Update app.py

app.py

@@ -5,37 +5,65 @@ from PIL import Image
 # Connect to the verified IC-Light engine
 client = Client("lllyasviel/IC-Light")
 
+def get_smart_resolution(width, height):
+    """
+    Intelligently picks the best resolution supported by the model
+    based on the input image's shape (Landscape vs Portrait).
+    This prevents the 'blurry/stretched' look.
+    """
+    aspect_ratio = width / height
+    if aspect_ratio > 1.2:  # Landscape
+        return 768, 512
+    elif aspect_ratio < 0.8: # Portrait
+        return 512, 768
+    else: # Square-ish
+        return 640, 640
+
 def dynamic_relight(image_path, prompt, lighting_choice, s1, s2, s3, s4):
     if image_path is None:
         return None
 
-    # 1. Slider Logic (Your Unique Feature)
-    keywords = ["cinematic", "detailed", "texture", "focus"]
+    # 1. SMART IMAGE PROCESSING
+    # Detect the shape of the uploaded image and resize correctly
+    img = Image.open(image_path)
+    orig_w, orig_h = img.size
+    target_w, target_h = get_smart_resolution(orig_w, orig_h)
+    
+    img.thumbnail((target_w, target_h)) 
+    safe_path = "smart_input.png"
+    img.save(safe_path)
+
+    # 2. CALIBRATED SLIDER LOGIC (Safety Rails)
+    # We map 0-100 to a safe range (0.0 to 1.6) to prevent "frying" the image
+    keywords = ["cinematic", "highly detailed", "sharp texture", "deep focus"]
     slider_vals = [s1, s2, s3, s4]
-    weighted_prompt = prompt
+    
+    user_adjustments = ""
     for i, word in enumerate(keywords):
-        weight = slider_vals[i] / 50.0 
-        weighted_prompt += f", ({word}:{weight:.1f})"
+        if slider_vals[i] > 0:
+            # Formula: 100 becomes 1.6 weight (Safe Maximum)
+            weight = 0.8 + (slider_vals[i] / 100.0) * 0.8 
+            user_adjustments += f", ({word}:{weight:.1f})"
     
-    # 2. MATCHING YOUR SCREENSHOT RESOLUTION
-    # Your screenshot shows 512x960. We must use this to get the same composition.
-    img = Image.open(image_path)
-    img.thumbnail((512, 960)) 
-    safe_path = "classic_input.png"
-    img.save(safe_path)
+    # 3. THE "MAGIC" QUALITY BOOSTER
+    # We force these keywords onto every request to guarantee professional output
+    # irrespective of what the user types.
+    quality_guard = ", masterpiece, best quality, ultra-realistic, 8k uhd, dslr, soft lighting, volumetric lighting"
+    
+    # Final robust prompt
+    final_prompt = prompt + quality_guard + user_adjustments
 
-    # 3. THE "CLASSIC" PAYLOAD
     try:
         result = client.predict(
             input_fg=handle_file(safe_path),   
-            prompt=weighted_prompt,            
-            image_width=512,                   
-            image_height=960,                  # FIXED: Matches your screenshot
+            prompt=final_prompt,               
+            image_width=target_w,              # Smart Resolution Width
+            image_height=target_h,             # Smart Resolution Height
             num_samples=1,                     
-            seed=8888,                         # CRITICAL FIX: The "Sunlight" Seed
-            steps=25,                          
-            a_prompt="best quality",           
-            n_prompt="lowres, bad anatomy",    
+            seed=12345,                        # Standard stable seed
+            steps=30,                          # Increased steps for better quality
+            a_prompt="best quality, masterpiece",           
+            n_prompt="lowres, bad anatomy, blurry, noisy, grain, distorted",    
             cfg=2.0,                           
             highres_scale=1.5,                 
             highres_denoise=0.5,               
@@ -43,29 +71,30 @@ def dynamic_relight(image_path, prompt, lighting_choice, s1, s2, s3, s4):
             bg_source=lighting_choice,         
             api_name="/process_relight"        
         )
-        # Extract image from gallery tuple
         return result[1][0]['image']
         
     except Exception as e:
-        raise gr.Error(f"Execution Failed: {str(e)}")
+        raise gr.Error(f"System Error: {str(e)}")
 
 # UI Setup
-with gr.Blocks() as demo:
-    gr.Markdown("# 💡 Final 'Classic' Feature Relighter")
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# ⚡ Smart Robust Relighter")
+    gr.Markdown("Auto-enhances quality regardless of input parameters.")
+    
     with gr.Row():
         with gr.Column():
-            img = gr.Image(type="filepath", label="Input Image")
-            # The prompt is now correct because the SEED (8888) handles the lighting style
-            txt = gr.Textbox(label="Base Prompt", value="beautiful woman, detailed face, light and shadow")
-            dirs = gr.Radio(["Left Light", "Right Light", "Top Light", "Bottom Light"], label="Light Direction", value="Left Light")
+            img = gr.Image(type="filepath", label="Input Image (Any Size)")
+            txt = gr.Textbox(label="Base Prompt", value="beautiful woman, detailed face")
+            dirs = gr.Radio(["Left Light", "Right Light", "Top Light", "Bottom Light"], label="Light Direction", value="Right Light")
             
+            gr.Markdown("### Enhancement Sliders")
             s1 = gr.Slider(0, 100, value=50, label="Cinematic Intensity")
             s2 = gr.Slider(0, 100, value=50, label="Detail Level")
             s3 = gr.Slider(0, 100, value=50, label="Texture Sharpness")
             s4 = gr.Slider(0, 100, value=50, label="Focus Depth")
             
-            btn = gr.Button("Execute Classic Relight", variant="primary")
-        out = gr.Image(label="Output")
+            btn = gr.Button("Execute Smart Relight", variant="primary")
+        out = gr.Image(label="Enhanced Output")
 
     btn.click(dynamic_relight, [img, txt, dirs, s1, s2, s3, s4], out)