ -1,5 +1,4 @@
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import gradio as gr
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import torch
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import spaces
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@@ -132,10 +131,10 @@ with gr.Blocks() as demo:
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box_detail_phrases_list = gr.Dataframe(headers=["Region Captions"], label="Region Captions")
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boxes = gr.Dataframe(headers=["x1", "y1", "x2", "y2"], label="Region Bounding Boxes (x_min,y_min,x_max,y_max)")
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with gr.Accordion("Advanced Settings", open=False):
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seed = gr.Slider(0, 100, step=1, label="Seed", value=
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randomize_seed = gr.Checkbox(label="Randomize seed", value=False)
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guidance_scale = gr.Slider(1, 30, step=0.5, label="Guidance Scale", value=7.5)
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num_inference_steps = gr.Slider(1, 50, step=1, label="Number of inference steps", value=
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with gr.Column():
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bbox_visualization_img = gr.Image(type="pil", label="Bounding Box Visualization")
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import gradio as gr
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import torch
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import spaces
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box_detail_phrases_list = gr.Dataframe(headers=["Region Captions"], label="Region Captions")
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boxes = gr.Dataframe(headers=["x1", "y1", "x2", "y2"], label="Region Bounding Boxes (x_min,y_min,x_max,y_max)")
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with gr.Accordion("Advanced Settings", open=False):
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seed = gr.Slider(0, 100, step=1, label="Seed", value=21)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=False)
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guidance_scale = gr.Slider(1, 30, step=0.5, label="Guidance Scale", value=7.5)
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num_inference_steps = gr.Slider(1, 50, step=1, label="Number of inference steps", value=28)
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with gr.Column():
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bbox_visualization_img = gr.Image(type="pil", label="Bounding Box Visualization")
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