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Running
on
L40S
Running
on
L40S
Commit
•
69c6cfb
1
Parent(s):
fd1c741
Update app.py
Browse files
app.py
CHANGED
@@ -154,7 +154,7 @@ depthanything_v2 = NODE_CLASS_MAPPINGS["DepthAnything_V2"]()
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imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
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@spaces.GPU
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def generate_image(prompt
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"""Main generation function that processes inputs and returns the path to the generated image."""
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with torch.inference_mode():
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# Set up CLIP
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@@ -288,9 +288,16 @@ def generate_image(prompt: str, structure_image: str, depth_strength: float, sty
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return saved_path
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# Create Gradio interface
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with gr.Blocks() as app:
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gr.Markdown("#
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with gr.Row():
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with gr.Column():
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prompt_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
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@@ -305,10 +312,16 @@ with gr.Blocks() as app:
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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generate_btn.click(
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fn=generate_image,
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inputs=[prompt_input, structure_image,
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outputs=[output_image]
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)
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imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
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@spaces.GPU
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def generate_image(prompt, structure_image, style_image, depth_strength=15, style_strength=0.5, progress=gr.Progress(track_tqdm=True)) -> str:
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"""Main generation function that processes inputs and returns the path to the generated image."""
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with torch.inference_mode():
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# Set up CLIP
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return saved_path
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# Create Gradio interface
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examples = [
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["", "mona.png", "receita-tacos.webp"],
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["a woman looking at a house catching fire on the background", "disaster_girl.png", "abaporu.jpg"]
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["istanbul aerial, dramatic photography", "natasha.png", "istambul.png"],
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]
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with gr.Blocks() as app:
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gr.Markdown("# FLUX Style Shaping")
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gr.Markdown("## Flux[dev] Redux + Flux[dev] Depth ComfyUI workflow by [CitizenPlain](https://x.com/CitizenPlain) running directly on Gradio. [workflow](https://gist.github.com/nathanshipley/7a9ac1901adde76feebe58d558026f68) - [how to convert your comfy workflow to gradio (soon)](#)")
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with gr.Row():
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with gr.Column():
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prompt_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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gr.Examples(
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examples=examples,
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inputs=[prompt, structure_image, style_image],
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outputs=[output_image]
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fn=generate_image,
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cache_examples="lazy"
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)
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generate_btn.click(
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fn=generate_image,
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inputs=[prompt_input, structure_image, style_image, depth_strength, style_strength],
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outputs=[output_image]
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)
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