Update app.py

app.py

@@ -7,64 +7,61 @@ 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.
+    Auto-detects Landscape/Portrait to prevent stretching.
     """
     aspect_ratio = width / height
-    if aspect_ratio > 1.2:  # Landscape
+    if aspect_ratio > 1.2:  # Landscape (Like your new photo)
         return 768, 512
     elif aspect_ratio < 0.8: # Portrait
         return 512, 768
-    else: # Square-ish
+    else: # Square
         return 640, 640
 
 def dynamic_relight(image_path, prompt, lighting_choice, s1, s2, s3, s4):
     if image_path is None:
         return None
 
-    # 1. SMART IMAGE PROCESSING
-    # Detect the shape of the uploaded image and resize correctly
+    # 1. SMART RESOLUTION
     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"
+    safe_path = "robust_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"]
+    # 2. CALIBRATED SLIDERS (Visual Enhancement ONLY)
+    # We removed "Cinematic" from the hidden logic to prevent darkness.
+    # Now sliders only add QUALITY (Sharpness, Texture), not Darkness.
+    keywords = ["ultra detailed", "sharp texture", "realistic skin", "perfect focus"]
     slider_vals = [s1, s2, s3, s4]
     
     user_adjustments = ""
     for i, word in enumerate(keywords):
         if slider_vals[i] > 0:
-            # Formula: 100 becomes 1.6 weight (Safe Maximum)
-            weight = 0.8 + (slider_vals[i] / 100.0) * 0.8 
+            weight = 0.5 + (slider_vals[i] / 100.0) * 0.7  # Gentle range (0.5 to 1.2)
             user_adjustments += f", ({word}:{weight:.1f})"
     
-    # 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"
+    # 3. THE "DAYLIGHT PROTECTION" GUARD
+    # This acts as a firewall. It blocks the model from making the image dark.
+    # It forces 'global illumination' so the background stays visible.
+    lighting_guard = ", natural lighting, ambient light, global illumination, balanced exposure, detailed background, raw photo"
     
-    # Final robust prompt
-    final_prompt = prompt + quality_guard + user_adjustments
+    # We combine your prompt + The Guard + The Sliders
+    final_prompt = prompt + lighting_guard + user_adjustments
 
     try:
         result = client.predict(
             input_fg=handle_file(safe_path),   
             prompt=final_prompt,               
-            image_width=target_w,              # Smart Resolution Width
-            image_height=target_h,             # Smart Resolution Height
+            image_width=target_w,              
+            image_height=target_h,             
             num_samples=1,                     
-            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,                           
+            seed=12345,                        
+            steps=30,                          
+            a_prompt="best quality, masterpiece, 8k uhd", # Pure Quality boosters           
+            n_prompt="lowres, bad anatomy, dark, moody, shadow, silhouette, black background", # ANTI-DARKNESS Negative Prompts
+            cfg=1.8,                           # Slightly lower CFG prevents "hallucinating" new backgrounds
             highres_scale=1.5,                 
             highres_denoise=0.5,               
             lowres_denoise=0.9,                
@@ -78,22 +75,26 @@ def dynamic_relight(image_path, prompt, lighting_choice, s1, s2, s3, s4):
 
 # UI Setup
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# ⚡ Smart Robust Relighter")
-    gr.Markdown("Auto-enhances quality regardless of input parameters.")
+    gr.Markdown("# ☀️ Robust Daylight Relighter")
+    gr.Markdown("Guarantees bright, high-quality results for any input image.")
     
     with gr.Row():
         with gr.Column():
-            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")
+            img = gr.Image(type="filepath", label="Input Image")
             
-            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")
+            # DEFAULT PROMPT is now generic and safe
+            txt = gr.Textbox(label="Prompt (Optional)", value="beautiful woman, detailed face")
             
-            btn = gr.Button("Execute Smart Relight", variant="primary")
+            dirs = gr.Radio(["Left Light", "Right Light", "Top Light", "Bottom Light"], label="Light Direction", value="Top Light")
+            
+            gr.Markdown("### Enhancement (Safe Range)")
+            # Renamed 'Cinematic' to 'Contrast' to be accurate
+            s1 = gr.Slider(0, 100, value=20, label="Contrast Boost") 
+            s2 = gr.Slider(0, 100, value=80, label="Detail Level")
+            s3 = gr.Slider(0, 100, value=70, label="Texture Sharpness")
+            s4 = gr.Slider(0, 100, value=60, label="Focus Depth")
+            
+            btn = gr.Button("Execute Robust Relight", variant="primary")
         out = gr.Image(label="Enhanced Output")
 
     btn.click(dynamic_relight, [img, txt, dirs, s1, s2, s3, s4], out)