Connect diffusion pipeline progress to Gradio progress bar

app.py

@@ -56,13 +56,20 @@ def enhance_image_simple(
         # Step 1: AI Enhancement
         progress(0.3, desc="Applying AI enhancement (this may take several minutes on CPU)...")
         try:
+            # Create a callback to update progress during diffusion
+            def update_progress(percent, description):
+                # Map internal progress (30-85%) to our progress range
+                mapped_progress = 0.3 + (percent / 100) * 0.4  # 30% to 70%
+                progress(mapped_progress, desc=description)
+            
             enhanced = pipeline_manager.enhance(
                 image=input_image,
                 prompt="professional architectural photography, highly detailed, 8k, photorealistic",
                 negative_prompt="blurry, low quality, distorted, ugly, bad architecture",
                 strength=strength,
                 guidance_scale=guidance_scale,
-                num_inference_steps=30
+                num_inference_steps=30,
+                progress_callback=update_progress
             )
         except Exception as e:
             logger.error(f"AI enhancement failed: {e}", exc_info=True)
@@ -70,7 +77,7 @@ def enhance_image_simple(
         
         # Step 2: Upscaling
         if use_upscaler:
-            progress(0.7, desc="Upscaling image...")
+            progress(0.75, desc="Upscaling image...")
             try:
                 enhanced = upscale_image(enhanced, scale=2)
             except Exception as e:
@@ -78,7 +85,7 @@ def enhance_image_simple(
         
         # Step 3: Post-processing
         if use_postprocess:
-            progress(0.9, desc="Applying final touches...")
+            progress(0.85, desc="Applying final touches...")
             try:
                 enhanced = postprocess_image(
                     enhanced,