Add some more nodes

resize_image.py

@@ -0,0 +1,43 @@
+import numpy as np
+import torch
+from PIL import Image
+
+class ResizeImage:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE", {}),
+                "width": ("INT", {"default": 256}),
+                "height": ("INT", {"default": 256}),
+            }
+        }
+
+    FUNCTION = "resize_image"
+    RETURN_TYPES = ("IMAGE",)
+    OUTPUT_NODE = True
+    CATEGORY = "Bjornulf"
+
+    def resize_image(self, image, width=256, height=256):
+        # Convert the image from ComfyUI format to PIL Image
+        i = 255. * image.cpu().numpy()
+
+        # Reshape the image if it's not in the expected format, remove any leading dimensions of size 1
+        if i.ndim > 3:
+            i = np.squeeze(i)
+        # Ensure the image is 3D (height, width, channels)
+        if i.ndim == 2:
+            i = i[:, :, np.newaxis]  # Add a channel dimension if it's missing
+
+        img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+
+        # Resize the image
+        img_resized = img.resize((width, height), Image.LANCZOS)
+
+        # Convert the PIL image back to numpy array
+        img_resized_np = np.array(img_resized).astype(np.float32) / 255.0
+
+        # Assuming ComfyUI format needs the image back in tensor format, convert it back
+        img_resized_tensor = torch.tensor(img_resized_np)
+
+        return (img_resized_tensor, )