Fix: Add pipeline component mismatch fallback for image model loading in I2V mode

videogen

@@ -4245,7 +4245,54 @@ def main(args):
 
             try:
                 print(f"\n🖼️  Loading image model for I2V: {args.image_model}")
-                img_pipe = ImgCls.from_pretrained(img_model_id_to_load, **img_kwargs)
+                
+                # Initialize flag for pipeline mismatch fallback
+                img_pipeline_loaded_successfully = False
+                
+                try:
+                    img_pipe = ImgCls.from_pretrained(img_model_id_to_load, **img_kwargs)
+                    img_pipeline_loaded_successfully = True
+                except Exception as e:
+                    error_str = str(e)
+                    
+                    # Check if this is a pipeline component mismatch error
+                    is_component_mismatch = "expected" in error_str and "but only" in error_str and "were passed" in error_str
+                    
+                    if is_component_mismatch:
+                        # Try to re-detect the correct pipeline class from model ID pattern
+                        detected_class = None
+                        img_model_id_lower = img_model_id_to_load.lower()
+                        
+                        # Force detection based on model ID patterns
+                        if "flux" in img_model_id_lower:
+                            detected_class = "FluxPipeline"
+                        elif "sdxl" in img_model_id_lower or "stable-diffusion-xl" in img_model_id_lower:
+                            detected_class = "StableDiffusionXLPipeline"
+                        elif "sd3" in img_model_id_lower or "stable-diffusion-3" in img_model_id_lower:
+                            detected_class = "StableDiffusion3Pipeline"
+                        elif "sd15" in img_model_id_lower or "stable-diffusion-1.5" in img_model_id_lower:
+                            detected_class = "StableDiffusionPipeline"
+                        
+                        if detected_class and detected_class != img_info["class"]:
+                            print(f"\n⚠️  Image model pipeline component mismatch detected!")
+                            print(f"   Configured class: {img_info['class']}")
+                            print(f"   Detected class: {detected_class}")
+                            print(f"   Retrying with detected pipeline class: {detected_class}")
+                            
+                            # Get the correct pipeline class
+                            CorrectImgCls = get_pipeline_class(detected_class)
+                            if CorrectImgCls:
+                                try:
+                                    img_pipe = CorrectImgCls.from_pretrained(img_model_id_to_load, **img_kwargs)
+                                    print(f"  ✅ Successfully loaded image model with {detected_class}")
+                                    ImgCls = CorrectImgCls
+                                    img_pipeline_loaded_successfully = True
+                                except Exception as retry_e:
+                                    print(f"  ❌ Retry with {detected_class} also failed: {retry_e}")
+                                    raise e  # Re-raise original error
+                    
+                    if not img_pipeline_loaded_successfully:
+                        raise e  # Re-raise if we couldn't handle it
                 
                 # Apply LoRA if image model is a LoRA adapter
                 if img_is_lora and img_lora_id: