Add warning when multiple overlay images are detected

Co-authored-by: jags111 <5968619+jags111@users.noreply.github.com>

.gitignore

@@ -1,10 +1,8 @@
-# Python cache
+# Python
 __pycache__/
 *.py[cod]
 *$py.class
 *.so
-
-# Distribution / packaging
 .Python
 build/
 develop-eggs/
@@ -27,7 +25,7 @@ venv/
 ENV/
 env/
 
-# IDEs
+# IDE
 .vscode/
 .idea/
 *.swp

efficiency_nodes.py

@@ -99,16 +99,6 @@ def encode_prompts(positive_prompt, negative_prompt, token_normalization, weight
     elif return_type == "both":
         return positive_encoded, negative_encoded, clip, refiner_positive_encoded, refiner_negative_encoded, refiner_clip
 
-########################################################################################################################
-# Helper function for VAE error message
-def get_missing_vae_error(ckpt_name):
-    """Generate error message for checkpoints without embedded VAE"""
-    return (
-        f"Checkpoint '{ckpt_name}' does not contain an embedded VAE. "
-        f"This checkpoint (likely an AIO model) requires an external VAE. "
-        f"Please select a VAE file instead of 'Baked VAE'."
-    )
-
 ########################################################################################################################
 # TSC Efficient Loader
 class TSC_EfficientLoader:
@@ -176,9 +166,6 @@ class TSC_EfficientLoader:
                         f"{warning('Efficiency Nodes:')} Baked VAE not found in cache, loading checkpoint to extract VAE...")
                     _, _, vae = load_checkpoint(ckpt_name, my_unique_id, output_vae=True, cache=ckpt_cache,
                                                 cache_overwrite=True)
-                    # Check if VAE extraction was successful
-                    if vae is None:
-                        raise ValueError(get_missing_vae_error(ckpt_name))
         else:
             model, clip, vae = load_checkpoint(ckpt_name, my_unique_id, cache=ckpt_cache, cache_overwrite=True)
             lora_params = None
@@ -208,9 +195,6 @@ class TSC_EfficientLoader:
         # Check for custom VAE
         if vae_name != "Baked VAE":
             vae = load_vae(vae_name, my_unique_id, cache=vae_cache, cache_overwrite=True)
-        elif vae is None:
-            # If "Baked VAE" was selected but checkpoint has no embedded VAE
-            raise ValueError(get_missing_vae_error(ckpt_name))
 
         # Data for XY Plot
         dependencies = (vae_name, ckpt_name, clip, clip_skip, refiner_name, refiner_clip, refiner_clip_skip,
@@ -3973,6 +3957,12 @@ class TSC_ImageOverlay:
             samples = overlay_image.movedim(-1, 1)
             overlay_image = comfy.utils.common_upscale(samples, overlay_image_size[0], overlay_image_size[1], resize_method, False)
             overlay_image = overlay_image.movedim(1, -1)
+        
+        # Handle batch dimension - use first image if overlay_image is a batch
+        if len(overlay_image.shape) == 4:
+            if overlay_image.shape[0] > 1:
+                print(f"{warning('Image Overlay Warning:')} Multiple overlay images detected ({overlay_image.shape[0]}), using only the first image.")
+            overlay_image = overlay_image[0]
             
         overlay_image = tensor2pil(overlay_image)