fix pingpong, new node combine image background + overlay

video_pingpong.py

@@ -1,4 +1,8 @@
 import torch
+import os
+import shutil
+from PIL import Image
+import numpy as np
 
 class VideoPingPong:
     @classmethod
@@ -14,10 +18,55 @@ class VideoPingPong:
     CATEGORY = "Bjornulf"
 
     def pingpong_images(self, images):
-        if isinstance(images, torch.Tensor):
-            reversed_images = torch.flip(images, [0])
-            combined_images = torch.cat((images, reversed_images[1:]), dim=0)
-        else:
-            reversed_images = images[::-1]
-            combined_images = images + reversed_images[1:]
-        return (combined_images,)
+        # Create a clean folder to store the images
+        temp_dir = "temp_pingpong"
+        if os.path.exists(temp_dir):
+            shutil.rmtree(temp_dir)
+        os.makedirs(temp_dir)
+
+        try:
+            # Save each image in the temporary directory
+            num_images = images.shape[0]
+            for i in range(num_images):
+                img_tensor = images[i]
+                img_pil = Image.fromarray((img_tensor.cpu().numpy() * 255).astype('uint8'))
+                img_path = os.path.join(temp_dir, f"image_{i:04d}.png")
+                img_pil.save(img_path)
+
+            # Create the pingpong sequence
+            pingpong_list = list(range(num_images)) + list(range(num_images - 2, 0, -1))
+
+            # Process images in batches
+            batch_size = 10
+            pingpong_tensors = []
+            
+            for i in range(0, len(pingpong_list), batch_size):
+                batch = pingpong_list[i:i+batch_size]
+                batch_tensors = []
+                
+                for j in batch:
+                    img_path = os.path.join(temp_dir, f"image_{j:04d}.png")
+                    img_pil = Image.open(img_path)
+                    img_np = np.array(img_pil).astype(np.float32) / 255.0
+                    img_tensor = torch.from_numpy(img_np)
+                    batch_tensors.append(img_tensor)
+                    
+                    # Close the image to free up memory
+                    img_pil.close()
+                
+                # Stack the batch tensors
+                batch_tensor = torch.stack(batch_tensors)
+                pingpong_tensors.append(batch_tensor)
+                
+                # Clear unnecessary variables
+                del batch_tensors
+                torch.cuda.empty_cache()
+
+            # Concatenate all batches
+            pingpong_tensor = torch.cat(pingpong_tensors, dim=0)
+
+        finally:
+            # Clean up the temporary directory
+            shutil.rmtree(temp_dir)
+
+        return (pingpong_tensor,)