cleanup: remove temporary debug files
This commit is contained in:
Vito Sansevero
@@ -1,213 +0,0 @@
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#!/usr/bin/env python3
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"""
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Debug script to extract and analyze PNG metadata from the test image
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to understand what should be displayed in the gallery views.
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"""
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import json
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from PIL import Image
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from PIL.PngImagePlugin import PngInfo
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def extract_png_metadata(image_path):
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"""Extract PNG metadata chunks from an image file."""
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try:
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with Image.open(image_path) as img:
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metadata = {}
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# Extract text chunks
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if hasattr(img, 'text'):
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for key, value in img.text.items():
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metadata[key] = value
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print(f"Found text chunk: {key} = {value[:100]}{'...' if len(value) > 100 else ''}")
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# Try to extract PNG info
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if hasattr(img, 'info'):
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print(f"\nImage info keys: {list(img.info.keys())}")
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for key, value in img.info.items():
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if isinstance(value, str):
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print(f"Info {key}: {value[:100]}{'...' if len(value) > 100 else ''}")
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return metadata
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except Exception as e:
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print(f"Error reading PNG metadata: {e}")
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return {}
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def parse_comfyui_data(metadata):
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"""Parse ComfyUI workflow and prompt data from PNG metadata."""
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workflow_data = None
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prompt_data = None
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# Look for workflow data
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workflow_fields = ['workflow', 'Workflow', 'comfy', 'ComfyUI']
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for field in workflow_fields:
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if field in metadata:
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try:
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workflow_data = json.loads(metadata[field])
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print(f"\nFound workflow data in field '{field}'")
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if isinstance(workflow_data, dict) and 'nodes' in workflow_data:
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print(f"Workflow has {len(workflow_data['nodes'])} nodes")
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break
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except json.JSONDecodeError as e:
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print(f"Failed to parse workflow field '{field}': {e}")
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# Look for prompt data
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prompt_fields = ['prompt', 'Prompt', 'parameters', 'Parameters']
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for field in prompt_fields:
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if field in metadata:
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try:
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# Clean up NaN values that might break JSON parsing
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cleaned_json = metadata[field]
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cleaned_json = cleaned_json.replace(': NaN', ': null')
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cleaned_json = cleaned_json.replace(':NaN', ':null')
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cleaned_json = cleaned_json.replace('NaN', 'null')
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prompt_data = json.loads(cleaned_json)
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print(f"\nFound prompt data in field '{field}'")
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if isinstance(prompt_data, dict):
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print(f"Prompt data has {len(prompt_data)} nodes")
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break
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except json.JSONDecodeError as e:
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print(f"Failed to parse prompt field '{field}': {e}")
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return workflow_data, prompt_data
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def extract_generation_params(workflow_data, prompt_data):
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"""Extract generation parameters from ComfyUI data."""
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params = {
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'checkpoint': 'Unknown',
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'positive_prompt': 'No prompt found',
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'negative_prompt': 'No negative prompt found',
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'steps': 'Unknown',
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'cfg_scale': 'Unknown',
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'sampler': 'Unknown',
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'seed': 'Unknown'
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}
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# Parse prompt data first (more reliable)
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if prompt_data:
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print("\nAnalyzing prompt data...")
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for node_id, node in prompt_data.items():
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node_type = node.get('class_type', '')
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inputs = node.get('inputs', {})
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print(f" Node {node_id}: {node_type}")
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if inputs:
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print(f" Inputs: {list(inputs.keys())}")
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if node_type == 'CheckpointLoaderSimple' and 'ckpt_name' in inputs:
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params['checkpoint'] = inputs['ckpt_name']
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print(f" Found checkpoint: {params['checkpoint']}")
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elif node_type == 'PromptManager' and 'text' in inputs:
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params['positive_prompt'] = inputs['text']
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print(f" Found PromptManager text: {params['positive_prompt'][:100]}...")
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elif node_type == 'CLIPTextEncode' and 'text' in inputs:
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text = inputs['text'].lower()
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if any(neg_word in text for neg_word in ['bad anatomy', 'unfinished', 'censored', 'negative', 'embedding:']):
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params['negative_prompt'] = inputs['text']
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print(f" Found negative prompt: {params['negative_prompt'][:100]}...")
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elif params['positive_prompt'] == 'No prompt found':
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params['positive_prompt'] = inputs['text']
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print(f" Found positive prompt: {params['positive_prompt'][:100]}...")
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elif 'sampler' in node_type.lower() or node_type in ['KSampler', 'SamplerCustomAdvanced', 'DetailDaemonSamplerNode']:
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if 'seed' in inputs:
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params['seed'] = inputs['seed']
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if 'steps' in inputs:
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params['steps'] = inputs['steps']
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if 'cfg' in inputs:
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params['cfg_scale'] = inputs['cfg']
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if 'sampler_name' in inputs:
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params['sampler'] = inputs['sampler_name']
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if 'scheduler' in inputs:
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params['scheduler'] = inputs['scheduler']
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print(f" Found {node_type}: seed={inputs.get('seed', 'N/A')}, steps={inputs.get('steps', 'N/A')}, cfg={inputs.get('cfg', 'N/A')}, sampler={inputs.get('sampler_name', 'N/A')}")
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# Also check for BasicScheduler which might have steps
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elif node_type == 'BasicScheduler' and 'steps' in inputs:
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if params['steps'] == 'Unknown':
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params['steps'] = inputs['steps']
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print(f" Found BasicScheduler with steps: {params['steps']}")
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# Check for CFG values
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elif node_type == 'CFGGuider' and 'cfg' in inputs:
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if params['cfg_scale'] == 'Unknown':
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params['cfg_scale'] = inputs['cfg']
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print(f" Found CFGGuider with cfg: {params['cfg_scale']}")
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# Check for seed in various nodes
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elif 'seed' in inputs:
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if params['seed'] == 'Unknown':
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params['seed'] = inputs['seed']
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print(f" Found {node_type} with seed: {params['seed']}")
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elif 'noise_seed' in inputs:
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if params['seed'] == 'Unknown':
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params['seed'] = inputs['noise_seed']
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print(f" Found {node_type} with noise_seed: {params['seed']}")
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# Check for noise/seed generators
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elif node_type in ['RandomNoise', 'EmptyLatentImage'] and 'seed' in inputs:
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if params['seed'] == 'Unknown':
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params['seed'] = inputs['seed']
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print(f" Found {node_type} with seed: {params['seed']}")
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# Fallback to workflow data if needed
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if workflow_data and workflow_data.get('nodes'):
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print("\nAnalyzing workflow data...")
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for node in workflow_data['nodes']:
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node_type = node.get('type', '')
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widgets = node.get('widgets_values', [])
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if node_type == 'CheckpointLoaderSimple' and widgets:
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if params['checkpoint'] == 'Unknown':
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params['checkpoint'] = widgets[0]
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print(f" Found checkpoint in workflow: {params['checkpoint']}")
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elif node_type == 'PromptManager' and widgets:
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if params['positive_prompt'] == 'No prompt found':
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params['positive_prompt'] = widgets[0]
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print(f" Found PromptManager in workflow: {params['positive_prompt'][:100]}...")
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elif node_type == 'KSampler' and len(widgets) >= 4:
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if params['seed'] == 'Unknown':
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params['seed'] = widgets[0]
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params['steps'] = widgets[1]
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params['cfg_scale'] = widgets[2]
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params['sampler'] = widgets[3]
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print(f" Found KSampler in workflow: seed={params['seed']}, steps={params['steps']}")
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return params
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def main():
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print("=== PNG Metadata Debug Tool ===\n")
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image_path = "test_metadata_file.png"
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print(f"Analyzing: {image_path}")
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# Extract raw metadata
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metadata = extract_png_metadata(image_path)
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print(f"\nFound {len(metadata)} metadata fields:")
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for key in metadata.keys():
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print(f" - {key}")
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# Parse ComfyUI data
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workflow_data, prompt_data = parse_comfyui_data(metadata)
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# Extract generation parameters
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params = extract_generation_params(workflow_data, prompt_data)
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print("\n=== EXTRACTED PARAMETERS ===")
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for key, value in params.items():
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print(f"{key}: {value}")
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print("\n=== RAW METADATA FIELDS ===")
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for key, value in metadata.items():
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if len(value) < 200:
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print(f"{key}: {value}")
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else:
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print(f"{key}: {value[:200]}... (truncated)")
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if __name__ == "__main__":
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main()
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@@ -1,253 +0,0 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Metadata Parsing Test</title>
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<style>
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body { font-family: Arial, sans-serif; margin: 20px; background: #1a1a1a; color: #fff; }
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.result { background: #2a2a2a; padding: 20px; margin: 10px 0; border-radius: 8px; }
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.error { background: #3a1a1a; border: 1px solid #ff6b6b; }
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.success { background: #1a3a1a; border: 1px solid #6bcf7f; }
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input[type="file"] { margin: 20px 0; padding: 10px; background: #3a3a3a; color: #fff; border: none; border-radius: 4px; }
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pre { white-space: pre-wrap; word-wrap: break-word; }
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</style>
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</head>
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<body>
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<h1>PNG Metadata Parsing Test</h1>
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<p>Select the test_metadata_file.png to verify metadata extraction works correctly.</p>
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<input type="file" id="fileInput" accept=".png" />
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<div id="results"></div>
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<script>
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// Copy the updated parsing functions from metadata.html
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async function parsePNGMetadata(arrayBuffer) {
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const dataView = new DataView(arrayBuffer);
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let offset = 8; // Skip PNG signature
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const metadata = {};
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while (offset < arrayBuffer.byteLength - 8) {
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const length = dataView.getUint32(offset);
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const type = new TextDecoder().decode(arrayBuffer.slice(offset + 4, offset + 8));
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if (type === 'tEXt' || type === 'iTXt' || type === 'zTXt') {
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const chunkData = arrayBuffer.slice(offset + 8, offset + 8 + length);
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let text;
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if (type === 'tEXt') {
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text = new TextDecoder().decode(chunkData);
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} else if (type === 'iTXt') {
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const textData = new TextDecoder().decode(chunkData);
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const parts = textData.split('\0');
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if (parts.length >= 5) {
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metadata[parts[0]] = parts[4];
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}
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text = textData;
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} else if (type === 'zTXt') {
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text = new TextDecoder().decode(chunkData);
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}
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const nullIndex = text.indexOf('\0');
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if (nullIndex !== -1) {
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const key = text.substring(0, nullIndex);
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const value = text.substring(nullIndex + 1);
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metadata[key] = value;
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}
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}
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offset += 8 + length + 4;
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}
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return metadata;
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}
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function extractComfyUIData(metadata) {
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let workflowData = null;
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let promptData = null;
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const workflowFields = ['workflow', 'Workflow', 'comfy', 'ComfyUI'];
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const promptFields = ['prompt', 'Prompt', 'parameters', 'Parameters'];
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for (const field of workflowFields) {
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if (metadata[field]) {
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try {
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let cleanedJson = metadata[field];
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cleanedJson = cleanedJson.replace(/:\s*NaN\b/g, ': null');
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cleanedJson = cleanedJson.replace(/\bNaN\b/g, 'null');
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workflowData = JSON.parse(cleanedJson);
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break;
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} catch (e) {
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console.log('Failed to parse workflow field:', field);
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}
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}
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}
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for (const field of promptFields) {
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if (metadata[field]) {
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try {
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let cleanedJson = metadata[field];
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cleanedJson = cleanedJson.replace(/:\s*NaN\b/g, ': null');
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cleanedJson = cleanedJson.replace(/\bNaN\b/g, 'null');
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promptData = JSON.parse(cleanedJson);
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break;
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} catch (e) {
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console.log('Failed to parse prompt field:', field);
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}
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}
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}
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return { workflow: workflowData, prompt: promptData };
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}
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function parseWorkflowData(comfyData) {
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let checkpoint = 'Unknown';
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let positivePrompt = 'No prompt found';
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let negativePrompt = 'No negative prompt found';
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let steps = 'Unknown';
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let cfgScale = 'Unknown';
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let sampler = 'Unknown';
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let seed = 'Unknown';
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// Parse prompt data first (more reliable for actual generation parameters)
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if (comfyData.prompt) {
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console.log('Parsing prompt data...');
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const promptNodes = comfyData.prompt;
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for (const nodeId in promptNodes) {
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const node = promptNodes[nodeId];
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console.log(`Node ${nodeId}: ${node.class_type}`);
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// Checkpoint
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if (node.class_type === 'CheckpointLoaderSimple' && node.inputs) {
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checkpoint = node.inputs.ckpt_name || checkpoint;
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}
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// Prompts
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if (node.class_type === 'PromptManager' && node.inputs && node.inputs.text) {
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positivePrompt = node.inputs.text;
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}
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if (node.class_type === 'CLIPTextEncode' && node.inputs && node.inputs.text) {
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const text = node.inputs.text.toLowerCase();
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if (text.includes('bad anatomy') || text.includes('unfinished') ||
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text.includes('censored') || text.includes('weird anatomy') ||
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text.includes('negative') || text.includes('embedding:')) {
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negativePrompt = node.inputs.text;
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} else if (positivePrompt === 'No prompt found') {
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positivePrompt = node.inputs.text;
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}
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}
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// Sampling parameters - check multiple sampler types
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if ((node.class_type === 'KSampler' ||
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node.class_type === 'KSamplerAdvanced' ||
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node.class_type === 'SamplerCustom' ||
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node.class_type === 'SamplerCustomAdvanced') && node.inputs) {
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seed = node.inputs.seed || seed;
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steps = node.inputs.steps || steps;
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cfgScale = node.inputs.cfg || cfgScale;
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sampler = node.inputs.sampler_name || sampler;
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}
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// New ComfyUI node types for modern workflows
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if (node.class_type === 'CFGGuider' && node.inputs && node.inputs.cfg) {
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cfgScale = node.inputs.cfg;
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}
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if (node.class_type === 'BasicScheduler' && node.inputs && node.inputs.steps) {
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steps = node.inputs.steps;
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}
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if (node.class_type === 'KSamplerSelect' && node.inputs && node.inputs.sampler_name) {
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sampler = node.inputs.sampler_name;
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}
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if ((node.class_type === 'RandomNoise' || node.class_type === 'SeedHistory') && node.inputs) {
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if (node.inputs.noise_seed) {
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seed = Array.isArray(node.inputs.noise_seed) ? node.inputs.noise_seed[0] : node.inputs.noise_seed;
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} else if (node.inputs.seed) {
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seed = node.inputs.seed;
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}
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}
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}
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}
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return {
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checkpoint,
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positivePrompt,
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negativePrompt,
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steps,
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cfgScale,
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sampler,
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seed
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};
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}
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document.getElementById('fileInput').addEventListener('change', async (event) => {
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const file = event.target.files[0];
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if (!file) return;
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const resultsDiv = document.getElementById('results');
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resultsDiv.innerHTML = '<div class="result">Processing...</div>';
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try {
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const arrayBuffer = await file.arrayBuffer();
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const metadata = await parsePNGMetadata(arrayBuffer);
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const comfyData = extractComfyUIData(metadata);
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const params = parseWorkflowData(comfyData);
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const expectedParams = {
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checkpoint: 'illustrious/realism/Realism_Illustrious_BSY_PATREON_FP16_V4.5_C27.safetensors',
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steps: 35,
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cfgScale: 4.0,
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sampler: 'euler_ancestral',
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positivePrompt: 'An amateur candid photo of kiko9natsumi, looking at the viewer.',
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negativePrompt: 'embedding:'
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};
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let html = '<div class="result success"><h2>✅ Metadata Extraction Test Results</h2>';
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for (const [key, value] of Object.entries(params)) {
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const expected = expectedParams[key];
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let status = '✅';
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let statusText = 'OK';
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if (expected && (key === 'negativePrompt' ? !String(value).includes(String(expected)) : value !== expected)) {
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status = '❌';
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statusText = `Expected: ${expected}`;
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} else if (value === 'Unknown' || value === 'No prompt found') {
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status = '⚠️';
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statusText = 'Not found';
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}
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html += `
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<div style="margin: 10px 0; padding: 10px; background: rgba(255,255,255,0.1); border-radius: 4px;">
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<strong>${key}:</strong> ${status} ${String(value).substring(0, 100)}${String(value).length > 100 ? '...' : ''}
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<br><small style="color: #aaa;">${statusText}</small>
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</div>
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`;
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}
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html += '</div>';
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html += `
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<div class="result">
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<h3>Raw Metadata Fields Found:</h3>
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<pre>${Object.keys(metadata).join(', ')}</pre>
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</div>
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`;
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|
||||
resultsDiv.innerHTML = html;
|
||||
|
||||
} catch (error) {
|
||||
resultsDiv.innerHTML = `<div class="result error"><h2>❌ Error</h2><p>${error.message}</p></div>`;
|
||||
console.error('Error processing image:', error);
|
||||
}
|
||||
});
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
Reference in New Issue
Block a user