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import json
import re
from PIL import Image
from PIL.PngImagePlugin import PngInfo
import logging
logger = logging.getLogger(__name__)
def extract_png_metadata(image_path: str) -> dict:
"""
Extract metadata from PNG files generated by A1111 or ComfyUI
Args:
image_path: Path to the PNG image file
Returns:
Dictionary containing extracted metadata
"""
try:
with Image.open(image_path) as img:
metadata = {}
# Check for A1111 metadata
a1111_data = extract_a1111_metadata(img)
if a1111_data:
metadata.update(a1111_data)
metadata['source'] = 'automatic1111'
# Check for ComfyUI metadata
comfyui_data = extract_comfyui_metadata(img)
if comfyui_data:
metadata.update(comfyui_data)
metadata['source'] = 'comfyui'
# Check for other common metadata fields
other_data = extract_other_metadata(img)
if other_data:
metadata.update(other_data)
return metadata if metadata else None
except Exception as e:
logger.error(f"Error extracting metadata from {image_path}: {str(e)}")
return None
def extract_a1111_metadata(img: Image.Image) -> dict:
"""Extract Automatic1111 metadata from PNG text fields"""
try:
metadata = {}
# A1111 stores metadata in the 'parameters' text field
if hasattr(img, 'text') and 'parameters' in img.text:
parameters_text = img.text['parameters']
metadata.update(parse_a1111_parameters(parameters_text))
return metadata
except Exception as e:
logger.error(f"Error extracting A1111 metadata: {str(e)}")
return {}
def parse_a1111_parameters(parameters_text: str) -> dict:
"""Parse A1111 parameters text into structured data"""
try:
metadata = {}
# Split the parameters text into lines
lines = parameters_text.strip().split('\n')
# The first line is usually the prompt
if lines:
metadata['prompt'] = lines[0].strip()
# Look for negative prompt
negative_prompt_match = re.search(r'Negative prompt:\s*(.+?)(?:\n|$)', parameters_text, re.DOTALL)
if negative_prompt_match:
metadata['negative_prompt'] = negative_prompt_match.group(1).strip()
# Extract other parameters using regex
param_patterns = {
'steps': r'Steps:\s*(\d+)',
'sampler': r'Sampler:\s*([^,\n]+)',
'cfg_scale': r'CFG scale:\s*([\d.]+)',
'seed': r'Seed:\s*(\d+)',
'size': r'Size:\s*(\d+x\d+)',
'model_hash': r'Model hash:\s*([a-fA-F0-9]+)',
'model': r'Model:\s*([^,\n]+)',
'denoising_strength': r'Denoising strength:\s*([\d.]+)',
'clip_skip': r'Clip skip:\s*(\d+)',
'ensd': r'ENSD:\s*(\d+)'
}
for param_name, pattern in param_patterns.items():
match = re.search(pattern, parameters_text)
if match:
value = match.group(1).strip()
# Convert numeric values
if param_name in ['steps', 'seed', 'clip_skip', 'ensd']:
metadata[param_name] = int(value)
elif param_name in ['cfg_scale', 'denoising_strength']:
metadata[param_name] = float(value)
else:
metadata[param_name] = value
# Parse size into width and height
if 'size' in metadata:
size_match = re.match(r'(\d+)x(\d+)', metadata['size'])
if size_match:
metadata['width'] = int(size_match.group(1))
metadata['height'] = int(size_match.group(2))
return metadata
except Exception as e:
logger.error(f"Error parsing A1111 parameters: {str(e)}")
return {}
def extract_comfyui_metadata(img: Image.Image) -> dict:
"""Extract ComfyUI metadata from PNG text fields"""
try:
metadata = {}
# ComfyUI stores metadata in 'workflow' and 'prompt' text fields
if hasattr(img, 'text'):
# Check for workflow data
if 'workflow' in img.text:
try:
workflow_data = json.loads(img.text['workflow'])
metadata.update(parse_comfyui_workflow(workflow_data))
except json.JSONDecodeError:
logger.warning("Could not parse ComfyUI workflow JSON")
# Check for prompt data
if 'prompt' in img.text:
try:
prompt_data = json.loads(img.text['prompt'])
metadata.update(parse_comfyui_prompt(prompt_data))
except json.JSONDecodeError:
logger.warning("Could not parse ComfyUI prompt JSON")
return metadata
except Exception as e:
logger.error(f"Error extracting ComfyUI metadata: {str(e)}")
return {}
def parse_comfyui_workflow(workflow_data: dict) -> dict:
"""Parse ComfyUI workflow data"""
try:
metadata = {}
# Extract nodes from workflow
if 'nodes' in workflow_data:
nodes = workflow_data['nodes']
# Look for common node types
for node in nodes:
if isinstance(node, dict):
node_type = node.get('type', '')
# Extract prompt from text nodes
if 'text' in node_type.lower() or 'prompt' in node_type.lower():
if 'widgets_values' in node and node['widgets_values']:
text_value = node['widgets_values'][0]
if isinstance(text_value, str) and len(text_value) > 10:
if 'prompt' not in metadata:
metadata['prompt'] = text_value
# Extract sampler settings
elif 'sampler' in node_type.lower():
if 'widgets_values' in node:
values = node['widgets_values']
if len(values) >= 3:
metadata['steps'] = values[0] if isinstance(values[0], int) else None
metadata['cfg_scale'] = values[1] if isinstance(values[1], (int, float)) else None
metadata['sampler'] = values[2] if isinstance(values[2], str) else None
return metadata
except Exception as e:
logger.error(f"Error parsing ComfyUI workflow: {str(e)}")
return {}
def parse_comfyui_prompt(prompt_data: dict) -> dict:
"""Parse ComfyUI prompt data"""
try:
metadata = {}
# ComfyUI prompt data is usually a nested structure
# Extract common parameters from the prompt structure
for node_id, node_data in prompt_data.items():
if isinstance(node_data, dict) and 'inputs' in node_data:
inputs = node_data['inputs']
# Look for text inputs (prompts)
for key, value in inputs.items():
if isinstance(value, str) and len(value) > 10:
if 'text' in key.lower() or 'prompt' in key.lower():
if 'prompt' not in metadata:
metadata['prompt'] = value
# Look for numeric parameters
if 'steps' in inputs:
metadata['steps'] = inputs['steps']
if 'cfg' in inputs:
metadata['cfg_scale'] = inputs['cfg']
if 'seed' in inputs:
metadata['seed'] = inputs['seed']
if 'denoise' in inputs:
metadata['denoising_strength'] = inputs['denoise']
return metadata
except Exception as e:
logger.error(f"Error parsing ComfyUI prompt: {str(e)}")
return {}
def extract_other_metadata(img: Image.Image) -> dict:
"""Extract other common metadata fields"""
try:
metadata = {}
# Check standard EXIF data
if hasattr(img, '_getexif') and img._getexif():
exif_data = img._getexif()
# Extract relevant EXIF fields
exif_fields = {
'software': 0x0131, # Software tag
'artist': 0x013B, # Artist tag
'copyright': 0x8298 # Copyright tag
}
for field_name, tag_id in exif_fields.items():
if tag_id in exif_data:
metadata[field_name] = exif_data[tag_id]
# Check for other text fields that might contain prompts
if hasattr(img, 'text'):
text_fields = ['description', 'comment', 'title', 'subject']
for field in text_fields:
if field in img.text:
value = img.text[field].strip()
if len(value) > 10 and 'prompt' not in metadata:
metadata['prompt'] = value
return metadata
except Exception as e:
logger.error(f"Error extracting other metadata: {str(e)}")
return {}
def clean_prompt_text(prompt: str) -> str:
"""Clean and normalize prompt text"""
try:
if not prompt:
return ""
# Remove extra whitespace
prompt = re.sub(r'\s+', ' ', prompt.strip())
# Remove common prefixes/suffixes
prefixes_to_remove = [
'prompt:', 'positive prompt:', 'text prompt:',
'description:', 'caption:'
]
for prefix in prefixes_to_remove:
if prompt.lower().startswith(prefix):
prompt = prompt[len(prefix):].strip()
return prompt
except Exception:
return prompt if prompt else ""
def get_generation_parameters(metadata: dict) -> dict:
"""Extract key generation parameters for display"""
try:
params = {}
# Essential parameters
if 'prompt' in metadata:
params['prompt'] = clean_prompt_text(metadata['prompt'])
if 'negative_prompt' in metadata:
params['negative_prompt'] = clean_prompt_text(metadata['negative_prompt'])
# Technical parameters
technical_params = ['steps', 'cfg_scale', 'sampler', 'seed', 'model', 'width', 'height']
for param in technical_params:
if param in metadata:
params[param] = metadata[param]
# Source information
if 'source' in metadata:
params['source'] = metadata['source']
return params
except Exception as e:
logger.error(f"Error extracting generation parameters: {str(e)}")
return {}
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