Aguilar Elizondo commited on
Commit
ed8c1f8
·
1 Parent(s): 5c463fb

Add custom prompt field for user input

Browse files
Files changed (1) hide show
  1. app.py +18 -4
app.py CHANGED
@@ -34,6 +34,7 @@ def enhance_image_simple(
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  input_image: Image.Image,
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  strength: float,
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  guidance_scale: float,
 
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  use_upscaler: bool,
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  use_postprocess: bool,
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  progress=gr.Progress()
@@ -53,6 +54,13 @@ def enhance_image_simple(
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  logger.error(f"Model initialization failed: {e}", exc_info=True)
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  raise ValueError(f"Failed to load AI models: {str(e)}")
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  # Step 1: AI Enhancement
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  progress(0.3, desc="Applying AI enhancement (this may take several minutes on CPU)...")
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  try:
@@ -64,7 +72,7 @@ def enhance_image_simple(
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  enhanced = pipeline_manager.enhance(
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  image=input_image,
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- prompt="professional architectural photography, highly detailed, 8k, photorealistic",
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  negative_prompt="blurry, low quality, distorted, ugly, bad architecture",
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  strength=strength,
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  guidance_scale=guidance_scale,
@@ -113,9 +121,15 @@ iface = gr.Interface(
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  fn=enhance_image_simple,
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  inputs=[
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  gr.Image(label="Input Image", type="pil"),
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- gr.Slider(0.1, 0.8, value=0.3, step=0.05, label="Strength"),
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- gr.Slider(1.0, 15.0, value=5.5, step=0.5, label="Guidance Scale"),
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- gr.Checkbox(label="Enable Upscaling", value=True),
 
 
 
 
 
 
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  gr.Checkbox(label="Enable Post-Processing", value=True)
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  ],
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  outputs=gr.Image(label="Enhanced Image", type="pil"),
 
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  input_image: Image.Image,
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  strength: float,
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  guidance_scale: float,
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+ custom_prompt: str,
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  use_upscaler: bool,
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  use_postprocess: bool,
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  progress=gr.Progress()
 
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  logger.error(f"Model initialization failed: {e}", exc_info=True)
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  raise ValueError(f"Failed to load AI models: {str(e)}")
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+ # Build prompt
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+ base_prompt = "professional architectural photography, highly detailed, 8k, photorealistic"
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+ if custom_prompt and custom_prompt.strip():
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+ final_prompt = f"{base_prompt}, {custom_prompt.strip()}"
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+ else:
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+ final_prompt = base_prompt
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+
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  # Step 1: AI Enhancement
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  progress(0.3, desc="Applying AI enhancement (this may take several minutes on CPU)...")
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  try:
 
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  enhanced = pipeline_manager.enhance(
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  image=input_image,
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+ prompt=final_prompt,
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  negative_prompt="blurry, low quality, distorted, ugly, bad architecture",
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  strength=strength,
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  guidance_scale=guidance_scale,
 
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  fn=enhance_image_simple,
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  inputs=[
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  gr.Image(label="Input Image", type="pil"),
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+ gr.Slider(0.1, 0.8, value=0.3, step=0.05, label="Strength", info="Lower = more faithful to input, Higher = more creative"),
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+ gr.Slider(1.0, 15.0, value=5.5, step=0.5, label="Guidance Scale", info="How closely to follow the prompt"),
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+ gr.Textbox(
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+ label="Additional Prompt (Optional)",
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+ placeholder="e.g., modern minimalist, glass facade, sunset lighting...",
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+ lines=2,
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+ info="Add custom details to enhance specific aspects"
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+ ),
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+ gr.Checkbox(label="Enable Upscaling (2x)", value=True),
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  gr.Checkbox(label="Enable Post-Processing", value=True)
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  ],
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  outputs=gr.Image(label="Enhanced Image", type="pil"),