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Update app.py
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app.py
CHANGED
@@ -18,7 +18,9 @@ from share_btn import community_icon_html, loading_icon_html, share_js
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from gallery_history import fetch_gallery_history, show_gallery_history
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from illusion_style import css
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BASE_MODEL = "HusseinHE/icbinh"
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# Initialize both pipelines
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vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse", torch_dtype=torch.float16)
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@@ -148,7 +150,7 @@ def inference(
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with gr.Blocks(css=css) as app:
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gr.Markdown(
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'''
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<center><h1>
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<span font-size:16px;">Generate stunning high quality illusion artwork with Stable Diffusion</span>
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</center>
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'''
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@@ -158,7 +160,7 @@ with gr.Blocks(css=css) as app:
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with gr.Column():
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control_image = gr.Image(label="Input Illusion", type="pil", elem_id="control_image")
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controlnet_conditioning_scale = gr.Slider(minimum=0.0, maximum=5.0, step=0.01, value=0.8, label="Illusion strength", elem_id="illusion_strength", info="ControlNet conditioning scale")
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gr.Examples(examples=["checkers.png", "checkers_mid.jpg", "pattern.png", "ultra_checkers.png", "spiral.jpeg", "funky.jpeg" ], inputs=control_image)
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prompt = gr.Textbox(label="Prompt", elem_id="prompt")
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negative_prompt = gr.Textbox(label="Negative Prompt", value="low quality", elem_id="negative_prompt")
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with gr.Accordion(label="Advanced Options", open=False):
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from gallery_history import fetch_gallery_history, show_gallery_history
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from illusion_style import css
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#BASE_MODEL = "HusseinHE/icbinh"
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BASE_MODEL = "SG161222/Realistic_Vision_V5.1_noVAE"
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# Initialize both pipelines
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vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse", torch_dtype=torch.float16)
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with gr.Blocks(css=css) as app:
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gr.Markdown(
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'''
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<center><h1>Poiesis Diffusion</h1></span>
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<span font-size:16px;">Generate stunning high quality illusion artwork with Stable Diffusion</span>
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</center>
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'''
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with gr.Column():
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control_image = gr.Image(label="Input Illusion", type="pil", elem_id="control_image")
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controlnet_conditioning_scale = gr.Slider(minimum=0.0, maximum=5.0, step=0.01, value=0.8, label="Illusion strength", elem_id="illusion_strength", info="ControlNet conditioning scale")
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gr.Examples(examples=["checkers.png", "checkers_mid.jpg", "pattern.png", "ultra_checkers.png", "spiral.jpeg", "funky.jpeg" , "poiesis.png" ], inputs=control_image)
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prompt = gr.Textbox(label="Prompt", elem_id="prompt")
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negative_prompt = gr.Textbox(label="Negative Prompt", value="low quality", elem_id="negative_prompt")
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with gr.Accordion(label="Advanced Options", open=False):
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