Eric Hiss
513b975fb8
- Add DeepSeek Prompt Rewriter node for fast API-based rewriting - Add Load Image with Prompt node for metadata extraction - Add config.json.example with API backend templates - Add flux2/schema.yaml - Update .gitignore to exclude dev/ and config.json (contains API keys)
90 lines
3.2 KiB
Python
90 lines
3.2 KiB
Python
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import os
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import json
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from PIL import Image, ImageOps
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import torch
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import numpy as np
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try:
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import folder_paths
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except ImportError:
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folder_paths = None
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class EricLoadImageWithPrompt:
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"""
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Loads an image and extracts generation metadata (prompt) if available.
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Supports standard ComfyUI image loading + metadata extraction.
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"""
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@classmethod
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def INPUT_TYPES(s):
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input_dir = folder_paths.get_input_directory()
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
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return {
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"required": {
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"image": (sorted(files), {"image_upload": True})
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}
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}
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CATEGORY = "Eric Prompt Enhancers"
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RETURN_TYPES = ("IMAGE", "MASK", "STRING")
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RETURN_NAMES = ("IMAGE", "MASK", "PROMPT_TEXT")
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FUNCTION = "load_image"
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def load_image(self, image):
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image_path = folder_paths.get_annotated_filepath(image)
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i = Image.open(image_path)
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i = ImageOps.exif_transpose(i)
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image = i.convert("RGB")
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# Process image for ComfyUI (Tensor)
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image = np.array(image).astype(np.float32) / 255.0
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image = torch.from_numpy(image)[None,]
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# Create mask
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if 'A' in i.getbands():
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mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
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mask = 1. - torch.from_numpy(mask)
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else:
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mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
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# Extract Metadata
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prompt_text = ""
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# 1. Try standard PNG info (parameters/Comment)
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# A1111 stores generation info in 'parameters'
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if i.info:
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if 'parameters' in i.info:
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prompt_text = i.info['parameters']
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elif 'Comment' in i.info:
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# Some software uses Comment
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try:
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# Try to parse JSON if it looks like it
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comment = i.info['Comment']
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if comment.strip().startswith('{'):
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data = json.loads(comment)
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prompt_text = data.get('prompt', comment)
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else:
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prompt_text = comment
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except:
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prompt_text = i.info['Comment']
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# 2. Try ComfyUI workflow metadata (often in 'workflow' or 'prompt')
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# This is complex because it's the whole graph. We try to find a primitive string or positive prompt.
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# For now, we'll stick to the text-based 'parameters' which is the standard for sharing prompts.
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# Clean up A1111 'parameters' block to get just the positive prompt
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# Usually it's: "Positive Prompt\nNegative Prompt: ...\nSteps: ..."
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if prompt_text and "Negative prompt:" in prompt_text:
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prompt_text = prompt_text.split("Negative prompt:")[0].strip()
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elif prompt_text and "Steps:" in prompt_text:
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prompt_text = prompt_text.split("Steps:")[0].strip()
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return (image, mask, prompt_text)
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@classmethod
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def IS_CHANGED(s, image):
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image_path = folder_paths.get_annotated_filepath(image)
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m = os.path.getmtime(image_path)
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return m
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