fix pingpong, new node combine image background + overlay

README.md

@@ -1,4 +1,4 @@
-# 🔗 Comfyui : Bjornulf_custom_nodes v0.5 🔗
+# 🔗 Comfyui : Bjornulf_custom_nodes v0.6 🔗
 
 # Dependencies
 
@@ -12,6 +12,7 @@
 - **v0.4**: Support transparency option with webm format, options encoders. As well as input for audio stream. 
 - **v0.5**: New node : Remove image transparency (alpha) - Fill alpha channel with solid color.
 - **v0.5**: New node : Image to grayscale (black & white) - Convert an image to grayscale.
+- **v0.6**: New node : Combine images (Background + Overlay) - Combine two images into a single image.
 
 # 📝 Nodes descriptions
 
@@ -144,7 +145,7 @@ Combine a sequence of images into a video file.
 Temporary images are stored in the folder `ComfyUI/temp_images_imgs2video/` as well as the wav audio file.
 
 ## 22 - 🔲 Remove image Transparency (alpha)
-![Images to Video](screenshots/remove_alpha.png)
+![Remove Alpha](screenshots/remove_alpha.png)
 
 **Description:**  
 Remove transparency from an image by filling the alpha channel with a solid color. (black, white or greenscreen)  
@@ -152,9 +153,16 @@ Of course it takes in an image with transparency, like from rembg nodes.
 Necessary for some nodes that don't support transparency.  
 
 ## 23 - 🔲 Image to grayscale (black & white)
-![Images to Video](screenshots/grayscale.png)
+![Image to Grayscale](screenshots/grayscale.png)
 
 **Description:**  
 Convert an image to grayscale (black & white)  
 Example : I sometimes use it with Ipadapter to disable color influence.  
 But you can sometimes also want a black and white image... 
+
+## 24 - 🖼+🖼 Combine images (Background + Overlay)
+![Combine Images](screenshots/combine_background_overlay.png)
+
+**Description:**  
+Combine two images into a single image : a background and one (or several) transparent overlay. (allow for video frames.)  
+❗ Warning : For now, `background` is a static image. (I will allow video there later too.)  

__init__.py

@@ -27,6 +27,7 @@ from .resize_image import ResizeImage
 from .loop_my_combos_samplers_schedulers import LoopCombosSamplersSchedulers
 from .remove_transparency import RemoveTransparency
 from .image_to_grayscale import GrayscaleTransform
+from .combine_background_overlay import CombineBackgroundOverlay
 
 # from .CUSTOM_STRING import CustomStringType
 
@@ -36,6 +37,7 @@ NODE_CLASS_MAPPINGS = {
     "Bjornulf_WriteText": WriteText,
     "Bjornulf_RemoveTransparency": RemoveTransparency,
     "Bjornulf_GrayscaleTransform": GrayscaleTransform,
+    "Bjornulf_CombineBackgroundOverlay": CombineBackgroundOverlay,
     # "Bjornulf_WriteImageEnvironment": WriteImageEnvironment,
     # "Bjornulf_WriteImageCharacters": WriteImageCharacters,
     # "Bjornulf_WriteImageCharacter": WriteImageCharacter,
@@ -69,6 +71,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "Bjornulf_ShowText": "👁 Show (Text)",
     "Bjornulf_ShowInt": "👁 Show (Int)",
     "Bjornulf_ShowFloat": "👁 Show (Float)",
+    "Bjornulf_CombineBackgroundOverlay": "🖼+🖼 Combine images (Background+Overlay alpha)",
     "Bjornulf_GrayscaleTransform": "🔲 Image to grayscale (black & white)",
     "Bjornulf_RemoveTransparency": "🔲 Remove image Transparency (alpha)",
     "Bjornulf_ResizeImage": "📏 Resize Image",

combine_background_overlay.py

@@ -0,0 +1,66 @@
+import torch
+import numpy as np
+from PIL import Image
+
+class CombineBackgroundOverlay:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "background": ("IMAGE",),
+                "overlay_alpha": ("IMAGE",),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "combine_background_overlay"
+    CATEGORY = "Bjornulf"
+
+    def combine_background_overlay(self, background, overlay_alpha):
+        # Convert background from torch tensor to numpy array
+        bg = background[0].numpy()
+        bg = (bg * 255).astype(np.uint8)
+        bg_img = Image.fromarray(bg, 'RGB')
+
+        results = []
+
+        for overlay in overlay_alpha:
+            # Convert overlay from torch tensor to numpy array
+            ov = overlay.numpy()
+            ov = (ov * 255).astype(np.uint8)
+
+            # Create PIL Image for overlay
+            if ov.shape[2] == 4:
+                ov_img = Image.fromarray(ov, 'RGBA')
+            else:
+                ov_img = Image.fromarray(ov, 'RGB')
+                ov_img = ov_img.convert('RGBA')
+
+            # Calculate position to center the overlay
+            x = (bg_img.width - ov_img.width) // 2
+            y = (bg_img.height - ov_img.height) // 2
+
+            # Create a new image for this overlay
+            result = Image.new('RGBA', bg_img.size, (0, 0, 0, 0))
+
+            # Paste the background
+            result.paste(bg_img, (0, 0))
+
+            # Paste the overlay in the center
+            result.paste(ov_img, (x, y), ov_img)
+
+            # Convert back to numpy array and then to torch tensor
+            result_np = np.array(result)
+            
+            # If the result is RGBA, convert to RGB
+            if result_np.shape[2] == 4:
+                result_np = result_np[:,:,:3]
+
+            result_tensor = torch.from_numpy(result_np).float() / 255.0
+
+            results.append(result_tensor)
+
+        # Stack all results into a single tensor
+        final_result = torch.stack(results)
+
+        return (final_result,)

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):
+        # Create a clean folder to store the images
-            reversed_images = torch.flip(images, [0])
+        temp_dir = "temp_pingpong"
-            combined_images = torch.cat((images, reversed_images[1:]), dim=0)
+        if os.path.exists(temp_dir):
-        else:
+            shutil.rmtree(temp_dir)
-            reversed_images = images[::-1]
+        os.makedirs(temp_dir)
-            combined_images = images + reversed_images[1:]
+
-        return (combined_images,)
+        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,)