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Runtime error
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fb81033
1
Parent(s):
53e8420
Update app.py
Browse files
app.py
CHANGED
@@ -485,7 +485,7 @@ with gr.Blocks(css=css, delete_cache=(60, 3600)) as app:
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with gr.Column(scale=8):
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with gr.Row():
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with gr.Column(scale=0, min_width=50):
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lora_image_1 = gr.Image(label="LoRA 1 Image", interactive=False, min_width=50, width=50, show_label=False, show_share_button=False, show_download_button=False, show_fullscreen_button=False, height=50)
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with gr.Column(scale=3, min_width=100):
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selected_info_1 = gr.Markdown("Select a LoRA 1")
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with gr.Column(scale=5, min_width=50):
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@@ -495,7 +495,7 @@ with gr.Blocks(css=css, delete_cache=(60, 3600)) as app:
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with gr.Column(scale=8):
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with gr.Row():
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with gr.Column(scale=0, min_width=50):
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-
lora_image_2 = gr.Image(label="LoRA 2 Image", interactive=False, min_width=50, width=50, show_label=False, show_share_button=False, show_download_button=False, show_fullscreen_button=False, height=50)
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with gr.Column(scale=3, min_width=100):
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selected_info_2 = gr.Markdown("Select a LoRA 2")
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with gr.Column(scale=5, min_width=50):
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@@ -515,18 +515,19 @@ with gr.Blocks(css=css, delete_cache=(60, 3600)) as app:
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label="Or pick from the LoRA Explorer gallery",
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allow_preview=False,
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columns=5,
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elem_id="gallery"
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)
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with gr.Column():
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progress_bar = gr.Markdown(elem_id="progress", visible=False)
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result = gr.Image(label="Generated Image", interactive=False)
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with gr.Accordion("History", open=False):
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history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain", interactive=False)
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with gr.Row():
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with gr.Accordion("Advanced Settings", open=False):
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with gr.Row():
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input_image = gr.Image(label="Input image", type="filepath")
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image_strength = gr.Slider(label="Denoise Strength", info="Lower means more image influence", minimum=0.1, maximum=1.0, step=0.01, value=0.75)
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with gr.Column():
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with gr.Row():
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@@ -575,7 +576,7 @@ with gr.Blocks(css=css, delete_cache=(60, 3600)) as app:
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fn=run_lora,
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inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2, randomize_seed, seed, width, height, loras_state],
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outputs=[result, seed, progress_bar]
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).then(
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fn=lambda x, history: update_history(x, history),
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inputs=[result, history_gallery],
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outputs=history_gallery,
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with gr.Column(scale=8):
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with gr.Row():
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with gr.Column(scale=0, min_width=50):
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lora_image_1 = gr.Image(label="LoRA 1 Image", interactive=False, min_width=50, width=50, show_label=False, show_share_button=False, show_download_button=False, show_fullscreen_button=False, height=50, show_share_button=False)
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with gr.Column(scale=3, min_width=100):
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selected_info_1 = gr.Markdown("Select a LoRA 1")
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with gr.Column(scale=5, min_width=50):
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with gr.Column(scale=8):
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with gr.Row():
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with gr.Column(scale=0, min_width=50):
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lora_image_2 = gr.Image(label="LoRA 2 Image", interactive=False, min_width=50, width=50, show_label=False, show_share_button=False, show_download_button=False, show_fullscreen_button=False, height=50, show_share_button=False)
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with gr.Column(scale=3, min_width=100):
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selected_info_2 = gr.Markdown("Select a LoRA 2")
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with gr.Column(scale=5, min_width=50):
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label="Or pick from the LoRA Explorer gallery",
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allow_preview=False,
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columns=5,
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elem_id="gallery",
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show_share_button=False
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)
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with gr.Column():
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progress_bar = gr.Markdown(elem_id="progress", visible=False)
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result = gr.Image(label="Generated Image", interactive=False, show_share_button=False)
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with gr.Accordion("History", open=False):
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history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain", interactive=False)
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with gr.Row():
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with gr.Accordion("Advanced Settings", open=False):
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with gr.Row():
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input_image = gr.Image(label="Input image", type="filepath", show_share_button=False)
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image_strength = gr.Slider(label="Denoise Strength", info="Lower means more image influence", minimum=0.1, maximum=1.0, step=0.01, value=0.75)
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with gr.Column():
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with gr.Row():
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fn=run_lora,
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inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2, randomize_seed, seed, width, height, loras_state],
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outputs=[result, seed, progress_bar]
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).then(
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fn=lambda x, history: update_history(x, history),
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inputs=[result, history_gallery],
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outputs=history_gallery,
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