Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
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@@ -192,7 +192,7 @@ DEFAULT_VALUES = {
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}
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# Define example data
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[
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"examples/1.png", # Input image path
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"clean, texture, high-resolution, 8k", # Prompt
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@@ -250,43 +250,6 @@ examples = [
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]
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]
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def process_example(img_path, prompt_text, neg_prompt, guid_scale, cond_scale, steps, seed_val, up_factor, color_method):
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# First update the input fields and preview
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yield [
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img_path, # input_image
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prompt_text,
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neg_prompt,
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guid_scale,
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cond_scale,
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steps,
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seed_val,
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up_factor,
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color_method,
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img_path, # preview_input
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gr.update(value=None, label="Processing...") # output_image
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]
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# Process the image
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output = process_image(
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img_path, prompt_text, neg_prompt, guid_scale,
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cond_scale, steps, seed_val, up_factor, color_method
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)
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# Return final result
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yield [
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img_path, # input_image
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prompt_text,
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neg_prompt,
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guid_scale,
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cond_scale,
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steps,
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seed_val,
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up_factor,
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color_method,
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img_path, # preview_input
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gr.update(value=output, label="Generated Image") # output_image
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]
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# Create interface components
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with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
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gr.Markdown("## Controllable Conditional Super-Resolution")
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@@ -315,43 +278,24 @@ with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
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submit_btn = gr.Button("Submit", variant="primary")
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with gr.Column():
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preview_input = gr.Image(label="Preview Input")
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output_image = gr.Image(label="Generated Image")
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# Add
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color_fix_method, preview_input, output_image
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],
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fn=process_example,
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cache_examples=True,
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)
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# Define submit action with progress
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def process_with_progress(img, prompt_text, neg_prompt, guid_scale, cond_scale, steps, seed_val, up_factor, color_method):
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# Update UI to show processing state
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yield gr.update(value=None, label="Processing...")
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# Process image
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result = process_image(
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img, prompt_text, neg_prompt, guid_scale,
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cond_scale, steps, seed_val, up_factor, color_method
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)
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# Return final result
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yield gr.update(value=result, label="Generated Image")
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submit_btn.click(
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fn=
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inputs=[
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input_image, prompt, negative_prompt, guidance_scale,
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conditioning_scale, num_steps, seed, upscale_factor,
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@@ -360,16 +304,6 @@ with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
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outputs=output_image
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)
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# Add event handler for input image change
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def update_preview(img):
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return img if img is not None else None
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input_image.change(
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fn=update_preview,
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inputs=input_image,
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outputs=preview_input
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)
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# Define clear action that resets to default values
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def reset_to_defaults():
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return [
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@@ -381,9 +315,7 @@ with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
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DEFAULT_VALUES["num_steps"],
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DEFAULT_VALUES["seed"],
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DEFAULT_VALUES["upscale_factor"],
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DEFAULT_VALUES["color_fix_method"]
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None, # preview_input
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None # output_image
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]
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clear_btn.click(
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@@ -392,9 +324,9 @@ with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
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outputs=[
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input_image, prompt, negative_prompt, guidance_scale,
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conditioning_scale, num_steps, seed, upscale_factor,
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color_fix_method
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]
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)
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if __name__ == "__main__":
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demo.launch()
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}
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# Define example data
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EXAMPLES = [
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[
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"examples/1.png", # Input image path
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"clean, texture, high-resolution, 8k", # Prompt
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]
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]
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# Create interface components
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with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
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gr.Markdown("## Controllable Conditional Super-Resolution")
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submit_btn = gr.Button("Submit", variant="primary")
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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# Add examples
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gr.Examples(
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examples=EXAMPLES,
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inputs=[
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input_image, prompt, negative_prompt, guidance_scale,
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conditioning_scale, num_steps, seed, upscale_factor,
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color_fix_method
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],
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outputs=output_image,
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fn=process_image,
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cache_examples=True # Cache the results for faster loading
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)
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# Define submit action
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submit_btn.click(
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fn=process_image,
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inputs=[
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input_image, prompt, negative_prompt, guidance_scale,
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conditioning_scale, num_steps, seed, upscale_factor,
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outputs=output_image
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)
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# Define clear action that resets to default values
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def reset_to_defaults():
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return [
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DEFAULT_VALUES["num_steps"],
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DEFAULT_VALUES["seed"],
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DEFAULT_VALUES["upscale_factor"],
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DEFAULT_VALUES["color_fix_method"]
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]
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clear_btn.click(
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outputs=[
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input_image, prompt, negative_prompt, guidance_scale,
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conditioning_scale, num_steps, seed, upscale_factor,
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color_fix_method
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]
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)
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if __name__ == "__main__":
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demo.launch()
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