Fix Priority 1 & 4: Enhanced prompt detection and restored LoRA extraction
- Priority 4: Added missing _extract_loras_from_text method to MetaManLoadImage class - Priority 1: Enhanced _score_as_positive_prompt with better detection for processed fields (populated_text, formatted, etc.) - Priority 2: Improved _parse_parameter_line to handle complex prompts with nested parentheses and brackets - Increased scoring weight for LoRA presence and processed text fields - Better handling of ImpactWildcardEncode and custom node outputs
This commit is contained in:
PXL8D
+115
-29
@@ -143,47 +143,99 @@ class MetaManLoadAndConvert:
|
||||
return metadata
|
||||
|
||||
def _parse_parameter_line(self, line: str) -> dict:
|
||||
"""Parse A1111 parameter line"""
|
||||
"""Parse A1111 parameter line with improved handling of complex prompts"""
|
||||
params = {}
|
||||
|
||||
# Split by comma, but be careful of commas in quoted values
|
||||
# Enhanced splitting that handles quotes, parentheses, and brackets
|
||||
parts = []
|
||||
current = ""
|
||||
in_quotes = False
|
||||
paren_depth = 0
|
||||
bracket_depth = 0
|
||||
|
||||
for char in line:
|
||||
if char == '"' and (not current or current[-1] != '\\'):
|
||||
in_quotes = not in_quotes
|
||||
elif char == ',' and not in_quotes:
|
||||
parts.append(current.strip())
|
||||
elif char == '(' and not in_quotes:
|
||||
paren_depth += 1
|
||||
elif char == ')' and not in_quotes:
|
||||
paren_depth -= 1
|
||||
elif char == '[' and not in_quotes:
|
||||
bracket_depth += 1
|
||||
elif char == ']' and not in_quotes:
|
||||
bracket_depth -= 1
|
||||
elif char == ',' and not in_quotes and paren_depth == 0 and bracket_depth == 0:
|
||||
# Only split on commas that are not inside quotes, parentheses, or brackets
|
||||
part = current.strip()
|
||||
if part: # Only add non-empty parts
|
||||
parts.append(part)
|
||||
current = ""
|
||||
continue
|
||||
current += char
|
||||
|
||||
# Don't forget the last part
|
||||
if current.strip():
|
||||
parts.append(current.strip())
|
||||
|
||||
print(f"MetaMan Debug: Parsed {len(parts)} parameter parts from line")
|
||||
|
||||
# Parse each parameter
|
||||
for part in parts:
|
||||
if ':' in part:
|
||||
key, value = part.split(':', 1)
|
||||
key = key.strip().lower().replace(' ', '_')
|
||||
value = value.strip()
|
||||
part = part.strip()
|
||||
if not part:
|
||||
continue
|
||||
|
||||
# Convert known numeric values
|
||||
if key in ['steps', 'width', 'height', 'seed', 'clip_skip']:
|
||||
try:
|
||||
params[key] = int(value)
|
||||
except:
|
||||
params[key] = value
|
||||
elif key in ['cfg_scale', 'denoising_strength', 'eta']:
|
||||
try:
|
||||
params[key] = float(value)
|
||||
except:
|
||||
if ':' in part:
|
||||
# Find the first colon that's not inside parentheses or brackets
|
||||
colon_pos = -1
|
||||
paren_depth = 0
|
||||
bracket_depth = 0
|
||||
in_quotes = False
|
||||
|
||||
for i, char in enumerate(part):
|
||||
if char == '"' and (i == 0 or part[i-1] != '\\'):
|
||||
in_quotes = not in_quotes
|
||||
elif char == '(' and not in_quotes:
|
||||
paren_depth += 1
|
||||
elif char == ')' and not in_quotes:
|
||||
paren_depth -= 1
|
||||
elif char == '[' and not in_quotes:
|
||||
bracket_depth += 1
|
||||
elif char == ']' and not in_quotes:
|
||||
bracket_depth -= 1
|
||||
elif char == ':' and not in_quotes and paren_depth == 0 and bracket_depth == 0:
|
||||
colon_pos = i
|
||||
break
|
||||
|
||||
if colon_pos > 0:
|
||||
key = part[:colon_pos].strip().lower().replace(' ', '_')
|
||||
value = part[colon_pos + 1:].strip()
|
||||
|
||||
# Remove quotes if present
|
||||
if value.startswith('"') and value.endswith('"'):
|
||||
value = value[1:-1]
|
||||
|
||||
print(f"MetaMan Debug: Parsed parameter '{key}': '{value}' (length: {len(value)})")
|
||||
|
||||
# Convert known numeric values
|
||||
if key in ['steps', 'width', 'height', 'seed', 'clip_skip']:
|
||||
try:
|
||||
params[key] = int(value)
|
||||
except ValueError:
|
||||
params[key] = value
|
||||
elif key in ['cfg_scale', 'denoising_strength', 'eta']:
|
||||
try:
|
||||
params[key] = float(value)
|
||||
except ValueError:
|
||||
params[key] = value
|
||||
else:
|
||||
params[key] = value
|
||||
else:
|
||||
params[key] = value
|
||||
print(f"MetaMan Debug: Skipping malformed parameter part: '{part}'")
|
||||
else:
|
||||
print(f"MetaMan Debug: Skipping non-parameter part: '{part}'")
|
||||
|
||||
print(f"MetaMan Debug: Final parsed parameters: {list(params.keys())}")
|
||||
return params
|
||||
|
||||
def _extract_params_from_comfyui_prompt(self, prompt_data: dict) -> dict:
|
||||
@@ -906,17 +958,23 @@ class MetaManLoadImage:
|
||||
return classified
|
||||
|
||||
def _score_as_positive_prompt(self, candidate: dict) -> float:
|
||||
"""Score text as likely positive prompt"""
|
||||
"""Score text as likely positive prompt with enhanced detection for processed fields"""
|
||||
score = 0.0
|
||||
text = candidate['text']
|
||||
text_lower = text.lower()
|
||||
field_name = candidate['field_name'].lower()
|
||||
node_type = candidate['node_type']
|
||||
|
||||
# Field name indicators (strong signals)
|
||||
# ENHANCED: Field name indicators (strong signals)
|
||||
if 'positive' in field_name or 'prompt' in field_name:
|
||||
score += 3.0
|
||||
if 'populated' in field_name or 'formatted' in field_name:
|
||||
score += 2.0 # Processed text usually main prompt
|
||||
# PRIORITY: Processed/populated fields are very likely to be the main prompt
|
||||
if 'populated' in field_name or 'formatted' in field_name or 'processed' in field_name:
|
||||
score += 4.0 # Increased from 2.0 - these are usually the complete prompt
|
||||
print(f"MetaMan Universal: HIGH PRIORITY processed field detected: {candidate['source']}")
|
||||
# Custom node field detection
|
||||
if 'wildcard' in field_name or 'impact' in node_type.lower():
|
||||
score += 3.0 # ImpactWildcardEncode is a common complete prompt source
|
||||
if 'text' in field_name:
|
||||
score += 1.0
|
||||
|
||||
@@ -933,17 +991,24 @@ class MetaManLoadImage:
|
||||
# LoRA presence (strong indicator of main prompt)
|
||||
if '<lora:' in text:
|
||||
lora_count = text.count('<lora:')
|
||||
score += lora_count * 1.0
|
||||
print(f"MetaMan Universal: Found {lora_count} LoRAs in {candidate['source']} (+{lora_count} score)")
|
||||
score += lora_count * 2.0 # Increased weight - LoRAs are almost always in positive prompts
|
||||
print(f"MetaMan Universal: Found {lora_count} LoRAs in {candidate['source']} (+{lora_count * 2.0} score)")
|
||||
|
||||
# Length scoring (longer text often positive)
|
||||
if len(text) > 200:
|
||||
# ENHANCED: Length scoring with better thresholds
|
||||
text_length = len(text)
|
||||
if text_length > 500:
|
||||
score += 3.0 # Very long text likely main prompt
|
||||
elif text_length > 200:
|
||||
score += 2.0
|
||||
elif len(text) > 100:
|
||||
elif text_length > 100:
|
||||
score += 1.0
|
||||
elif len(text) > 50:
|
||||
elif text_length > 50:
|
||||
score += 0.5
|
||||
|
||||
# BREAK indicators (common in ComfyUI prompts)
|
||||
if 'BREAK' in text.upper():
|
||||
score += 1.0 # BREAK is common in detailed positive prompts
|
||||
|
||||
# Negative indicators (reduce score)
|
||||
negative_keywords = ['worst', 'low quality', 'bad', 'ugly', 'blurry', 'deformed']
|
||||
negative_count = sum(1 for keyword in negative_keywords if keyword in text_lower)
|
||||
@@ -1000,6 +1065,27 @@ class MetaManLoadImage:
|
||||
|
||||
return max(0.0, score)
|
||||
|
||||
def _extract_loras_from_text(self, text: str) -> list:
|
||||
"""Extract LoRA information from text using regex"""
|
||||
import re
|
||||
|
||||
loras = []
|
||||
|
||||
# Pattern for <lora:name:weight> or <lora:name>
|
||||
lora_pattern = r'<lora:([^>:]+)(?::([0-9.]+))?[^>]*>'
|
||||
matches = re.findall(lora_pattern, text, re.IGNORECASE)
|
||||
|
||||
for match in matches:
|
||||
name = match[0].strip()
|
||||
weight = float(match[1]) if match[1] else 1.0
|
||||
|
||||
loras.append({
|
||||
'name': name,
|
||||
'weight': weight
|
||||
})
|
||||
|
||||
return loras
|
||||
|
||||
def _extract_loras_universal(self, text_candidates: list) -> list:
|
||||
"""Extract LoRAs from all text content"""
|
||||
all_loras = []
|
||||
|
||||
Reference in New Issue
Block a user