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note_image.py

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+import random
+import os
+import hashlib
+# import logging
+import numpy as np
+import torch
+from nodes import SaveImage
+import folder_paths
+from PIL import Image
+from server import PromptServer
+from aiohttp import web
+
+# Configure logging
+# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
+# logger = logging.getLogger("ImageNote")
+
+class ImageNote(SaveImage):
+    def __init__(self):
+        self.output_dir = folder_paths.get_temp_directory()
+        self.type = "temp"
+        self.prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for _ in range(5))
+        self.compress_level = 1
+        self.note_dir = os.path.join("ComfyUI", "Bjornulf", "imageNote")
+        os.makedirs(self.note_dir, exist_ok=True)
+
+        # Store last image path and hash to prevent unnecessary reloading
+        self.last_image_path = None
+        self.last_image_hash = None
+        self.last_output_images = None
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "optional": {
+                "images": ("IMAGE", ),
+                "image_path": ("STRING", {"default": ""}),
+                "note_text": ("STRING", {"default": "", "multiline": True})
+            },
+            "hidden": {
+                "prompt": "PROMPT",
+                "extra_pnginfo": "EXTRA_PNGINFO"
+            },
+        }
+    
+    FUNCTION = "process_image"
+    OUTPUT_NODE = True
+    CATEGORY = "Bjornulf"
+
+    def compute_md5(self, image):
+        image_bytes = image.tobytes() if isinstance(image, Image.Image) else image
+        return hashlib.md5(image_bytes).hexdigest()
+
+    def process_image(self, images=None, image_path="", note_text="", prompt=None, extra_pnginfo=None):
+        output_images = None
+        output_note_text = ""
+
+        # If images are given, process them
+        if images is not None and len(images) > 0:
+            output_images = images
+            image_np = (images[0].numpy() * 255).astype(np.uint8)
+            image = Image.fromarray(image_np)
+            image_hash = self.compute_md5(image)
+
+            note_path = os.path.join(self.note_dir, f"{image_hash}.txt")
+            if os.path.exists(note_path):
+                with open(note_path, "r", encoding="utf-8") as f:
+                    output_note_text = f.read()
+            elif note_text:
+                with open(note_path, "w", encoding="utf-8") as f:
+                    f.write(note_text)
+                    output_note_text = note_text
+
+        # If image_path is empty, do nothing
+        elif not image_path:
+            # logger.debug("No image path provided, skipping processing.")
+            return None, ""
+
+        # Process image from path only if it has changed
+        elif os.path.isfile(image_path):
+            if image_path == self.last_image_path:
+                # logger.debug("Image path has not changed, skipping reload.")
+                return super().save_images(images=self.last_output_images, prompt=prompt, extra_pnginfo=extra_pnginfo)
+
+            image = Image.open(image_path).convert("RGB")
+            image_hash = self.compute_md5(image)
+
+            if image_hash == self.last_image_hash:
+                # logger.debug("Image content has not changed, skipping reload.")
+                return super().save_images(images=self.last_output_images, prompt=prompt, extra_pnginfo=extra_pnginfo)
+
+            note_path = os.path.join(self.note_dir, f"{image_hash}.txt")
+            if os.path.exists(note_path):
+                with open(note_path, "r", encoding="utf-8") as f:
+                    output_note_text = f.read()
+            elif note_text:
+                with open(note_path, "w", encoding="utf-8") as f:
+                    f.write(note_text)
+                    output_note_text = note_text
+
+            image_np = np.array(image).astype(np.float32) / 255.0
+            output_images = torch.from_numpy(image_np).unsqueeze(0)
+
+            # Update stored values
+            self.last_image_path = image_path
+            self.last_image_hash = image_hash
+            self.last_output_images = output_images
+
+        return super().save_images(images=output_images, prompt=prompt, extra_pnginfo=extra_pnginfo)