Upload 2 files

app.py

@@ -106,7 +106,7 @@ def get_model_status():
         status_text += f"- Custom Checkpoint (Horizon): {'[OK] Loaded' if converter.models_loaded['custom_checkpoint'] else '[OK] Using SDXL base'}\n"
         status_text += f"- LORA (RetroArt): {'[OK] Loaded' if converter.models_loaded['lora'] else ' Disabled'}\n"
         status_text += f"- InstantID: {'[OK] Loaded' if converter.models_loaded['instantid'] else ' Disabled'}\n"
-        status_text += f"- Leres Depth: {'[OK] Loaded' if converter.models_loaded['leres_depth'] else ' Fallback'}\n"
+        status_text += f"- Depth: Grayscale (simple & reliable)\n"
         status_text += f"- IP-Adapter (Face Embeddings): {'[OK] Loaded' if converter.models_loaded.get('ip_adapter', False) else ' Keypoints only'}\n"
         return status_text
     return "**Model status unavailable**"
@@ -452,4 +452,4 @@ if __name__ == "__main__":
         server_port=7860,
         share=True,
         show_api=True
-    )
+    )

generator.py

@@ -40,9 +40,9 @@ class RetroArtConverter:
         # Initialize face analysis
         self.face_app, self.face_detection_enabled = load_face_analysis()
         
-        # Load Leres Depth detector
-        self.leres_depth, leres_success = load_depth_detector()
-        self.models_loaded['leres_depth'] = leres_success
+        # Skip depth detector - using grayscale conversion instead
+        self.leres_depth = None
+        self.models_loaded['leres_depth'] = False
         
         # Load ControlNets
         controlnet_depth, self.controlnet_instantid, instantid_success = load_controlnets()
@@ -151,37 +151,24 @@ class RetroArtConverter:
         print("============================\n")
     
     def get_depth_map(self, image):
-        """Generate depth map using Leres Depth for better quality"""
-        if self.leres_depth is not None:
-            try:
-                # Ensure RGB mode
-                if image.mode != 'RGB':
-                    image = image.convert('RGB')
-                
-                # Get original dimensions
-                orig_width, orig_height = image.size
-                
-                # Ensure dimensions are multiples of 64 for better processing
-                detect_width = int((orig_width // 64) * 64) or 64
-                detect_height = int((orig_height // 64) * 64) or 64
-                
-                # Resize if needed
-                if detect_width != orig_width or detect_height != orig_height:
-                    detect_image = image.resize((detect_width, detect_height), Image.LANCZOS)
-                    print(f"[DEPTH] Resized for detection: {orig_width}x{orig_height} -> {detect_width}x{detect_height}")
-                else:
-                    detect_image = image
-                
-                # Generate depth map with Leres (better quality than Zoe)
-                with torch.no_grad():
-                    depth_image = self.leres_depth(detect_image)
-                
-                # Resize back to original dimensions
-                if depth_image.size != (orig_width, orig_height):
-                    depth_image = depth_image.resize((orig_width, orig_height), Image.LANCZOS)
-                
-                print(f"[DEPTH] Leres depth map generated: {orig_width}x{orig_height}")
-                return depth_image
+        """Generate depth map using grayscale conversion for reliability"""
+        try:
+            # Ensure RGB mode
+            if image.mode != 'RGB':
+                image = image.convert('RGB')
+            
+            # Convert to grayscale for depth
+            gray = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2GRAY)
+            
+            # Apply some enhancement to make depth more pronounced
+            gray = cv2.equalizeHist(gray)
+            
+            # Convert back to RGB format (ControlNet expects RGB)
+            depth_colored = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)
+            depth_image = Image.fromarray(depth_colored)
+            
+            print(f"[DEPTH] Grayscale depth map generated: {image.size}")
+            return depth_image
                 
             except Exception as e:
                 print(f"[DEPTH] LeresDetector failed ({e}), falling back to grayscale depth")
@@ -466,7 +453,7 @@ class RetroArtConverter:
         resized_image = input_image.resize((int(target_width), int(target_height)), Image.LANCZOS)
         
         # Generate depth map
-        print("Generating Leres depth map...")
+        print("Generating grayscale depth map...")
         depth_image = self.get_depth_map(resized_image)
         if depth_image.size != (target_width, target_height):
             depth_image = depth_image.resize((int(target_width), int(target_height)), Image.LANCZOS)
@@ -547,17 +534,24 @@ class RetroArtConverter:
                 print(f"Face info: bbox={face.bbox}, age={age if age else 'N/A'}, gender={gender_str}")
                 print(f"Face crop size: {face_crop.size}, enhanced: {face_crop_enhanced.size if face_crop_enhanced else 'N/A'}")
         
-        # Set LORA scale
-        if hasattr(self.pipe, 'set_adapters') and self.models_loaded['lora']:
+        # Set LORA scale - use fuse_lora for immediate effect
+        if hasattr(self.pipe, 'fuse_lora') and self.models_loaded['lora']:
             try:
-                # Try retroart first (if loaded with that name), then default_0
-                for adapter_name in ["retroart", "default_0"]:
-                    try:
-                        self.pipe.set_adapters([adapter_name], adapter_weights=[lora_scale])
-                        print(f"[LORA] Set adapter '{adapter_name}' with scale: {lora_scale}")
-                        break
-                    except:
-                        continue
+                self.pipe.fuse_lora(lora_scale=lora_scale)
+                print(f"[LORA] Fused with scale: {lora_scale}")
+            except Exception as e:
+                print(f"[WARNING] LORA fuse failed: {e}")
+                # Try set_adapters as fallback
+                try:
+                    for adapter_name in ["retroart", "default_0"]:
+                        try:
+                            self.pipe.set_adapters([adapter_name], adapter_weights=[lora_scale])
+                            print(f"[LORA] Set adapter '{adapter_name}' with scale: {lora_scale}")
+                            break
+                        except:
+                            continue
+                except Exception as e2:
+                    print(f"[WARNING] LORA set_adapters also failed: {e2}")
                         
             except Exception as e:
                 print(f"[WARNING] LORA set_adapters failed: {e}")