6252be6c6f
When rotation is detected, the OCR coordinate system needs to be swapped: - Original OCR dimensions: 1242 x 1755 (portrait image) - Content coordinates: up to x=1593 (exceeds image width, indicates rotation) - Rotated OCR dimensions: 1755 x 1242 (matching content coordinate system) Previously, page_dimensions was incorrectly set to target PDF dimensions, causing scale factors to be ~1.0 instead of ~0.48. Now correctly: - original_page_sizes[0] = target PDF dimensions (842.4 x 595.68) - page_dimensions[0] = swapped OCR dimensions (1755 x 1242) - Scale = 842.4/1755 ≈ 0.48 for both x and y 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
3581 lines
154 KiB
Python
3581 lines
154 KiB
Python
"""
|
||
Layout-Preserving PDF Generation Service
|
||
Generates PDF files that preserve the original document layout using OCR JSON data
|
||
"""
|
||
|
||
import json
|
||
import logging
|
||
import re
|
||
from pathlib import Path
|
||
from typing import Dict, List, Optional, Tuple, Union
|
||
from datetime import datetime
|
||
|
||
from reportlab.lib.pagesizes import A4, letter
|
||
from reportlab.lib.units import mm
|
||
from reportlab.pdfgen import canvas
|
||
from reportlab.pdfbase import pdfmetrics
|
||
from reportlab.pdfbase.ttfonts import TTFont
|
||
from reportlab.platypus import Table, TableStyle
|
||
from reportlab.lib import colors
|
||
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT
|
||
from reportlab.platypus import Paragraph
|
||
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
|
||
from PIL import Image
|
||
from html.parser import HTMLParser
|
||
|
||
from app.core.config import settings
|
||
|
||
# Import UnifiedDocument for dual-track support
|
||
try:
|
||
from app.models.unified_document import (
|
||
UnifiedDocument, DocumentElement, ElementType,
|
||
BoundingBox, TableData, ProcessingTrack,
|
||
DocumentMetadata, Dimensions, Page, StyleInfo
|
||
)
|
||
UNIFIED_DOCUMENT_AVAILABLE = True
|
||
except ImportError:
|
||
UNIFIED_DOCUMENT_AVAILABLE = False
|
||
UnifiedDocument = None
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
|
||
class HTMLTableParser(HTMLParser):
|
||
"""Parse HTML table to extract structure and data"""
|
||
|
||
def __init__(self):
|
||
super().__init__()
|
||
self.tables = []
|
||
self.current_table = None
|
||
self.current_row = None
|
||
self.current_cell = None
|
||
self.in_table = False
|
||
|
||
def handle_starttag(self, tag, attrs):
|
||
attrs_dict = dict(attrs)
|
||
|
||
if tag == 'table':
|
||
self.in_table = True
|
||
self.current_table = {'rows': []}
|
||
|
||
elif tag == 'tr' and self.in_table:
|
||
self.current_row = {'cells': []}
|
||
|
||
elif tag in ('td', 'th') and self.in_table and self.current_row is not None:
|
||
colspan = int(attrs_dict.get('colspan', 1))
|
||
rowspan = int(attrs_dict.get('rowspan', 1))
|
||
self.current_cell = {
|
||
'text': '',
|
||
'is_header': tag == 'th',
|
||
'colspan': colspan,
|
||
'rowspan': rowspan
|
||
}
|
||
|
||
def handle_endtag(self, tag):
|
||
if tag == 'table' and self.in_table:
|
||
if self.current_table and self.current_table['rows']:
|
||
self.tables.append(self.current_table)
|
||
self.current_table = None
|
||
self.in_table = False
|
||
|
||
elif tag == 'tr' and self.current_row is not None:
|
||
if self.current_table is not None:
|
||
self.current_table['rows'].append(self.current_row)
|
||
self.current_row = None
|
||
|
||
elif tag in ('td', 'th') and self.current_cell is not None:
|
||
if self.current_row is not None:
|
||
self.current_row['cells'].append(self.current_cell)
|
||
self.current_cell = None
|
||
|
||
def handle_data(self, data):
|
||
if self.current_cell is not None:
|
||
self.current_cell['text'] += data.strip() + ' '
|
||
|
||
|
||
class PDFGeneratorService:
|
||
"""Service for generating layout-preserving PDFs from OCR JSON data"""
|
||
|
||
# Font mapping from common fonts to PDF standard fonts
|
||
FONT_MAPPING = {
|
||
'Arial': 'Helvetica',
|
||
'Arial Black': 'Helvetica-Bold',
|
||
'Times New Roman': 'Times-Roman',
|
||
'Times': 'Times-Roman',
|
||
'Courier New': 'Courier',
|
||
'Courier': 'Courier',
|
||
'Calibri': 'Helvetica',
|
||
'Cambria': 'Times-Roman',
|
||
'Georgia': 'Times-Roman',
|
||
'Verdana': 'Helvetica',
|
||
'Tahoma': 'Helvetica',
|
||
'Trebuchet MS': 'Helvetica',
|
||
'Comic Sans MS': 'Helvetica',
|
||
'Impact': 'Helvetica-Bold',
|
||
'Lucida Console': 'Courier',
|
||
'Palatino': 'Times-Roman',
|
||
'Garamond': 'Times-Roman',
|
||
'Bookman': 'Times-Roman',
|
||
'Century Gothic': 'Helvetica',
|
||
'Franklin Gothic': 'Helvetica',
|
||
}
|
||
|
||
# Style flags for text formatting
|
||
STYLE_FLAG_BOLD = 1
|
||
STYLE_FLAG_ITALIC = 2
|
||
STYLE_FLAG_UNDERLINE = 4
|
||
STYLE_FLAG_STRIKETHROUGH = 8
|
||
|
||
def __init__(self):
|
||
"""Initialize PDF generator with font configuration"""
|
||
self.font_name = 'NotoSansSC'
|
||
self.font_path = None
|
||
self.font_registered = False
|
||
self.current_processing_track = None # Track type for current document
|
||
|
||
self._register_chinese_font()
|
||
|
||
def _register_chinese_font(self):
|
||
"""Register Chinese font for PDF generation"""
|
||
try:
|
||
# Get font path from settings
|
||
font_path = Path(settings.chinese_font_path)
|
||
|
||
# Try relative path from project root
|
||
if not font_path.is_absolute():
|
||
# Adjust path - settings.chinese_font_path starts with ./backend/
|
||
project_root = Path(__file__).resolve().parent.parent.parent.parent
|
||
font_path = project_root / font_path
|
||
|
||
if not font_path.exists():
|
||
logger.error(f"Chinese font not found at {font_path}")
|
||
return
|
||
|
||
# Register font
|
||
pdfmetrics.registerFont(TTFont(self.font_name, str(font_path)))
|
||
self.font_path = font_path
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||
self.font_registered = True
|
||
logger.info(f"Chinese font registered: {self.font_name} from {font_path}")
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to register Chinese font: {e}")
|
||
self.font_registered = False
|
||
|
||
def _detect_content_orientation(
|
||
self,
|
||
page_width: float,
|
||
page_height: float,
|
||
ocr_data: Dict
|
||
) -> Tuple[bool, float, float]:
|
||
"""
|
||
Detect if content orientation differs from page dimensions.
|
||
|
||
This handles cases where a document is scanned in portrait orientation
|
||
but the actual content is landscape (or vice versa). PP-StructureV3
|
||
may return bounding boxes in the "corrected" orientation while the
|
||
image remains in its scanned orientation.
|
||
|
||
Args:
|
||
page_width: Declared page width from image dimensions
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||
page_height: Declared page height from image dimensions
|
||
ocr_data: OCR data dictionary containing bounding boxes
|
||
|
||
Returns:
|
||
Tuple of (needs_rotation, adjusted_width, adjusted_height)
|
||
- needs_rotation: True if page orientation should be swapped
|
||
- adjusted_width: Width to use for PDF page
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||
- adjusted_height: Height to use for PDF page
|
||
"""
|
||
# Find max content bounds from all regions
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||
max_x = 0
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||
max_y = 0
|
||
|
||
all_regions = []
|
||
|
||
# Collect regions from various sources
|
||
if 'text_regions' in ocr_data and isinstance(ocr_data['text_regions'], list):
|
||
all_regions.extend(ocr_data['text_regions'])
|
||
|
||
if 'layout_data' in ocr_data and isinstance(ocr_data['layout_data'], dict):
|
||
elements = ocr_data['layout_data'].get('elements', [])
|
||
if elements:
|
||
all_regions.extend(elements)
|
||
|
||
if 'images_metadata' in ocr_data and isinstance(ocr_data['images_metadata'], list):
|
||
all_regions.extend(ocr_data['images_metadata'])
|
||
|
||
for region in all_regions:
|
||
try:
|
||
bbox = region.get('bbox')
|
||
if not bbox:
|
||
continue
|
||
|
||
# Handle different bbox formats
|
||
if isinstance(bbox, dict):
|
||
# BoundingBox object format
|
||
max_x = max(max_x, float(bbox.get('x1', bbox.get('x0', 0) + bbox.get('width', 0))))
|
||
max_y = max(max_y, float(bbox.get('y1', bbox.get('y0', 0) + bbox.get('height', 0))))
|
||
elif isinstance(bbox, (list, tuple)):
|
||
if len(bbox) >= 4 and isinstance(bbox[0], (int, float)):
|
||
# [x1, y1, x2, y2] format
|
||
max_x = max(max_x, float(bbox[2]))
|
||
max_y = max(max_y, float(bbox[3]))
|
||
elif isinstance(bbox[0], (list, tuple)):
|
||
# Polygon format [[x, y], ...]
|
||
x_coords = [p[0] for p in bbox if len(p) >= 2]
|
||
y_coords = [p[1] for p in bbox if len(p) >= 2]
|
||
if x_coords and y_coords:
|
||
max_x = max(max_x, max(x_coords))
|
||
max_y = max(max_y, max(y_coords))
|
||
except Exception as e:
|
||
logger.debug(f"Error processing bbox for orientation detection: {e}")
|
||
continue
|
||
|
||
if max_x == 0 or max_y == 0:
|
||
# No valid bboxes found, use original dimensions
|
||
return (False, page_width, page_height)
|
||
|
||
logger.info(f"內容邊界偵測: max_x={max_x:.1f}, max_y={max_y:.1f}, "
|
||
f"page_dims={page_width:.1f}x{page_height:.1f}")
|
||
|
||
# Calculate how much content extends beyond page boundaries
|
||
x_overflow = max_x / page_width if page_width > 0 else 1
|
||
y_overflow = max_y / page_height if page_height > 0 else 1
|
||
|
||
# Check if content significantly exceeds page dimensions in one direction
|
||
# This suggests the content is in a different orientation
|
||
OVERFLOW_THRESHOLD = 1.15 # Content extends >15% beyond declared dimensions
|
||
|
||
if x_overflow > OVERFLOW_THRESHOLD and y_overflow <= 1.05:
|
||
# Content is wider than page but fits in height
|
||
# This suggests portrait image with landscape content
|
||
logger.warning(f"偵測到內容方向可能與頁面不符: "
|
||
f"x_overflow={x_overflow:.2f}, y_overflow={y_overflow:.2f}")
|
||
|
||
# Check if swapping dimensions would help
|
||
# If max_x fits better in page_height, swap
|
||
if max_x <= page_height * 1.05:
|
||
logger.info(f"建議頁面旋轉: {page_width:.1f}x{page_height:.1f} -> "
|
||
f"{page_height:.1f}x{page_width:.1f}")
|
||
return (True, page_height, page_width)
|
||
else:
|
||
# Content still doesn't fit, just scale to fit content
|
||
logger.info(f"內容超出頁面邊界，調整頁面大小以容納內容")
|
||
return (False, max_x * 1.02, page_height)
|
||
|
||
elif y_overflow > OVERFLOW_THRESHOLD and x_overflow <= 1.05:
|
||
# Content is taller than page but fits in width
|
||
# Less common - landscape image with portrait content
|
||
logger.warning(f"偵測到內容方向可能與頁面不符 (高度溢出): "
|
||
f"x_overflow={x_overflow:.2f}, y_overflow={y_overflow:.2f}")
|
||
|
||
if max_y <= page_width * 1.05:
|
||
logger.info(f"建議頁面旋轉: {page_width:.1f}x{page_height:.1f} -> "
|
||
f"{page_height:.1f}x{page_width:.1f}")
|
||
return (True, page_height, page_width)
|
||
else:
|
||
logger.info(f"內容超出頁面邊界，調整頁面大小以容納內容")
|
||
return (False, page_width, max_y * 1.02)
|
||
|
||
# No orientation issue detected
|
||
return (False, page_width, page_height)
|
||
|
||
def _parse_color(self, color_value) -> Tuple[float, float, float]:
|
||
"""
|
||
Parse color value to RGB tuple.
|
||
|
||
Args:
|
||
color_value: Color as hex string (#RRGGBB), RGB tuple, or color name
|
||
|
||
Returns:
|
||
RGB tuple with values 0-1 for ReportLab
|
||
"""
|
||
if not color_value:
|
||
return (0, 0, 0) # Default to black
|
||
|
||
try:
|
||
# Handle hex color (#RRGGBB or #RGB)
|
||
if isinstance(color_value, str) and color_value.startswith('#'):
|
||
hex_color = color_value.lstrip('#')
|
||
|
||
# Expand short form (#RGB -> #RRGGBB)
|
||
if len(hex_color) == 3:
|
||
hex_color = ''.join([c*2 for c in hex_color])
|
||
|
||
if len(hex_color) == 6:
|
||
r = int(hex_color[0:2], 16) / 255.0
|
||
g = int(hex_color[2:4], 16) / 255.0
|
||
b = int(hex_color[4:6], 16) / 255.0
|
||
return (r, g, b)
|
||
|
||
# Handle RGB tuple or list
|
||
elif isinstance(color_value, (tuple, list)) and len(color_value) >= 3:
|
||
r, g, b = color_value[0:3]
|
||
# Normalize to 0-1 if values are 0-255
|
||
if any(v > 1 for v in [r, g, b]):
|
||
return (r/255.0, g/255.0, b/255.0)
|
||
return (r, g, b)
|
||
|
||
except (ValueError, TypeError) as e:
|
||
logger.warning(f"Failed to parse color {color_value}: {e}")
|
||
|
||
# Default to black
|
||
return (0, 0, 0)
|
||
|
||
def _map_font(self, font_name: Optional[str]) -> str:
|
||
"""
|
||
Map font name to PDF standard font.
|
||
|
||
Args:
|
||
font_name: Original font name
|
||
|
||
Returns:
|
||
PDF standard font name
|
||
"""
|
||
if not font_name:
|
||
return 'Helvetica'
|
||
|
||
# Direct lookup
|
||
if font_name in self.FONT_MAPPING:
|
||
return self.FONT_MAPPING[font_name]
|
||
|
||
# Case-insensitive lookup
|
||
font_lower = font_name.lower()
|
||
for orig_font, pdf_font in self.FONT_MAPPING.items():
|
||
if orig_font.lower() == font_lower:
|
||
return pdf_font
|
||
|
||
# Partial match for common patterns
|
||
if 'arial' in font_lower:
|
||
return 'Helvetica'
|
||
elif 'times' in font_lower:
|
||
return 'Times-Roman'
|
||
elif 'courier' in font_lower:
|
||
return 'Courier'
|
||
|
||
# Default fallback
|
||
logger.debug(f"Font '{font_name}' not found in mapping, using Helvetica")
|
||
return 'Helvetica'
|
||
|
||
def _apply_text_style(self, c: canvas.Canvas, style_info, default_size: float = 12):
|
||
"""
|
||
Apply text styling from StyleInfo to PDF canvas.
|
||
|
||
Args:
|
||
c: ReportLab canvas object
|
||
style_info: StyleInfo object or dict with font, size, color, flags
|
||
default_size: Default font size if not specified
|
||
"""
|
||
if not style_info:
|
||
# Apply default styling
|
||
c.setFont('Helvetica', default_size)
|
||
c.setFillColorRGB(0, 0, 0)
|
||
return
|
||
|
||
try:
|
||
# Extract style attributes
|
||
if hasattr(style_info, '__dict__'):
|
||
# StyleInfo object
|
||
font_family = getattr(style_info, 'font_name', None)
|
||
font_size = getattr(style_info, 'font_size', default_size)
|
||
color = getattr(style_info, 'text_color', None)
|
||
font_weight = getattr(style_info, 'font_weight', 'normal')
|
||
font_style = getattr(style_info, 'font_style', 'normal')
|
||
# Legacy flags support
|
||
flags = getattr(style_info, 'flags', 0)
|
||
elif isinstance(style_info, dict):
|
||
# Dictionary
|
||
font_family = style_info.get('font_name')
|
||
font_size = style_info.get('font_size', default_size)
|
||
color = style_info.get('text_color')
|
||
font_weight = style_info.get('font_weight', 'normal')
|
||
font_style = style_info.get('font_style', 'normal')
|
||
# Legacy flags support
|
||
flags = style_info.get('flags', 0)
|
||
else:
|
||
# Unknown format, use defaults
|
||
c.setFont('Helvetica', default_size)
|
||
c.setFillColorRGB(0, 0, 0)
|
||
return
|
||
|
||
# Map font name
|
||
base_font = self._map_font(font_family) if font_family else 'Helvetica'
|
||
|
||
# Determine bold and italic from font_weight/font_style (preferred) or flags (legacy)
|
||
is_bold = font_weight == 'bold' if font_weight else bool(flags & self.STYLE_FLAG_BOLD)
|
||
is_italic = font_style == 'italic' if font_style else bool(flags & self.STYLE_FLAG_ITALIC)
|
||
|
||
# Apply bold/italic modifiers
|
||
if is_bold or is_italic:
|
||
|
||
if is_bold and is_italic:
|
||
# Try bold-italic variant
|
||
if 'Helvetica' in base_font:
|
||
base_font = 'Helvetica-BoldOblique'
|
||
elif 'Times' in base_font:
|
||
base_font = 'Times-BoldItalic'
|
||
elif 'Courier' in base_font:
|
||
base_font = 'Courier-BoldOblique'
|
||
elif is_bold:
|
||
# Try bold variant
|
||
if 'Helvetica' in base_font:
|
||
base_font = 'Helvetica-Bold'
|
||
elif 'Times' in base_font:
|
||
base_font = 'Times-Bold'
|
||
elif 'Courier' in base_font:
|
||
base_font = 'Courier-Bold'
|
||
elif is_italic:
|
||
# Try italic variant
|
||
if 'Helvetica' in base_font:
|
||
base_font = 'Helvetica-Oblique'
|
||
elif 'Times' in base_font:
|
||
base_font = 'Times-Italic'
|
||
elif 'Courier' in base_font:
|
||
base_font = 'Courier-Oblique'
|
||
|
||
# Apply font and size
|
||
actual_size = font_size if font_size and font_size > 0 else default_size
|
||
try:
|
||
c.setFont(base_font, actual_size)
|
||
except KeyError:
|
||
# Font not available, fallback
|
||
logger.warning(f"Font '{base_font}' not available, using Helvetica")
|
||
c.setFont('Helvetica', actual_size)
|
||
|
||
# Apply color
|
||
rgb_color = None
|
||
if hasattr(style_info, 'get_rgb_color'):
|
||
# Use StyleInfo method if available
|
||
rgb_color = style_info.get_rgb_color()
|
||
elif color is not None:
|
||
# Parse from extracted color value
|
||
r, g, b = self._parse_color(color)
|
||
rgb_color = (r, g, b)
|
||
|
||
if rgb_color:
|
||
# text_color is in 0-255 range, convert to 0-1 for ReportLab
|
||
r, g, b = rgb_color
|
||
if any(v > 1 for v in [r, g, b]):
|
||
r, g, b = r/255.0, g/255.0, b/255.0
|
||
c.setFillColorRGB(r, g, b)
|
||
else:
|
||
c.setFillColorRGB(0, 0, 0) # Default black
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to apply text style: {e}")
|
||
# Fallback to defaults
|
||
c.setFont('Helvetica', default_size)
|
||
c.setFillColorRGB(0, 0, 0)
|
||
|
||
def load_ocr_json(self, json_path: Path) -> Optional[Dict]:
|
||
"""
|
||
Load and parse OCR JSON result file
|
||
|
||
Args:
|
||
json_path: Path to JSON file
|
||
|
||
Returns:
|
||
Parsed JSON data or None if failed
|
||
"""
|
||
try:
|
||
with open(json_path, 'r', encoding='utf-8') as f:
|
||
data = json.load(f)
|
||
|
||
logger.info(f"Loaded OCR JSON: {json_path.name}")
|
||
return data
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to load JSON {json_path}: {e}")
|
||
return None
|
||
|
||
def _get_image_path(self, element) -> Optional[str]:
|
||
"""
|
||
Get image path with fallback logic.
|
||
|
||
Checks multiple locations in order:
|
||
1. element.content["saved_path"] - Direct track saved path
|
||
2. element.content["path"] - Legacy path
|
||
3. element.content["image_path"] - Alternative path
|
||
4. element.saved_path - Direct attribute
|
||
5. element.metadata["path"] - Metadata fallback
|
||
|
||
Args:
|
||
element: DocumentElement object
|
||
|
||
Returns:
|
||
Path to image file or None if not found
|
||
"""
|
||
# Check content dictionary
|
||
if isinstance(element.content, dict):
|
||
for key in ['saved_path', 'path', 'image_path']:
|
||
if key in element.content:
|
||
return element.content[key]
|
||
|
||
# Check direct attribute
|
||
if hasattr(element, 'saved_path') and element.saved_path:
|
||
return element.saved_path
|
||
|
||
# Check metadata
|
||
if element.metadata and isinstance(element.metadata, dict):
|
||
if 'path' in element.metadata:
|
||
return element.metadata['path']
|
||
if 'saved_path' in element.metadata:
|
||
return element.metadata['saved_path']
|
||
|
||
return None
|
||
|
||
def convert_unified_document_to_ocr_data(self, unified_doc: 'UnifiedDocument') -> Dict:
|
||
"""
|
||
Convert UnifiedDocument to OCR data format for PDF generation.
|
||
|
||
This method transforms the UnifiedDocument structure into the legacy
|
||
OCR data format that the PDF generator expects, supporting both
|
||
OCR and DIRECT processing tracks.
|
||
|
||
Args:
|
||
unified_doc: UnifiedDocument object from either processing track
|
||
|
||
Returns:
|
||
Dictionary in OCR data format with text_regions, images_metadata, layout_data
|
||
"""
|
||
text_regions = []
|
||
images_metadata = []
|
||
layout_elements = []
|
||
|
||
for page in unified_doc.pages:
|
||
page_num = page.page_number # 1-based
|
||
|
||
for element in page.elements:
|
||
# Convert BoundingBox to polygon format [[x,y], [x,y], [x,y], [x,y]]
|
||
bbox_polygon = [
|
||
[element.bbox.x0, element.bbox.y0], # top-left
|
||
[element.bbox.x1, element.bbox.y0], # top-right
|
||
[element.bbox.x1, element.bbox.y1], # bottom-right
|
||
[element.bbox.x0, element.bbox.y1], # bottom-left
|
||
]
|
||
|
||
# Handle text elements
|
||
if element.is_text or element.type in [
|
||
ElementType.TEXT, ElementType.TITLE, ElementType.HEADER,
|
||
ElementType.FOOTER, ElementType.PARAGRAPH, ElementType.CAPTION,
|
||
ElementType.LIST_ITEM, ElementType.FOOTNOTE, ElementType.REFERENCE
|
||
]:
|
||
text_content = element.get_text()
|
||
if text_content:
|
||
text_region = {
|
||
'text': text_content,
|
||
'bbox': bbox_polygon,
|
||
'confidence': element.confidence or 1.0,
|
||
'page': page_num,
|
||
'element_type': element.type.value # Include element type for styling
|
||
}
|
||
|
||
# Include style information if available (for Direct track)
|
||
if hasattr(element, 'style') and element.style:
|
||
text_region['style'] = element.style
|
||
|
||
text_regions.append(text_region)
|
||
|
||
# Handle table elements
|
||
elif element.type == ElementType.TABLE:
|
||
# Convert TableData to HTML for layout_data
|
||
if isinstance(element.content, TableData):
|
||
html_content = element.content.to_html()
|
||
elif isinstance(element.content, dict):
|
||
html_content = element.content.get('html', str(element.content))
|
||
else:
|
||
html_content = str(element.content)
|
||
|
||
table_element = {
|
||
'type': 'table',
|
||
'content': html_content,
|
||
'bbox': [element.bbox.x0, element.bbox.y0,
|
||
element.bbox.x1, element.bbox.y1],
|
||
'page': page_num - 1 # layout uses 0-based
|
||
}
|
||
|
||
# Preserve cell_boxes and embedded_images from metadata
|
||
# These are extracted by PP-StructureV3 and used for accurate table rendering
|
||
if element.metadata:
|
||
if 'cell_boxes' in element.metadata:
|
||
table_element['cell_boxes'] = element.metadata['cell_boxes']
|
||
table_element['cell_boxes_source'] = element.metadata.get('cell_boxes_source', 'metadata')
|
||
if 'embedded_images' in element.metadata:
|
||
table_element['embedded_images'] = element.metadata['embedded_images']
|
||
|
||
layout_elements.append(table_element)
|
||
|
||
# Add bbox to images_metadata for text overlap filtering
|
||
# (no actual image file, just bbox for filtering)
|
||
images_metadata.append({
|
||
'image_path': None, # No fake table image
|
||
'bbox': bbox_polygon,
|
||
'page': page_num - 1, # 0-based for images_metadata
|
||
'type': 'table',
|
||
'element_id': element.element_id
|
||
})
|
||
|
||
# Handle image/visual elements (including stamps/seals)
|
||
elif element.is_visual or element.type in [
|
||
ElementType.IMAGE, ElementType.FIGURE, ElementType.CHART,
|
||
ElementType.DIAGRAM, ElementType.LOGO, ElementType.STAMP
|
||
]:
|
||
# Get image path using fallback logic
|
||
image_path = self._get_image_path(element)
|
||
|
||
# Only add if we found a valid path
|
||
if image_path:
|
||
images_metadata.append({
|
||
'image_path': image_path,
|
||
'bbox': bbox_polygon,
|
||
'page': page_num - 1, # 0-based
|
||
'type': element.type.value
|
||
})
|
||
logger.debug(f"Found image path: {image_path} for element {element.element_id}")
|
||
else:
|
||
logger.warning(f"No image path found for visual element {element.element_id}")
|
||
|
||
# Build page dimensions mapping for multi-page support
|
||
page_dimensions = {}
|
||
for page in unified_doc.pages:
|
||
page_dimensions[page.page_number - 1] = { # 0-based index
|
||
'width': page.dimensions.width,
|
||
'height': page.dimensions.height
|
||
}
|
||
|
||
# Build OCR data structure
|
||
ocr_data = {
|
||
'text_regions': text_regions,
|
||
'images_metadata': images_metadata,
|
||
'layout_data': {
|
||
'elements': layout_elements,
|
||
'total_elements': len(layout_elements)
|
||
},
|
||
'total_pages': unified_doc.page_count,
|
||
'ocr_dimensions': {
|
||
'width': unified_doc.pages[0].dimensions.width if unified_doc.pages else 0,
|
||
'height': unified_doc.pages[0].dimensions.height if unified_doc.pages else 0
|
||
},
|
||
'page_dimensions': page_dimensions, # Per-page dimensions for multi-page support
|
||
# Metadata for tracking
|
||
'_from_unified_document': True,
|
||
'_processing_track': unified_doc.metadata.processing_track.value
|
||
}
|
||
|
||
logger.info(f"Converted UnifiedDocument to OCR data: "
|
||
f"{len(text_regions)} text regions, "
|
||
f"{len(images_metadata)} images, "
|
||
f"{len(layout_elements)} layout elements, "
|
||
f"track={unified_doc.metadata.processing_track.value}")
|
||
|
||
return ocr_data
|
||
|
||
def generate_from_unified_document(
|
||
self,
|
||
unified_doc: 'UnifiedDocument',
|
||
output_path: Path,
|
||
source_file_path: Optional[Path] = None
|
||
) -> bool:
|
||
"""
|
||
Generate layout-preserving PDF directly from UnifiedDocument.
|
||
|
||
This method supports both OCR and DIRECT processing tracks,
|
||
preserving layout and coordinate information from either source.
|
||
|
||
Args:
|
||
unified_doc: UnifiedDocument object
|
||
output_path: Path to save generated PDF
|
||
source_file_path: Optional path to original source file
|
||
|
||
Returns:
|
||
True if successful, False otherwise
|
||
"""
|
||
if not UNIFIED_DOCUMENT_AVAILABLE:
|
||
logger.error("UnifiedDocument support not available")
|
||
return False
|
||
|
||
try:
|
||
# Detect processing track for track-specific rendering
|
||
processing_track = None
|
||
if hasattr(unified_doc, 'metadata') and unified_doc.metadata:
|
||
if hasattr(unified_doc.metadata, 'processing_track'):
|
||
processing_track = unified_doc.metadata.processing_track
|
||
elif isinstance(unified_doc.metadata, dict):
|
||
processing_track = unified_doc.metadata.get('processing_track')
|
||
|
||
# Route to track-specific rendering method
|
||
# ProcessingTrack is (str, Enum), so comparing with enum value works for both string and enum
|
||
# HYBRID track uses Direct track rendering (Direct text/tables + OCR images)
|
||
is_direct_track = (processing_track == ProcessingTrack.DIRECT or
|
||
processing_track == ProcessingTrack.HYBRID)
|
||
|
||
logger.info(f"Processing track: {processing_track}, using {'Direct' if is_direct_track else 'OCR'} track rendering")
|
||
|
||
if is_direct_track:
|
||
# Direct track: Rich formatting preservation
|
||
return self._generate_direct_track_pdf(
|
||
unified_doc=unified_doc,
|
||
output_path=output_path,
|
||
source_file_path=source_file_path
|
||
)
|
||
else:
|
||
# OCR track: Simplified rendering (backward compatible)
|
||
return self._generate_ocr_track_pdf(
|
||
unified_doc=unified_doc,
|
||
output_path=output_path,
|
||
source_file_path=source_file_path
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to generate PDF from UnifiedDocument: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return False
|
||
|
||
def _is_element_inside_regions(self, element_bbox, regions_elements, overlap_threshold=0.5) -> bool:
|
||
"""
|
||
Check if an element overlaps significantly with any exclusion region (table, image).
|
||
|
||
This prevents duplicate rendering when text overlaps with tables/images.
|
||
Direct extraction often extracts both the structured element (table/image)
|
||
AND its text content as separate text blocks.
|
||
|
||
Uses overlap ratio detection instead of strict containment, since text blocks
|
||
from DirectExtractionEngine may be larger than detected table/image regions
|
||
(e.g., text block includes heading above table).
|
||
|
||
Args:
|
||
element_bbox: BBox of the element to check
|
||
regions_elements: List of region elements (tables, images) to check against
|
||
overlap_threshold: Minimum overlap percentage to trigger filtering (default 0.5 = 50%)
|
||
|
||
Returns:
|
||
True if element overlaps ≥50% with any region, False otherwise
|
||
"""
|
||
if not element_bbox:
|
||
return False
|
||
|
||
e_x0, e_y0, e_x1, e_y1 = element_bbox.x0, element_bbox.y0, element_bbox.x1, element_bbox.y1
|
||
elem_area = (e_x1 - e_x0) * (e_y1 - e_y0)
|
||
|
||
if elem_area <= 0:
|
||
return False
|
||
|
||
for region in regions_elements:
|
||
r_bbox = region.bbox
|
||
if not r_bbox:
|
||
continue
|
||
|
||
# Calculate overlap rectangle
|
||
overlap_x0 = max(e_x0, r_bbox.x0)
|
||
overlap_y0 = max(e_y0, r_bbox.y0)
|
||
overlap_x1 = min(e_x1, r_bbox.x1)
|
||
overlap_y1 = min(e_y1, r_bbox.y1)
|
||
|
||
# Check if there is any overlap
|
||
if overlap_x0 < overlap_x1 and overlap_y0 < overlap_y1:
|
||
# Calculate overlap area
|
||
overlap_area = (overlap_x1 - overlap_x0) * (overlap_y1 - overlap_y0)
|
||
overlap_ratio = overlap_area / elem_area
|
||
|
||
# If element overlaps more than threshold, filter it out
|
||
if overlap_ratio >= overlap_threshold:
|
||
return True
|
||
|
||
return False
|
||
|
||
def _generate_direct_track_pdf(
|
||
self,
|
||
unified_doc: 'UnifiedDocument',
|
||
output_path: Path,
|
||
source_file_path: Optional[Path] = None
|
||
) -> bool:
|
||
"""
|
||
Generate PDF with rich formatting preservation for Direct track.
|
||
|
||
This method processes UnifiedDocument directly without converting to
|
||
legacy OCR format, preserving StyleInfo and applying proper text
|
||
formatting including line breaks.
|
||
|
||
Args:
|
||
unified_doc: UnifiedDocument from Direct extraction
|
||
output_path: Path to save generated PDF
|
||
source_file_path: Optional path to original source file
|
||
|
||
Returns:
|
||
True if successful, False otherwise
|
||
"""
|
||
try:
|
||
logger.info("=== Direct Track PDF Generation ===")
|
||
logger.info(f"Total pages: {len(unified_doc.pages)}")
|
||
|
||
# Set current track for helper methods (may be DIRECT or HYBRID)
|
||
if hasattr(unified_doc, 'metadata') and unified_doc.metadata:
|
||
self.current_processing_track = unified_doc.metadata.processing_track
|
||
else:
|
||
self.current_processing_track = ProcessingTrack.DIRECT
|
||
|
||
# Get page dimensions from first page (for canvas initialization)
|
||
if not unified_doc.pages:
|
||
logger.error("No pages in document")
|
||
return False
|
||
|
||
first_page = unified_doc.pages[0]
|
||
page_width = first_page.dimensions.width
|
||
page_height = first_page.dimensions.height
|
||
|
||
logger.info(f"First page dimensions: {page_width} x {page_height}")
|
||
|
||
# Create PDF canvas with first page dimensions (will be updated per page)
|
||
from reportlab.pdfgen import canvas
|
||
pdf_canvas = canvas.Canvas(str(output_path), pagesize=(page_width, page_height))
|
||
|
||
# Process each page
|
||
for page_idx, page in enumerate(unified_doc.pages):
|
||
logger.info(f">>> Processing page {page_idx + 1}/{len(unified_doc.pages)}")
|
||
|
||
# Get current page dimensions
|
||
current_page_width = page.dimensions.width
|
||
current_page_height = page.dimensions.height
|
||
logger.info(f"Page {page_idx + 1} dimensions: {current_page_width} x {current_page_height}")
|
||
|
||
if page_idx > 0:
|
||
pdf_canvas.showPage()
|
||
|
||
# Set page size for current page
|
||
pdf_canvas.setPageSize((current_page_width, current_page_height))
|
||
|
||
# Separate elements by type
|
||
text_elements = []
|
||
table_elements = []
|
||
image_elements = []
|
||
list_elements = []
|
||
|
||
# FIX: Collect exclusion regions (tables, images) to prevent duplicate rendering
|
||
regions_to_avoid = []
|
||
|
||
for element in page.elements:
|
||
if element.type == ElementType.TABLE:
|
||
table_elements.append(element)
|
||
regions_to_avoid.append(element) # Tables are exclusion regions
|
||
elif element.is_visual or element.type in [
|
||
ElementType.IMAGE, ElementType.FIGURE,
|
||
ElementType.CHART, ElementType.DIAGRAM, ElementType.LOGO, ElementType.STAMP
|
||
]:
|
||
image_elements.append(element)
|
||
# Only add real images to exclusion regions, NOT charts/diagrams
|
||
# Charts often have large bounding boxes that include text labels
|
||
# which should be rendered as selectable text on top
|
||
if element.type in [ElementType.IMAGE, ElementType.FIGURE, ElementType.LOGO, ElementType.STAMP]:
|
||
regions_to_avoid.append(element)
|
||
elif element.type == ElementType.LIST_ITEM:
|
||
list_elements.append(element)
|
||
elif self._is_list_item_fallback(element):
|
||
# Fallback detection: Check metadata and text patterns
|
||
list_elements.append(element)
|
||
# Mark as list item for downstream processing
|
||
element.type = ElementType.LIST_ITEM
|
||
elif element.is_text or element.type in [
|
||
ElementType.TEXT, ElementType.TITLE, ElementType.HEADER,
|
||
ElementType.FOOTER, ElementType.PARAGRAPH
|
||
]:
|
||
text_elements.append(element)
|
||
|
||
logger.info(f"Page {page_idx + 1}: {len(text_elements)} text, "
|
||
f"{len(table_elements)} tables, {len(image_elements)} images, "
|
||
f"{len(list_elements)} list items")
|
||
|
||
# Use original element order from extraction engine
|
||
# The extraction engine has already sorted elements by reading order,
|
||
# handling multi-column layouts correctly (top-to-bottom, left-to-right)
|
||
all_elements = []
|
||
|
||
# Preserve original order by iterating through page.elements
|
||
for elem in page.elements:
|
||
if elem in image_elements:
|
||
all_elements.append(('image', elem))
|
||
elif elem in table_elements:
|
||
all_elements.append(('table', elem))
|
||
elif elem in list_elements:
|
||
all_elements.append(('list', elem))
|
||
elif elem in text_elements:
|
||
all_elements.append(('text', elem))
|
||
|
||
logger.debug(f"Drawing {len(all_elements)} elements in extraction order (preserves multi-column reading order)")
|
||
logger.debug(f"Exclusion regions: {len(regions_to_avoid)} (tables/images/charts)")
|
||
|
||
# Debug: Log exclusion region types
|
||
region_types = {}
|
||
for region in regions_to_avoid:
|
||
region_type = region.type.name
|
||
region_types[region_type] = region_types.get(region_type, 0) + 1
|
||
if region_types:
|
||
logger.debug(f" Exclusion region breakdown: {region_types}")
|
||
|
||
# Draw elements in document order
|
||
for elem_type, elem in all_elements:
|
||
if elem_type == 'image':
|
||
self._draw_image_element_direct(pdf_canvas, elem, current_page_height, output_path.parent)
|
||
elif elem_type == 'table':
|
||
self._draw_table_element_direct(pdf_canvas, elem, current_page_height)
|
||
elif elem_type == 'list':
|
||
# FIX: Check if list item overlaps with table/image
|
||
if not self._is_element_inside_regions(elem.bbox, regions_to_avoid):
|
||
self._draw_text_element_direct(pdf_canvas, elem, current_page_height)
|
||
else:
|
||
logger.debug(f"Skipping list element {elem.element_id} inside table/image region")
|
||
elif elem_type == 'text':
|
||
# FIX: Check if text overlaps with table/image before drawing
|
||
if not self._is_element_inside_regions(elem.bbox, regions_to_avoid):
|
||
self._draw_text_element_direct(pdf_canvas, elem, current_page_height)
|
||
else:
|
||
logger.debug(f"Skipping text element {elem.element_id} inside table/image region")
|
||
|
||
# Save PDF
|
||
pdf_canvas.save()
|
||
logger.info(f"Direct track PDF saved to {output_path}")
|
||
|
||
# Reset track
|
||
self.current_processing_track = None
|
||
return True
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to generate Direct track PDF: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
self.current_processing_track = None
|
||
return False
|
||
|
||
def _generate_ocr_track_pdf(
|
||
self,
|
||
unified_doc: 'UnifiedDocument',
|
||
output_path: Path,
|
||
source_file_path: Optional[Path] = None
|
||
) -> bool:
|
||
"""
|
||
Generate PDF with simplified rendering for OCR track.
|
||
|
||
This method uses the existing OCR data conversion and rendering
|
||
pipeline for backward compatibility.
|
||
|
||
Args:
|
||
unified_doc: UnifiedDocument from OCR processing
|
||
output_path: Path to save generated PDF
|
||
source_file_path: Optional path to original source file
|
||
|
||
Returns:
|
||
True if successful, False otherwise
|
||
"""
|
||
try:
|
||
logger.info("=== OCR Track PDF Generation ===")
|
||
|
||
# Set current track
|
||
self.current_processing_track = 'ocr'
|
||
|
||
# Convert UnifiedDocument to OCR data format (legacy)
|
||
ocr_data = self.convert_unified_document_to_ocr_data(unified_doc)
|
||
|
||
# Use existing generation pipeline
|
||
result = self._generate_pdf_from_data(
|
||
ocr_data=ocr_data,
|
||
output_path=output_path,
|
||
source_file_path=source_file_path
|
||
)
|
||
|
||
# Reset track
|
||
self.current_processing_track = None
|
||
return result
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to generate OCR track PDF: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
self.current_processing_track = None
|
||
return False
|
||
|
||
def _generate_pdf_from_data(
|
||
self,
|
||
ocr_data: Dict,
|
||
output_path: Path,
|
||
source_file_path: Optional[Path] = None,
|
||
json_parent_dir: Optional[Path] = None
|
||
) -> bool:
|
||
"""
|
||
Internal method to generate PDF from OCR data dictionary.
|
||
|
||
This is the core generation logic extracted for reuse by both
|
||
JSON-based and UnifiedDocument-based generation paths.
|
||
|
||
Args:
|
||
ocr_data: OCR data dictionary
|
||
output_path: Path to save generated PDF
|
||
source_file_path: Optional path to original source file
|
||
json_parent_dir: Directory containing images (for JSON-based generation)
|
||
|
||
Returns:
|
||
True if successful, False otherwise
|
||
"""
|
||
try:
|
||
# Note: Removed PDF caching - always regenerate to ensure latest code changes take effect
|
||
# If caching is needed, implement at a higher level with proper cache invalidation
|
||
|
||
# Get text regions
|
||
text_regions = ocr_data.get('text_regions', [])
|
||
if not text_regions:
|
||
logger.warning("No text regions found in data")
|
||
# Don't fail - might have only tables/images
|
||
|
||
# Get images metadata
|
||
images_metadata = ocr_data.get('images_metadata', [])
|
||
|
||
# Get layout data
|
||
layout_data = ocr_data.get('layout_data', {})
|
||
|
||
# Step 1: Get OCR processing dimensions (for first page / default)
|
||
ocr_width, ocr_height = self.calculate_page_dimensions(ocr_data, source_file_path=None)
|
||
logger.info(f"OCR 處理時使用的座標系尺寸 (第一頁): {ocr_width:.1f} x {ocr_height:.1f}")
|
||
|
||
# Step 2: Get page dimensions mapping for multi-page support
|
||
page_dimensions = ocr_data.get('page_dimensions', {})
|
||
if not page_dimensions:
|
||
# Fallback: use first page dimensions for all pages
|
||
page_dimensions = {0: {'width': ocr_width, 'height': ocr_height}}
|
||
logger.info("No page_dimensions found, using first page size for all pages")
|
||
|
||
# Step 3: Get original file dimensions for all pages
|
||
original_page_sizes = {}
|
||
if source_file_path:
|
||
original_page_sizes = self.get_all_page_sizes(source_file_path)
|
||
if original_page_sizes:
|
||
logger.info(f"從原始文件獲取到 {len(original_page_sizes)} 頁尺寸")
|
||
else:
|
||
logger.warning(f"無法獲取原始文件尺寸，將使用 OCR/UnifiedDocument 尺寸")
|
||
else:
|
||
logger.info(f"無原始文件，將使用 OCR/UnifiedDocument 尺寸")
|
||
|
||
# Determine initial canvas size (will be updated per page)
|
||
# Priority: original file first page > OCR/UnifiedDocument first page
|
||
if 0 in original_page_sizes:
|
||
target_width, target_height = original_page_sizes[0]
|
||
logger.info(f"初始 PDF 尺寸（來自原始文件首頁）: {target_width:.1f} x {target_height:.1f}")
|
||
else:
|
||
target_width, target_height = ocr_width, ocr_height
|
||
logger.info(f"初始 PDF 尺寸（來自 OCR/UnifiedDocument）: {target_width:.1f} x {target_height:.1f}")
|
||
|
||
# Step 4: Detect content orientation mismatch
|
||
# This handles rotated scans where content bbox exceeds page dimensions
|
||
# IMPORTANT: Use OCR dimensions (pixels) for detection, not PDF points
|
||
# because content bboxes are in the same coordinate system as OCR dimensions
|
||
needs_rotation, adjusted_ocr_width, adjusted_ocr_height = self._detect_content_orientation(
|
||
ocr_width, ocr_height, ocr_data
|
||
)
|
||
|
||
# If orientation change detected, calculate the adjusted target dimensions
|
||
if needs_rotation:
|
||
# Swap target dimensions to match the detected orientation
|
||
adjusted_width = target_height
|
||
adjusted_height = target_width
|
||
elif adjusted_ocr_width != ocr_width or adjusted_ocr_height != ocr_height:
|
||
# Content extends beyond OCR dimensions, scale target proportionally
|
||
scale_w = adjusted_ocr_width / ocr_width if ocr_width > 0 else 1.0
|
||
scale_h = adjusted_ocr_height / ocr_height if ocr_height > 0 else 1.0
|
||
adjusted_width = target_width * scale_w
|
||
adjusted_height = target_height * scale_h
|
||
else:
|
||
adjusted_width = target_width
|
||
adjusted_height = target_height
|
||
|
||
if needs_rotation or (adjusted_width != target_width or adjusted_height != target_height):
|
||
logger.info(f"頁面尺寸調整: {target_width:.1f}x{target_height:.1f} -> "
|
||
f"{adjusted_width:.1f}x{adjusted_height:.1f} (旋轉={needs_rotation})")
|
||
target_width, target_height = adjusted_width, adjusted_height
|
||
|
||
# Update original_page_sizes with the new TARGET dimensions
|
||
if 0 in original_page_sizes:
|
||
original_page_sizes[0] = (target_width, target_height)
|
||
logger.info(f"覆蓋原始文件尺寸以適應內容方向")
|
||
|
||
# CRITICAL: Update page_dimensions with SWAPPED OCR dimensions
|
||
# This is the coordinate system that the content bboxes are in
|
||
# When content is rotated, width and height are effectively swapped
|
||
if needs_rotation and 0 in page_dimensions:
|
||
# Swap the OCR dimensions to match the rotated content coordinate system
|
||
original_ocr_w = page_dimensions[0]['width']
|
||
original_ocr_h = page_dimensions[0]['height']
|
||
page_dimensions[0] = {'width': original_ocr_h, 'height': original_ocr_w}
|
||
logger.info(f"旋轉 OCR 座標系: {original_ocr_w:.1f}x{original_ocr_h:.1f} -> "
|
||
f"{original_ocr_h:.1f}x{original_ocr_w:.1f}")
|
||
|
||
# Create PDF canvas with initial page size (will be updated per page)
|
||
pdf_canvas = canvas.Canvas(str(output_path), pagesize=(target_width, target_height))
|
||
|
||
# LAYERED RENDERING: Exclude tables from regions_to_avoid
|
||
# Text inside tables will be rendered at raw OCR positions (via GapFillingService)
|
||
# while table borders are drawn separately using cell_boxes
|
||
# Only avoid overlap with actual images/figures/charts
|
||
regions_to_avoid = [img for img in images_metadata if img.get('type') != 'table']
|
||
table_count = len([img for img in images_metadata if img.get('type') == 'table'])
|
||
|
||
logger.info(f"過濾文字區域: {len(regions_to_avoid)} 個區域需要避免 (不含表格), {table_count} 個表格使用分層渲染")
|
||
|
||
filtered_text_regions = self._filter_text_in_regions(text_regions, regions_to_avoid)
|
||
|
||
# Group regions by page
|
||
pages_data = {}
|
||
for region in filtered_text_regions:
|
||
page_num = region.get('page', 1)
|
||
if page_num not in pages_data:
|
||
pages_data[page_num] = []
|
||
pages_data[page_num].append(region)
|
||
|
||
# Get table elements from layout_data
|
||
table_elements = []
|
||
if layout_data and layout_data.get('elements'):
|
||
table_elements = [e for e in layout_data['elements'] if e.get('type') == 'table']
|
||
|
||
# Process each page
|
||
total_pages = ocr_data.get('total_pages', 1)
|
||
logger.info(f"開始處理 {total_pages} 頁 PDF")
|
||
|
||
# Determine image directory
|
||
if json_parent_dir is None:
|
||
json_parent_dir = output_path.parent
|
||
|
||
for page_num in range(1, total_pages + 1):
|
||
logger.info(f">>> 處理第 {page_num}/{total_pages} 頁")
|
||
|
||
# Get current page dimensions with priority order:
|
||
# 1. Original file dimensions (highest priority)
|
||
# 2. OCR/UnifiedDocument dimensions
|
||
# 3. Fallback to first page dimensions
|
||
page_idx = page_num - 1
|
||
dimension_source = "unknown"
|
||
|
||
# Priority 1: Original file dimensions
|
||
if page_idx in original_page_sizes:
|
||
current_target_w, current_target_h = original_page_sizes[page_idx]
|
||
dimension_source = "original_file"
|
||
|
||
# Priority 2: OCR/UnifiedDocument dimensions (which may have been adjusted for orientation)
|
||
elif page_idx in page_dimensions:
|
||
current_page_dims = page_dimensions[page_idx]
|
||
current_target_w = float(current_page_dims['width'])
|
||
current_target_h = float(current_page_dims['height'])
|
||
dimension_source = "ocr_unified_doc"
|
||
|
||
# Priority 3: Fallback to first page
|
||
else:
|
||
current_target_w = ocr_width
|
||
current_target_h = ocr_height
|
||
dimension_source = "fallback_first_page"
|
||
logger.warning(f"No dimensions for page {page_num}, using first page size")
|
||
|
||
# For pages after the first, check if orientation adjustment is needed
|
||
# (First page was already handled above)
|
||
if page_num > 1 and dimension_source == "original_file":
|
||
# Build per-page data for orientation detection
|
||
page_ocr_data = {
|
||
'text_regions': [r for r in text_regions if r.get('page', 1) == page_num],
|
||
'layout_data': {
|
||
'elements': [e for e in layout_data.get('elements', [])
|
||
if e.get('page', 0) == page_idx]
|
||
},
|
||
'images_metadata': [i for i in images_metadata if i.get('page', 0) == page_idx]
|
||
}
|
||
needs_page_rotation, adj_w, adj_h = self._detect_content_orientation(
|
||
current_target_w, current_target_h, page_ocr_data
|
||
)
|
||
if needs_page_rotation or (adj_w != current_target_w or adj_h != current_target_h):
|
||
logger.info(f"第 {page_num} 頁尺寸調整: "
|
||
f"{current_target_w:.1f}x{current_target_h:.1f} -> "
|
||
f"{adj_w:.1f}x{adj_h:.1f}")
|
||
current_target_w, current_target_h = adj_w, adj_h
|
||
|
||
# Calculate scale factors for coordinate transformation
|
||
# OCR coordinates need to be scaled if original file dimensions differ
|
||
if dimension_source == "original_file":
|
||
# Get OCR dimensions for this page to calculate scale
|
||
if page_idx in page_dimensions:
|
||
ocr_page_w = float(page_dimensions[page_idx]['width'])
|
||
ocr_page_h = float(page_dimensions[page_idx]['height'])
|
||
else:
|
||
ocr_page_w = ocr_width
|
||
ocr_page_h = ocr_height
|
||
|
||
current_scale_w = current_target_w / ocr_page_w if ocr_page_w > 0 else 1.0
|
||
current_scale_h = current_target_h / ocr_page_h if ocr_page_h > 0 else 1.0
|
||
else:
|
||
# Using OCR/UnifiedDocument dimensions directly, no scaling needed
|
||
current_scale_w = 1.0
|
||
current_scale_h = 1.0
|
||
|
||
logger.info(f"第 {page_num} 頁尺寸: {current_target_w:.1f} x {current_target_h:.1f} "
|
||
f"(來源: {dimension_source}, 縮放: {current_scale_w:.3f}x{current_scale_h:.3f})")
|
||
|
||
if page_num > 1:
|
||
pdf_canvas.showPage()
|
||
|
||
# Set page size for current page
|
||
pdf_canvas.setPageSize((current_target_w, current_target_h))
|
||
|
||
# Get regions for this page
|
||
page_text_regions = pages_data.get(page_num, [])
|
||
page_table_regions = [t for t in table_elements if t.get('page') == page_num - 1]
|
||
page_image_regions = [
|
||
img for img in images_metadata
|
||
if img.get('page') == page_num - 1
|
||
and img.get('type') != 'table'
|
||
and img.get('image_path') is not None # Skip table placeholders
|
||
]
|
||
|
||
# Draw in layers: images → tables → text
|
||
|
||
# 1. Draw images (bottom layer)
|
||
for img_meta in page_image_regions:
|
||
self.draw_image_region(
|
||
pdf_canvas, img_meta, current_target_h,
|
||
json_parent_dir, current_scale_w, current_scale_h
|
||
)
|
||
|
||
# 2. Draw tables (middle layer)
|
||
for table_elem in page_table_regions:
|
||
self.draw_table_region(
|
||
pdf_canvas, table_elem, images_metadata,
|
||
current_target_h, current_scale_w, current_scale_h,
|
||
result_dir=json_parent_dir
|
||
)
|
||
|
||
# 3. Draw text (top layer)
|
||
for region in page_text_regions:
|
||
self.draw_text_region(
|
||
pdf_canvas, region, current_target_h,
|
||
current_scale_w, current_scale_h
|
||
)
|
||
|
||
logger.info(f"<<< 第 {page_num} 頁完成")
|
||
|
||
# Save PDF
|
||
pdf_canvas.save()
|
||
|
||
file_size = output_path.stat().st_size
|
||
logger.info(f"Generated PDF: {output_path.name} ({file_size} bytes)")
|
||
return True
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to generate PDF: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return False
|
||
|
||
def calculate_page_dimensions(self, ocr_data: Dict, source_file_path: Optional[Path] = None) -> Tuple[float, float]:
|
||
"""
|
||
從 OCR JSON 數據中取得頁面尺寸。
|
||
優先使用明確的 dimensions 欄位，失敗時才回退到 bbox 推斷。
|
||
|
||
Args:
|
||
ocr_data: Complete OCR data dictionary with text_regions and layout
|
||
source_file_path: Optional path to source file (fallback only)
|
||
|
||
Returns:
|
||
Tuple of (width, height) in points
|
||
"""
|
||
# *** 優先級 1: 檢查 ocr_dimensions (UnifiedDocument 轉換來的) ***
|
||
if 'ocr_dimensions' in ocr_data:
|
||
dims = ocr_data['ocr_dimensions']
|
||
# Handle both dict format {'width': w, 'height': h} and
|
||
# list format [{'page': 1, 'width': w, 'height': h}, ...]
|
||
if isinstance(dims, list) and len(dims) > 0:
|
||
dims = dims[0] # Use first page dimensions
|
||
if isinstance(dims, dict):
|
||
w = float(dims.get('width', 0))
|
||
h = float(dims.get('height', 0))
|
||
if w > 0 and h > 0:
|
||
logger.info(f"使用 ocr_dimensions 欄位的頁面尺寸: {w:.1f} x {h:.1f}")
|
||
return (w, h)
|
||
|
||
# *** 優先級 2: 檢查原始 JSON 的 dimensions ***
|
||
if 'dimensions' in ocr_data:
|
||
dims = ocr_data['dimensions']
|
||
w = float(dims.get('width', 0))
|
||
h = float(dims.get('height', 0))
|
||
if w > 0 and h > 0:
|
||
logger.info(f"使用 dimensions 欄位的頁面尺寸: {w:.1f} x {h:.1f}")
|
||
return (w, h)
|
||
|
||
# *** 優先級 3: Fallback - 從 bbox 推斷 (僅當上述皆缺失時使用) ***
|
||
logger.info("dimensions 欄位不可用，回退到 bbox 推斷")
|
||
max_x = 0
|
||
max_y = 0
|
||
|
||
# *** 關鍵修復：檢查所有可能包含 bbox 的字段 ***
|
||
# 不同版本的 OCR 輸出可能使用不同的字段名
|
||
all_regions = []
|
||
|
||
# 1. text_regions - 包含所有文字區域（最常見）
|
||
if 'text_regions' in ocr_data and isinstance(ocr_data['text_regions'], list):
|
||
all_regions.extend(ocr_data['text_regions'])
|
||
|
||
# 2. image_regions - 包含圖片區域
|
||
if 'image_regions' in ocr_data and isinstance(ocr_data['image_regions'], list):
|
||
all_regions.extend(ocr_data['image_regions'])
|
||
|
||
# 3. tables - 包含表格區域
|
||
if 'tables' in ocr_data and isinstance(ocr_data['tables'], list):
|
||
all_regions.extend(ocr_data['tables'])
|
||
|
||
# 4. layout - 可能包含布局信息（可能是空列表）
|
||
if 'layout' in ocr_data and isinstance(ocr_data['layout'], list):
|
||
all_regions.extend(ocr_data['layout'])
|
||
|
||
# 5. layout_data.elements - PP-StructureV3 格式
|
||
if 'layout_data' in ocr_data and isinstance(ocr_data['layout_data'], dict):
|
||
elements = ocr_data['layout_data'].get('elements', [])
|
||
if elements:
|
||
all_regions.extend(elements)
|
||
|
||
if not all_regions:
|
||
# 如果 JSON 為空，回退到原始檔案尺寸
|
||
logger.warning("JSON 中沒有找到 text_regions, image_regions, tables, layout 或 layout_data.elements，回退到原始檔案尺寸。")
|
||
if source_file_path:
|
||
dims = self.get_original_page_size(source_file_path)
|
||
if dims:
|
||
return dims
|
||
return A4
|
||
|
||
region_count = 0
|
||
for region in all_regions:
|
||
try:
|
||
bbox = region.get('bbox')
|
||
if not bbox:
|
||
continue
|
||
|
||
region_count += 1
|
||
|
||
# *** 關鍵修復：正確處理多邊形 [[x, y], ...] 格式 ***
|
||
if isinstance(bbox[0], (int, float)):
|
||
# 處理簡單的 [x1, y1, x2, y2] 格式
|
||
max_x = max(max_x, bbox[2])
|
||
max_y = max(max_y, bbox[3])
|
||
elif isinstance(bbox[0], (list, tuple)):
|
||
# 處理多邊形 [[x, y], ...] 格式
|
||
x_coords = [p[0] for p in bbox if isinstance(p, (list, tuple)) and len(p) >= 2]
|
||
y_coords = [p[1] for p in bbox if isinstance(p, (list, tuple)) and len(p) >= 2]
|
||
if x_coords and y_coords:
|
||
max_x = max(max_x, max(x_coords))
|
||
max_y = max(max_y, max(y_coords))
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Error processing bbox {bbox}: {e}")
|
||
|
||
if max_x > 0 and max_y > 0:
|
||
logger.info(f"從 {region_count} 個區域中推斷出的 OCR 座標系尺寸: {max_x:.1f} x {max_y:.1f}")
|
||
return (max_x, max_y)
|
||
else:
|
||
# 如果所有 bbox 都解析失敗，才回退
|
||
logger.warning("無法從 bbox 推斷尺寸，回退到原始檔案尺寸。")
|
||
if source_file_path:
|
||
dims = self.get_original_page_size(source_file_path)
|
||
if dims:
|
||
return dims
|
||
return A4
|
||
|
||
def get_all_page_sizes(self, file_path: Path) -> Dict[int, Tuple[float, float]]:
|
||
"""
|
||
Extract dimensions for all pages from original source file
|
||
|
||
Args:
|
||
file_path: Path to original file (image or PDF)
|
||
|
||
Returns:
|
||
Dict mapping page index (0-based) to (width, height) in points
|
||
Empty dict if extraction fails
|
||
"""
|
||
page_sizes = {}
|
||
|
||
try:
|
||
if not file_path.exists():
|
||
logger.warning(f"File not found: {file_path}")
|
||
return page_sizes
|
||
|
||
# For images, single page with dimensions from PIL
|
||
if file_path.suffix.lower() in ['.png', '.jpg', '.jpeg', '.bmp', '.tiff']:
|
||
img = Image.open(file_path)
|
||
# Use pixel dimensions directly as points (1:1 mapping)
|
||
# This matches how PaddleOCR reports coordinates
|
||
width_pt = float(img.width)
|
||
height_pt = float(img.height)
|
||
page_sizes[0] = (width_pt, height_pt)
|
||
logger.info(f"Extracted dimensions from image: {width_pt:.1f} x {height_pt:.1f} points (1:1 pixel mapping)")
|
||
return page_sizes
|
||
|
||
# For PDFs, extract dimensions for all pages using PyPDF2
|
||
if file_path.suffix.lower() == '.pdf':
|
||
try:
|
||
from PyPDF2 import PdfReader
|
||
reader = PdfReader(file_path)
|
||
total_pages = len(reader.pages)
|
||
|
||
for page_idx in range(total_pages):
|
||
page = reader.pages[page_idx]
|
||
# MediaBox gives [x1, y1, x2, y2] in points
|
||
mediabox = page.mediabox
|
||
width_pt = float(mediabox.width)
|
||
height_pt = float(mediabox.height)
|
||
|
||
# IMPORTANT: Consider page rotation!
|
||
# PDF pages can have /Rotate attribute (0, 90, 180, 270)
|
||
# When rotation is 90 or 270 degrees, width and height should be swapped
|
||
# because pdf2image and PDF viewers apply this rotation when rendering
|
||
rotation = page.get('/Rotate', 0)
|
||
if rotation is None:
|
||
rotation = 0
|
||
rotation = int(rotation) % 360
|
||
|
||
if rotation in (90, 270):
|
||
# Swap width and height for 90/270 degree rotation
|
||
width_pt, height_pt = height_pt, width_pt
|
||
logger.info(f"Page {page_idx}: Rotation={rotation}°, swapped dimensions to {width_pt:.1f} x {height_pt:.1f}")
|
||
|
||
page_sizes[page_idx] = (width_pt, height_pt)
|
||
|
||
logger.info(f"Extracted dimensions from PDF: {total_pages} pages")
|
||
for idx, (w, h) in page_sizes.items():
|
||
logger.debug(f" Page {idx}: {w:.1f} x {h:.1f} points")
|
||
|
||
return page_sizes
|
||
|
||
except ImportError:
|
||
logger.warning("PyPDF2 not available, cannot extract PDF dimensions")
|
||
except Exception as e:
|
||
logger.warning(f"Failed to extract PDF dimensions: {e}")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Failed to get page sizes from {file_path}: {e}")
|
||
|
||
return page_sizes
|
||
|
||
def get_original_page_size(self, file_path: Path) -> Optional[Tuple[float, float]]:
|
||
"""
|
||
Extract first page dimensions from original source file (backward compatibility)
|
||
|
||
Args:
|
||
file_path: Path to original file (image or PDF)
|
||
|
||
Returns:
|
||
Tuple of (width, height) in points or None
|
||
"""
|
||
page_sizes = self.get_all_page_sizes(file_path)
|
||
if 0 in page_sizes:
|
||
return page_sizes[0]
|
||
return None
|
||
|
||
def _get_bbox_coords(self, bbox: Union[Dict, List[List[float]], List[float]]) -> Optional[Tuple[float, float, float, float]]:
|
||
"""將任何 bbox 格式 (dict, 多邊形或 [x1,y1,x2,y2]) 轉換為 [x_min, y_min, x_max, y_max]"""
|
||
try:
|
||
if bbox is None:
|
||
return None
|
||
|
||
# Dict format from UnifiedDocument: {"x0": ..., "y0": ..., "x1": ..., "y1": ...}
|
||
if isinstance(bbox, dict):
|
||
if 'x0' in bbox and 'y0' in bbox and 'x1' in bbox and 'y1' in bbox:
|
||
return float(bbox['x0']), float(bbox['y0']), float(bbox['x1']), float(bbox['y1'])
|
||
else:
|
||
logger.warning(f"Dict bbox 缺少必要欄位: {bbox}")
|
||
return None
|
||
|
||
if not isinstance(bbox, (list, tuple)) or len(bbox) < 4:
|
||
return None
|
||
|
||
if isinstance(bbox[0], (list, tuple)):
|
||
# 處理多邊形 [[x, y], ...]
|
||
x_coords = [p[0] for p in bbox if isinstance(p, (list, tuple)) and len(p) >= 2]
|
||
y_coords = [p[1] for p in bbox if isinstance(p, (list, tuple)) and len(p) >= 2]
|
||
if not x_coords or not y_coords:
|
||
return None
|
||
return min(x_coords), min(y_coords), max(x_coords), max(y_coords)
|
||
elif isinstance(bbox[0], (int, float)) and len(bbox) == 4:
|
||
# 處理 [x1, y1, x2, y2]
|
||
return float(bbox[0]), float(bbox[1]), float(bbox[2]), float(bbox[3])
|
||
else:
|
||
logger.warning(f"未知的 bbox 格式: {bbox}")
|
||
return None
|
||
except Exception as e:
|
||
logger.error(f"解析 bbox {bbox} 時出錯: {e}")
|
||
return None
|
||
|
||
def _is_bbox_inside(self, inner_bbox_data: Dict, outer_bbox_data: Dict, tolerance: float = 5.0) -> bool:
|
||
"""
|
||
檢查 'inner_bbox' 是否在 'outer_bbox' 內部（帶有容錯）。
|
||
此版本可處理多邊形和矩形。
|
||
"""
|
||
inner_coords = self._get_bbox_coords(inner_bbox_data.get('bbox'))
|
||
outer_coords = self._get_bbox_coords(outer_bbox_data.get('bbox'))
|
||
|
||
if not inner_coords or not outer_coords:
|
||
return False
|
||
|
||
inner_x1, inner_y1, inner_x2, inner_y2 = inner_coords
|
||
outer_x1, outer_y1, outer_x2, outer_y2 = outer_coords
|
||
|
||
# 檢查 inner 是否在 outer 內部 (加入 tolerance)
|
||
is_inside = (
|
||
(inner_x1 >= outer_x1 - tolerance) and
|
||
(inner_y1 >= outer_y1 - tolerance) and
|
||
(inner_x2 <= outer_x2 + tolerance) and
|
||
(inner_y2 <= outer_y2 + tolerance)
|
||
)
|
||
return is_inside
|
||
|
||
def _bbox_overlaps(self, bbox1_data: Dict, bbox2_data: Dict, tolerance: float = 5.0) -> bool:
|
||
"""
|
||
檢查兩個 bbox 是否有重疊（帶有容錯）。
|
||
如果有任何重疊，返回 True。
|
||
|
||
Args:
|
||
bbox1_data: 第一個 bbox 數據
|
||
bbox2_data: 第二個 bbox 數據
|
||
tolerance: 容錯值（像素）
|
||
|
||
Returns:
|
||
True 如果兩個 bbox 有重疊
|
||
"""
|
||
coords1 = self._get_bbox_coords(bbox1_data.get('bbox'))
|
||
coords2 = self._get_bbox_coords(bbox2_data.get('bbox'))
|
||
|
||
if not coords1 or not coords2:
|
||
return False
|
||
|
||
x1_min, y1_min, x1_max, y1_max = coords1
|
||
x2_min, y2_min, x2_max, y2_max = coords2
|
||
|
||
# 擴展 bbox2（表格/圖片區域）的範圍
|
||
x2_min -= tolerance
|
||
y2_min -= tolerance
|
||
x2_max += tolerance
|
||
y2_max += tolerance
|
||
|
||
# 檢查是否有重疊：如果沒有重疊，則必定滿足以下條件之一
|
||
no_overlap = (
|
||
x1_max < x2_min or # bbox1 在 bbox2 左側
|
||
x1_min > x2_max or # bbox1 在 bbox2 右側
|
||
y1_max < y2_min or # bbox1 在 bbox2 上方
|
||
y1_min > y2_max # bbox1 在 bbox2 下方
|
||
)
|
||
|
||
return not no_overlap
|
||
|
||
def _calculate_overlap_ratio(self, text_bbox_data: Dict, avoid_bbox_data: Dict) -> float:
|
||
"""
|
||
計算文字區域與避免區域的重疊比例。
|
||
|
||
Args:
|
||
text_bbox_data: 文字區域 bbox 數據
|
||
avoid_bbox_data: 避免區域 bbox 數據
|
||
|
||
Returns:
|
||
重疊面積佔文字區域面積的比例 (0.0 - 1.0)
|
||
"""
|
||
text_coords = self._get_bbox_coords(text_bbox_data.get('bbox'))
|
||
avoid_coords = self._get_bbox_coords(avoid_bbox_data.get('bbox'))
|
||
|
||
if not text_coords or not avoid_coords:
|
||
return 0.0
|
||
|
||
tx0, ty0, tx1, ty1 = text_coords
|
||
ax0, ay0, ax1, ay1 = avoid_coords
|
||
|
||
# Calculate text area
|
||
text_area = (tx1 - tx0) * (ty1 - ty0)
|
||
if text_area <= 0:
|
||
return 0.0
|
||
|
||
# Calculate intersection
|
||
inter_x0 = max(tx0, ax0)
|
||
inter_y0 = max(ty0, ay0)
|
||
inter_x1 = min(tx1, ax1)
|
||
inter_y1 = min(ty1, ay1)
|
||
|
||
# Check if there's actual intersection
|
||
if inter_x1 <= inter_x0 or inter_y1 <= inter_y0:
|
||
return 0.0
|
||
|
||
inter_area = (inter_x1 - inter_x0) * (inter_y1 - inter_y0)
|
||
return inter_area / text_area
|
||
|
||
def _filter_text_in_regions(self, text_regions: List[Dict], regions_to_avoid: List[Dict], overlap_threshold: float = 0.5) -> List[Dict]:
|
||
"""
|
||
過濾掉與 'regions_to_avoid'（例如表格、圖片）顯著重疊的文字區域。
|
||
|
||
使用重疊比例閾值來判斷是否過濾，避免過濾掉僅相鄰但不重疊的文字。
|
||
|
||
Args:
|
||
text_regions: 文字區域列表
|
||
regions_to_avoid: 需要避免的區域列表（表格、圖片）
|
||
overlap_threshold: 重疊比例閾值 (0.0-1.0)，只有當文字區域
|
||
與避免區域的重疊比例超過此閾值時才會被過濾
|
||
預設 0.5 表示超過 50% 重疊才過濾
|
||
|
||
Returns:
|
||
過濾後的文字區域列表
|
||
"""
|
||
filtered_text = []
|
||
filtered_count = 0
|
||
|
||
for text_region in text_regions:
|
||
should_filter = False
|
||
max_overlap = 0.0
|
||
|
||
for avoid_region in regions_to_avoid:
|
||
# 計算重疊比例
|
||
overlap_ratio = self._calculate_overlap_ratio(text_region, avoid_region)
|
||
max_overlap = max(max_overlap, overlap_ratio)
|
||
|
||
# 只有當重疊比例超過閾值時才過濾
|
||
if overlap_ratio > overlap_threshold:
|
||
should_filter = True
|
||
filtered_count += 1
|
||
logger.debug(f"過濾掉重疊文字 (重疊比例: {overlap_ratio:.1%}): {text_region.get('text', '')[:30]}...")
|
||
break
|
||
|
||
if not should_filter:
|
||
filtered_text.append(text_region)
|
||
if max_overlap > 0:
|
||
logger.debug(f"保留文字 (最大重疊比例: {max_overlap:.1%}): {text_region.get('text', '')[:30]}...")
|
||
|
||
logger.info(f"原始文字區域: {len(text_regions)}, 過濾後: {len(filtered_text)}, 移除: {filtered_count}")
|
||
return filtered_text
|
||
|
||
def draw_text_region(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
region: Dict,
|
||
page_height: float,
|
||
scale_w: float = 1.0,
|
||
scale_h: float = 1.0
|
||
):
|
||
"""
|
||
Draw a text region at precise coordinates
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
region: Text region dict with text, bbox, confidence
|
||
page_height: Height of page (for coordinate transformation)
|
||
scale_w: Scale factor for X coordinates (PDF width / OCR width)
|
||
scale_h: Scale factor for Y coordinates (PDF height / OCR height)
|
||
"""
|
||
text = region.get('text', '')
|
||
bbox = region.get('bbox', [])
|
||
confidence = region.get('confidence', 1.0)
|
||
|
||
if not text or not bbox:
|
||
return
|
||
|
||
try:
|
||
# Handle different bbox formats
|
||
if isinstance(bbox, dict):
|
||
# Dict format from UnifiedDocument: {"x0": ..., "y0": ..., "x1": ..., "y1": ...}
|
||
if 'x0' in bbox and 'y0' in bbox and 'x1' in bbox and 'y1' in bbox:
|
||
ocr_x_left = float(bbox['x0'])
|
||
ocr_y_top = float(bbox['y0'])
|
||
ocr_x_right = float(bbox['x1'])
|
||
ocr_y_bottom = float(bbox['y1'])
|
||
else:
|
||
logger.warning(f"Dict bbox missing required keys: {bbox}")
|
||
return
|
||
elif isinstance(bbox, list):
|
||
if len(bbox) < 4:
|
||
return
|
||
# Polygon format [[x,y], [x,y], [x,y], [x,y]] (4 points)
|
||
if isinstance(bbox[0], list):
|
||
ocr_x_left = bbox[0][0] # Left X
|
||
ocr_y_top = bbox[0][1] # Top Y in OCR coordinates
|
||
ocr_x_right = bbox[2][0] # Right X
|
||
ocr_y_bottom = bbox[2][1] # Bottom Y in OCR coordinates
|
||
# Simple list format [x0, y0, x1, y1]
|
||
elif isinstance(bbox[0], (int, float)):
|
||
ocr_x_left = bbox[0]
|
||
ocr_y_top = bbox[1]
|
||
ocr_x_right = bbox[2]
|
||
ocr_y_bottom = bbox[3]
|
||
else:
|
||
logger.warning(f"Unexpected bbox list format: {bbox}")
|
||
return
|
||
else:
|
||
logger.warning(f"Invalid bbox format: {bbox}")
|
||
return
|
||
|
||
logger.info(f"[文字] '{text[:20]}...' OCR原始座標: L={ocr_x_left:.0f}, T={ocr_y_top:.0f}, R={ocr_x_right:.0f}, B={ocr_y_bottom:.0f}")
|
||
|
||
# Apply scale factors to convert from OCR space to PDF space
|
||
scaled_x_left = ocr_x_left * scale_w
|
||
scaled_y_top = ocr_y_top * scale_h
|
||
scaled_x_right = ocr_x_right * scale_w
|
||
scaled_y_bottom = ocr_y_bottom * scale_h
|
||
|
||
logger.info(f"[文字] '{text[:20]}...' 縮放後(scale={scale_w:.3f},{scale_h:.3f}): L={scaled_x_left:.1f}, T={scaled_y_top:.1f}, R={scaled_x_right:.1f}, B={scaled_y_bottom:.1f}")
|
||
|
||
# Calculate bbox dimensions (after scaling)
|
||
bbox_width = abs(scaled_x_right - scaled_x_left)
|
||
bbox_height = abs(scaled_y_bottom - scaled_y_top)
|
||
|
||
# Calculate font size using heuristics
|
||
# For multi-line text, divide bbox height by number of lines
|
||
lines = text.split('\n')
|
||
non_empty_lines = [l for l in lines if l.strip()]
|
||
num_lines = max(len(non_empty_lines), 1)
|
||
|
||
# Font size = bbox_height / num_lines * factor
|
||
# Use 0.8 factor to leave room for line spacing
|
||
font_size = (bbox_height / num_lines) * 0.8
|
||
font_size = max(min(font_size, 72), 4) # Clamp between 4pt and 72pt
|
||
|
||
logger.debug(f"Text has {num_lines} non-empty lines, bbox_height={bbox_height:.1f}, calculated font_size={font_size:.1f}")
|
||
|
||
# Transform coordinates: OCR (top-left origin) → PDF (bottom-left origin)
|
||
# CRITICAL: Y-axis flip!
|
||
# For multi-line text, start from TOP of bbox and go downward
|
||
pdf_x = scaled_x_left
|
||
pdf_y_top = page_height - scaled_y_top # Top of bbox in PDF coordinates
|
||
# Adjust for font baseline: first line starts below the top edge
|
||
pdf_y = pdf_y_top - font_size # Start first line one font size below top
|
||
|
||
logger.info(f"[文字] '{text[:30]}' → PDF位置: ({pdf_x:.1f}, {pdf_y:.1f}), 字體:{font_size:.1f}pt, 寬x高:{bbox_width:.0f}x{bbox_height:.0f}, 行數:{num_lines}")
|
||
|
||
# Set font with track-specific styling
|
||
style_info = region.get('style')
|
||
element_type = region.get('element_type', 'text')
|
||
is_direct_track = (self.current_processing_track == ProcessingTrack.DIRECT or
|
||
self.current_processing_track == ProcessingTrack.HYBRID)
|
||
|
||
if style_info and is_direct_track:
|
||
# Direct track: Apply rich styling from StyleInfo
|
||
self._apply_text_style(pdf_canvas, style_info, default_size=font_size)
|
||
# Get current font for width calculation
|
||
font_name = pdf_canvas._fontname
|
||
font_size = pdf_canvas._fontsize
|
||
logger.debug(f"Applied Direct track style: font={font_name}, size={font_size}")
|
||
else:
|
||
# OCR track or no style: Use simple font selection with element-type based styling
|
||
font_name = self.font_name if self.font_registered else 'Helvetica'
|
||
|
||
# Apply element-type specific styling (for OCR track)
|
||
if element_type == 'title':
|
||
# Titles: use larger, bold font
|
||
font_size = min(font_size * 1.3, 36) # 30% larger, max 36pt
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
logger.debug(f"Applied title style: size={font_size:.1f}")
|
||
elif element_type == 'header':
|
||
# Headers: slightly larger
|
||
font_size = min(font_size * 1.15, 24) # 15% larger, max 24pt
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
elif element_type == 'caption':
|
||
# Captions: slightly smaller, italic if available
|
||
font_size = max(font_size * 0.9, 6) # 10% smaller, min 6pt
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
else:
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
|
||
# Handle line breaks (split text by newlines)
|
||
# OCR track: simple left-aligned rendering
|
||
# Note: non_empty_lines was already calculated above for font sizing
|
||
line_height = font_size * 1.2 # 120% of font size for line spacing
|
||
|
||
# Draw each non-empty line (using proper line index for positioning)
|
||
for i, line in enumerate(non_empty_lines):
|
||
line_y = pdf_y - (i * line_height)
|
||
|
||
# Calculate text width to prevent overflow
|
||
text_width = pdf_canvas.stringWidth(line, font_name, font_size)
|
||
|
||
# If text is too wide for bbox, scale down font for this line
|
||
current_font_size = font_size
|
||
if text_width > bbox_width:
|
||
scale_factor = bbox_width / text_width
|
||
current_font_size = font_size * scale_factor * 0.95 # 95% to add small margin
|
||
current_font_size = max(current_font_size, 3) # Minimum 3pt
|
||
pdf_canvas.setFont(font_name, current_font_size)
|
||
|
||
# Draw text at left-aligned position (OCR track uses simple left alignment)
|
||
pdf_canvas.drawString(pdf_x, line_y, line)
|
||
|
||
# Reset font size for next line
|
||
if text_width > bbox_width:
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
|
||
# Debug: Draw bounding box (optional)
|
||
if settings.pdf_enable_bbox_debug:
|
||
pdf_canvas.setStrokeColorRGB(1, 0, 0, 0.3) # Red, semi-transparent
|
||
pdf_canvas.setLineWidth(0.5)
|
||
# Use already-extracted coordinates (works for all bbox formats)
|
||
# Draw rectangle using the scaled coordinates
|
||
pdf_x1 = ocr_x_left * scale_w
|
||
pdf_y1 = page_height - ocr_y_top * scale_h
|
||
pdf_x2 = ocr_x_right * scale_w
|
||
pdf_y2 = page_height - ocr_y_bottom * scale_h
|
||
# Draw bbox rectangle
|
||
pdf_canvas.line(pdf_x1, pdf_y1, pdf_x2, pdf_y1) # top
|
||
pdf_canvas.line(pdf_x2, pdf_y1, pdf_x2, pdf_y2) # right
|
||
pdf_canvas.line(pdf_x2, pdf_y2, pdf_x1, pdf_y2) # bottom
|
||
pdf_canvas.line(pdf_x1, pdf_y2, pdf_x1, pdf_y1) # left
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Failed to draw text region '{text[:20]}...': {e}")
|
||
|
||
def _compute_table_grid_from_cell_boxes(
|
||
self,
|
||
cell_boxes: List[List[float]],
|
||
table_bbox: List[float],
|
||
num_rows: int,
|
||
num_cols: int
|
||
) -> Tuple[Optional[List[float]], Optional[List[float]]]:
|
||
"""
|
||
Compute column widths and row heights from cell bounding boxes.
|
||
|
||
This uses the cell boxes extracted by SLANeXt to calculate the actual
|
||
column widths and row heights, which provides more accurate table rendering
|
||
than uniform distribution.
|
||
|
||
Args:
|
||
cell_boxes: List of cell bboxes [[x1,y1,x2,y2], ...]
|
||
table_bbox: Table bounding box [x1,y1,x2,y2]
|
||
num_rows: Number of rows in the table
|
||
num_cols: Number of columns in the table
|
||
|
||
Returns:
|
||
Tuple of (col_widths, row_heights) or (None, None) if calculation fails
|
||
"""
|
||
if not cell_boxes or len(cell_boxes) < 2:
|
||
return None, None
|
||
|
||
try:
|
||
table_x1, table_y1, table_x2, table_y2 = table_bbox
|
||
table_width = table_x2 - table_x1
|
||
table_height = table_y2 - table_y1
|
||
|
||
# Collect all unique X and Y boundaries from cell boxes
|
||
x_boundaries = set()
|
||
y_boundaries = set()
|
||
|
||
for box in cell_boxes:
|
||
if len(box) >= 4:
|
||
x1, y1, x2, y2 = box[:4]
|
||
# Convert to relative coordinates within table
|
||
x_boundaries.add(x1 - table_x1)
|
||
x_boundaries.add(x2 - table_x1)
|
||
y_boundaries.add(y1 - table_y1)
|
||
y_boundaries.add(y2 - table_y1)
|
||
|
||
# Sort boundaries
|
||
x_boundaries = sorted(x_boundaries)
|
||
y_boundaries = sorted(y_boundaries)
|
||
|
||
# Ensure we have boundaries at table edges
|
||
if x_boundaries and x_boundaries[0] > 5:
|
||
x_boundaries.insert(0, 0)
|
||
if x_boundaries and x_boundaries[-1] < table_width - 5:
|
||
x_boundaries.append(table_width)
|
||
|
||
if y_boundaries and y_boundaries[0] > 5:
|
||
y_boundaries.insert(0, 0)
|
||
if y_boundaries and y_boundaries[-1] < table_height - 5:
|
||
y_boundaries.append(table_height)
|
||
|
||
# Calculate column widths from X boundaries
|
||
# Merge boundaries that are too close (< 5px)
|
||
merged_x = [x_boundaries[0]] if x_boundaries else []
|
||
for x in x_boundaries[1:]:
|
||
if x - merged_x[-1] > 5:
|
||
merged_x.append(x)
|
||
x_boundaries = merged_x
|
||
|
||
# Calculate row heights from Y boundaries
|
||
merged_y = [y_boundaries[0]] if y_boundaries else []
|
||
for y in y_boundaries[1:]:
|
||
if y - merged_y[-1] > 5:
|
||
merged_y.append(y)
|
||
y_boundaries = merged_y
|
||
|
||
# Calculate widths and heights
|
||
col_widths = []
|
||
for i in range(len(x_boundaries) - 1):
|
||
col_widths.append(x_boundaries[i + 1] - x_boundaries[i])
|
||
|
||
row_heights = []
|
||
for i in range(len(y_boundaries) - 1):
|
||
row_heights.append(y_boundaries[i + 1] - y_boundaries[i])
|
||
|
||
# Validate: number of columns/rows should match expected
|
||
if len(col_widths) == num_cols and len(row_heights) == num_rows:
|
||
logger.info(f"[TABLE] Cell boxes grid: {num_cols} cols, {num_rows} rows")
|
||
logger.debug(f"[TABLE] Col widths from cell_boxes: {[f'{w:.1f}' for w in col_widths]}")
|
||
logger.debug(f"[TABLE] Row heights from cell_boxes: {[f'{h:.1f}' for h in row_heights]}")
|
||
return col_widths, row_heights
|
||
else:
|
||
# Grid doesn't match, might be due to merged cells
|
||
logger.debug(
|
||
f"[TABLE] Cell boxes grid mismatch: "
|
||
f"got {len(col_widths)}x{len(row_heights)}, expected {num_cols}x{num_rows}"
|
||
)
|
||
# Still return the widths/heights if counts are close
|
||
if abs(len(col_widths) - num_cols) <= 1 and abs(len(row_heights) - num_rows) <= 1:
|
||
# Adjust to match expected count
|
||
while len(col_widths) < num_cols:
|
||
col_widths.append(col_widths[-1] if col_widths else table_width / num_cols)
|
||
while len(col_widths) > num_cols:
|
||
col_widths.pop()
|
||
while len(row_heights) < num_rows:
|
||
row_heights.append(row_heights[-1] if row_heights else table_height / num_rows)
|
||
while len(row_heights) > num_rows:
|
||
row_heights.pop()
|
||
return col_widths, row_heights
|
||
|
||
return None, None
|
||
|
||
except Exception as e:
|
||
logger.warning(f"[TABLE] Failed to compute grid from cell boxes: {e}")
|
||
return None, None
|
||
|
||
def draw_table_region(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
table_element: Dict,
|
||
images_metadata: List[Dict],
|
||
page_height: float,
|
||
scale_w: float = 1.0,
|
||
scale_h: float = 1.0,
|
||
result_dir: Optional[Path] = None
|
||
):
|
||
"""
|
||
Draw a table region by parsing HTML and rebuilding with ReportLab Table
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
table_element: Table element dict with HTML content
|
||
images_metadata: List of image metadata to find table bbox
|
||
page_height: Height of page
|
||
scale_w: Scale factor for X coordinates (PDF width / OCR width)
|
||
scale_h: Scale factor for Y coordinates (PDF height / OCR height)
|
||
result_dir: Directory containing result files (for embedded images)
|
||
"""
|
||
try:
|
||
html_content = table_element.get('content', '')
|
||
if not html_content:
|
||
return
|
||
|
||
# Try to use cell_boxes for direct rendering first (more accurate)
|
||
cell_boxes = table_element.get('cell_boxes', [])
|
||
if cell_boxes:
|
||
logger.info(f"[TABLE] Using cell_boxes direct rendering ({len(cell_boxes)} cells)")
|
||
success = self._draw_table_with_cell_boxes(
|
||
pdf_canvas, table_element, page_height,
|
||
scale_w, scale_h, result_dir
|
||
)
|
||
if success:
|
||
return # Successfully rendered with cell_boxes
|
||
|
||
logger.info("[TABLE] Falling back to ReportLab Table")
|
||
|
||
# Fallback: Parse HTML to extract table structure and use ReportLab Table
|
||
parser = HTMLTableParser()
|
||
parser.feed(html_content)
|
||
|
||
if not parser.tables:
|
||
logger.warning("No tables found in HTML content")
|
||
return
|
||
|
||
# Get the first table (PP-StructureV3 usually provides one table per element)
|
||
table_data = parser.tables[0]
|
||
rows = table_data['rows']
|
||
|
||
if not rows:
|
||
return
|
||
|
||
# Get bbox directly from table element
|
||
table_bbox = table_element.get('bbox')
|
||
|
||
# If no bbox directly, check for bbox_polygon
|
||
if not table_bbox:
|
||
bbox_polygon = table_element.get('bbox_polygon')
|
||
if bbox_polygon and len(bbox_polygon) >= 4:
|
||
# Convert polygon format to simple bbox [x0, y0, x1, y1]
|
||
table_bbox = [
|
||
bbox_polygon[0][0], # x0
|
||
bbox_polygon[0][1], # y0
|
||
bbox_polygon[2][0], # x1
|
||
bbox_polygon[2][1] # y1
|
||
]
|
||
|
||
if not table_bbox:
|
||
logger.warning(f"No bbox found for table element")
|
||
return
|
||
|
||
# Handle different bbox formats
|
||
if isinstance(table_bbox, dict):
|
||
# Dict format from UnifiedDocument: {"x0": ..., "y0": ..., "x1": ..., "y1": ...}
|
||
if 'x0' in table_bbox and 'y0' in table_bbox and 'x1' in table_bbox and 'y1' in table_bbox:
|
||
ocr_x_left_raw = float(table_bbox['x0'])
|
||
ocr_y_top_raw = float(table_bbox['y0'])
|
||
ocr_x_right_raw = float(table_bbox['x1'])
|
||
ocr_y_bottom_raw = float(table_bbox['y1'])
|
||
else:
|
||
logger.error(f"Dict bbox missing required keys (x0, y0, x1, y1): {table_bbox}")
|
||
return
|
||
elif isinstance(table_bbox, list) and len(table_bbox) == 4:
|
||
# Simple bbox format [x0, y0, x1, y1]
|
||
if isinstance(table_bbox[0], (int, float)):
|
||
ocr_x_left_raw = table_bbox[0]
|
||
ocr_y_top_raw = table_bbox[1]
|
||
ocr_x_right_raw = table_bbox[2]
|
||
ocr_y_bottom_raw = table_bbox[3]
|
||
# Polygon format [[x,y], [x,y], [x,y], [x,y]]
|
||
elif isinstance(table_bbox[0], list):
|
||
ocr_x_left_raw = table_bbox[0][0]
|
||
ocr_y_top_raw = table_bbox[0][1]
|
||
ocr_x_right_raw = table_bbox[2][0]
|
||
ocr_y_bottom_raw = table_bbox[2][1]
|
||
else:
|
||
logger.error(f"Unexpected bbox format: {table_bbox}")
|
||
return
|
||
else:
|
||
logger.error(f"Invalid table_bbox format: {table_bbox}")
|
||
return
|
||
|
||
logger.info(f"[表格] OCR原始座標: L={ocr_x_left_raw:.0f}, T={ocr_y_top_raw:.0f}, R={ocr_x_right_raw:.0f}, B={ocr_y_bottom_raw:.0f}")
|
||
|
||
# Apply scaling
|
||
ocr_x_left = ocr_x_left_raw * scale_w
|
||
ocr_y_top = ocr_y_top_raw * scale_h
|
||
ocr_x_right = ocr_x_right_raw * scale_w
|
||
ocr_y_bottom = ocr_y_bottom_raw * scale_h
|
||
|
||
table_width = abs(ocr_x_right - ocr_x_left)
|
||
table_height = abs(ocr_y_bottom - ocr_y_top)
|
||
|
||
# Transform coordinates
|
||
pdf_x = ocr_x_left
|
||
pdf_y = page_height - ocr_y_bottom
|
||
|
||
# Build table data for ReportLab with proper colspan/rowspan handling
|
||
# First pass: determine the actual grid size by accounting for spans
|
||
num_rows = len(rows)
|
||
|
||
# Calculate actual number of columns by checking first row's total span
|
||
max_cols = 0
|
||
for row in rows:
|
||
row_cols = sum(cell.get('colspan', 1) for cell in row['cells'])
|
||
max_cols = max(max_cols, row_cols)
|
||
|
||
logger.info(f"[表格] {num_rows}行x{max_cols}列 → PDF位置: ({pdf_x:.1f}, {pdf_y:.1f}), 寬x高: {table_width:.0f}x{table_height:.0f}")
|
||
|
||
# Create a grid to track occupied cells (for rowspan handling)
|
||
# occupied[row][col] = True if cell is occupied by a span from above
|
||
occupied = [[False] * max_cols for _ in range(num_rows)]
|
||
|
||
# Build the 2D data array and collect span commands
|
||
reportlab_data = []
|
||
span_commands = []
|
||
|
||
for row_idx, row in enumerate(rows):
|
||
row_data = [''] * max_cols
|
||
col_idx = 0
|
||
|
||
for cell in row['cells']:
|
||
# Skip occupied cells (from rowspan above)
|
||
while col_idx < max_cols and occupied[row_idx][col_idx]:
|
||
col_idx += 1
|
||
|
||
if col_idx >= max_cols:
|
||
break
|
||
|
||
text = cell['text'].strip()
|
||
colspan = cell.get('colspan', 1)
|
||
rowspan = cell.get('rowspan', 1)
|
||
|
||
# Place text in the top-left cell of the span
|
||
row_data[col_idx] = text
|
||
|
||
# Mark cells as occupied for rowspan
|
||
for r in range(row_idx, min(row_idx + rowspan, num_rows)):
|
||
for c in range(col_idx, min(col_idx + colspan, max_cols)):
|
||
if r > row_idx or c > col_idx:
|
||
occupied[r][c] = True
|
||
|
||
# Add SPAN command if cell spans multiple rows/cols
|
||
if colspan > 1 or rowspan > 1:
|
||
span_end_col = min(col_idx + colspan - 1, max_cols - 1)
|
||
span_end_row = min(row_idx + rowspan - 1, num_rows - 1)
|
||
span_commands.append(('SPAN', (col_idx, row_idx), (span_end_col, span_end_row)))
|
||
|
||
col_idx += colspan
|
||
|
||
reportlab_data.append(row_data)
|
||
|
||
# Calculate column widths and row heights
|
||
# First, try to use cell_boxes if available for more accurate layout
|
||
cell_boxes = table_element.get('cell_boxes')
|
||
raw_table_bbox = [ocr_x_left_raw, ocr_y_top_raw, ocr_x_right_raw, ocr_y_bottom_raw]
|
||
|
||
computed_col_widths = None
|
||
computed_row_heights = None
|
||
|
||
if cell_boxes:
|
||
cell_boxes_source = table_element.get('cell_boxes_source', 'unknown')
|
||
logger.info(f"[TABLE] Using {len(cell_boxes)} cell boxes from {cell_boxes_source}")
|
||
computed_col_widths, computed_row_heights = self._compute_table_grid_from_cell_boxes(
|
||
cell_boxes, raw_table_bbox, num_rows, max_cols
|
||
)
|
||
|
||
# Use computed widths if available, otherwise fall back to equal distribution
|
||
if computed_col_widths:
|
||
# Scale col_widths to PDF coordinates
|
||
col_widths = [w * scale_w for w in computed_col_widths]
|
||
logger.info(f"[TABLE] Using cell_boxes col widths (scaled)")
|
||
else:
|
||
col_widths = [table_width / max_cols] * max_cols
|
||
logger.info(f"[TABLE] Using equal distribution col widths: {table_width/max_cols:.1f} each")
|
||
|
||
# Row heights - ALWAYS use to ensure table fits bbox properly
|
||
# Use computed heights from cell_boxes, or uniform distribution as fallback
|
||
if computed_row_heights:
|
||
# Scale row_heights to PDF coordinates
|
||
row_heights = [h * scale_h for h in computed_row_heights]
|
||
logger.info(f"[TABLE] Using cell_boxes row heights (scaled)")
|
||
else:
|
||
# Uniform distribution based on table bbox - ensures table fills its allocated space
|
||
row_heights = [table_height / num_rows] * num_rows
|
||
logger.info(f"[TABLE] Using uniform row heights: {table_height/num_rows:.1f} each")
|
||
|
||
# Create ReportLab Table
|
||
# Use smaller font to fit content with auto-wrap
|
||
font_size = 8 # Fixed reasonable font size for table content
|
||
|
||
# Create paragraph style for text wrapping in cells
|
||
cell_style = ParagraphStyle(
|
||
'CellStyle',
|
||
fontName=self.font_name if self.font_registered else 'Helvetica',
|
||
fontSize=font_size,
|
||
leading=font_size * 1.2,
|
||
alignment=TA_CENTER,
|
||
wordWrap='CJK', # Better wrapping for Chinese text
|
||
)
|
||
|
||
# Convert text to Paragraph objects for auto-wrapping
|
||
for row_idx, row_data in enumerate(reportlab_data):
|
||
for col_idx, cell_text in enumerate(row_data):
|
||
if cell_text:
|
||
# Escape HTML special characters and create Paragraph
|
||
escaped_text = cell_text.replace('&', '&').replace('<', '<').replace('>', '>')
|
||
reportlab_data[row_idx][col_idx] = Paragraph(escaped_text, cell_style)
|
||
|
||
# Create table with col widths and row heights
|
||
# Always use row_heights to ensure table fits bbox properly
|
||
table = Table(reportlab_data, colWidths=col_widths, rowHeights=row_heights)
|
||
logger.info(f"[TABLE] Created with {len(col_widths)} cols, {len(row_heights)} rows")
|
||
|
||
# Apply table style
|
||
style = TableStyle([
|
||
('FONT', (0, 0), (-1, -1), self.font_name if self.font_registered else 'Helvetica', font_size),
|
||
('GRID', (0, 0), (-1, -1), 0.5, colors.black),
|
||
('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),
|
||
('ALIGN', (0, 0), (-1, -1), 'CENTER'),
|
||
('LEFTPADDING', (0, 0), (-1, -1), 2),
|
||
('RIGHTPADDING', (0, 0), (-1, -1), 2),
|
||
('TOPPADDING', (0, 0), (-1, -1), 2),
|
||
('BOTTOMPADDING', (0, 0), (-1, -1), 2),
|
||
])
|
||
|
||
# Add header style if first row has headers
|
||
if rows and rows[0]['cells'] and rows[0]['cells'][0].get('is_header'):
|
||
style.add('BACKGROUND', (0, 0), (-1, 0), colors.lightgrey)
|
||
style.add('FONT', (0, 0), (-1, 0), self.font_name if self.font_registered else 'Helvetica-Bold', font_size)
|
||
|
||
# Add span commands for merged cells
|
||
for span_cmd in span_commands:
|
||
style.add(*span_cmd)
|
||
|
||
table.setStyle(style)
|
||
|
||
logger.info(f"[表格] 套用 {len(span_commands)} 個合併儲存格 (SPAN)")
|
||
|
||
# Calculate actual table size after wrapping
|
||
actual_width, actual_height = table.wrapOn(pdf_canvas, table_width, table_height)
|
||
|
||
logger.info(f"[表格] 目標尺寸: {table_width:.0f}x{table_height:.0f}, 實際尺寸: {actual_width:.0f}x{actual_height:.0f}")
|
||
|
||
# Scale table to fit bbox if it exceeds the target size
|
||
scale_x = table_width / actual_width if actual_width > table_width else 1.0
|
||
scale_y = table_height / actual_height if actual_height > table_height else 1.0
|
||
scale_factor = min(scale_x, scale_y) # Use smaller scale to fit both dimensions
|
||
|
||
# Calculate the table top position in PDF coordinates
|
||
# ReportLab uses bottom-left origin, so we need to position from TOP
|
||
pdf_y_top = page_height - ocr_y_top # Top of table in PDF coords
|
||
|
||
# Calculate the actual bottom position based on scaled height
|
||
# Table should be positioned so its TOP aligns with the bbox top
|
||
scaled_height = actual_height * scale_factor
|
||
pdf_y_bottom = pdf_y_top - scaled_height # Bottom of scaled table
|
||
|
||
logger.info(f"[表格] PDF座標: top={pdf_y_top:.0f}, bottom={pdf_y_bottom:.0f}, scaled_height={scaled_height:.0f}")
|
||
|
||
if scale_factor < 1.0:
|
||
logger.info(f"[表格] 縮放比例: {scale_factor:.2f} (需要縮小以適應 bbox)")
|
||
# Apply scaling transformation
|
||
pdf_canvas.saveState()
|
||
pdf_canvas.translate(pdf_x, pdf_y_bottom)
|
||
pdf_canvas.scale(scale_factor, scale_factor)
|
||
# Draw at origin since we've already translated
|
||
table.drawOn(pdf_canvas, 0, 0)
|
||
pdf_canvas.restoreState()
|
||
else:
|
||
# Draw table at position without scaling
|
||
# pdf_y should be the bottom of the table
|
||
table.drawOn(pdf_canvas, pdf_x, pdf_y_bottom)
|
||
|
||
logger.info(f"Drew table at ({pdf_x:.0f}, {pdf_y_bottom:.0f}) size {table_width:.0f}x{scaled_height:.0f} with {len(rows)} rows")
|
||
|
||
# Draw embedded images (images detected inside the table region)
|
||
embedded_images = table_element.get('embedded_images', [])
|
||
if embedded_images and result_dir:
|
||
logger.info(f"[TABLE] Drawing {len(embedded_images)} embedded images")
|
||
for emb_img in embedded_images:
|
||
self._draw_embedded_image(
|
||
pdf_canvas, emb_img, page_height, result_dir, scale_w, scale_h
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Failed to draw table region: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
|
||
def _draw_embedded_image(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
emb_img: Dict,
|
||
page_height: float,
|
||
result_dir: Path,
|
||
scale_w: float = 1.0,
|
||
scale_h: float = 1.0
|
||
):
|
||
"""Draw an embedded image inside a table region."""
|
||
try:
|
||
# Get image path
|
||
saved_path = emb_img.get('saved_path', '')
|
||
if not saved_path:
|
||
return
|
||
|
||
# Construct full path
|
||
image_path = result_dir / saved_path
|
||
if not image_path.exists():
|
||
image_path = result_dir / Path(saved_path).name
|
||
|
||
if not image_path.exists():
|
||
logger.warning(f"Embedded image not found: {saved_path}")
|
||
return
|
||
|
||
# Get bbox from embedded image data
|
||
bbox = emb_img.get('bbox', [])
|
||
if not bbox or len(bbox) < 4:
|
||
logger.warning(f"No bbox for embedded image: {saved_path}")
|
||
return
|
||
|
||
# Calculate position (bbox is [x0, y0, x1, y1])
|
||
x0, y0, x1, y1 = bbox[0], bbox[1], bbox[2], bbox[3]
|
||
|
||
# Apply scaling
|
||
x0_scaled = x0 * scale_w
|
||
y0_scaled = y0 * scale_h
|
||
x1_scaled = x1 * scale_w
|
||
y1_scaled = y1 * scale_h
|
||
|
||
width = x1_scaled - x0_scaled
|
||
height = y1_scaled - y0_scaled
|
||
|
||
# Transform Y coordinate (ReportLab uses bottom-left origin)
|
||
pdf_x = x0_scaled
|
||
pdf_y = page_height - y1_scaled
|
||
|
||
# Draw the image
|
||
from reportlab.lib.utils import ImageReader
|
||
img_reader = ImageReader(str(image_path))
|
||
pdf_canvas.drawImage(
|
||
img_reader, pdf_x, pdf_y, width, height,
|
||
preserveAspectRatio=True, mask='auto'
|
||
)
|
||
|
||
logger.info(f"Drew embedded image at ({pdf_x:.0f}, {pdf_y:.0f}) size {width:.0f}x{height:.0f}")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Failed to draw embedded image: {e}")
|
||
|
||
def _normalize_cell_boxes_to_grid(
|
||
self,
|
||
cell_boxes: List[List[float]],
|
||
threshold: float = 10.0
|
||
) -> List[List[float]]:
|
||
"""
|
||
Normalize cell boxes to create a proper aligned grid.
|
||
|
||
Groups nearby coordinates and snaps them to a common value,
|
||
eliminating the 2-11 pixel variations that cause skewed tables.
|
||
|
||
Args:
|
||
cell_boxes: List of cell bboxes [[x1,y1,x2,y2], ...]
|
||
threshold: Maximum distance to consider coordinates as "same line"
|
||
|
||
Returns:
|
||
Normalized cell_boxes with aligned coordinates
|
||
"""
|
||
if not cell_boxes or len(cell_boxes) < 2:
|
||
return cell_boxes
|
||
|
||
# Collect all X and Y coordinates
|
||
x_coords = [] # (value, box_idx, is_x1)
|
||
y_coords = [] # (value, box_idx, is_y1)
|
||
|
||
for i, box in enumerate(cell_boxes):
|
||
x1, y1, x2, y2 = box[0], box[1], box[2], box[3]
|
||
x_coords.append((x1, i, True)) # x1 (left)
|
||
x_coords.append((x2, i, False)) # x2 (right)
|
||
y_coords.append((y1, i, True)) # y1 (top)
|
||
y_coords.append((y2, i, False)) # y2 (bottom)
|
||
|
||
def cluster_and_normalize(coords, threshold):
|
||
"""Cluster nearby coordinates and return mapping to normalized values."""
|
||
if not coords:
|
||
return {}
|
||
|
||
# Sort by value
|
||
sorted_coords = sorted(coords, key=lambda x: x[0])
|
||
|
||
# Cluster nearby values
|
||
clusters = []
|
||
current_cluster = [sorted_coords[0]]
|
||
|
||
for coord in sorted_coords[1:]:
|
||
if coord[0] - current_cluster[-1][0] <= threshold:
|
||
current_cluster.append(coord)
|
||
else:
|
||
clusters.append(current_cluster)
|
||
current_cluster = [coord]
|
||
clusters.append(current_cluster)
|
||
|
||
# Create mapping: (box_idx, is_first) -> normalized value
|
||
mapping = {}
|
||
for cluster in clusters:
|
||
# Use average of cluster as normalized value
|
||
avg_value = sum(c[0] for c in cluster) / len(cluster)
|
||
for _, box_idx, is_first in cluster:
|
||
mapping[(box_idx, is_first)] = avg_value
|
||
|
||
return mapping
|
||
|
||
x_mapping = cluster_and_normalize(x_coords, threshold)
|
||
y_mapping = cluster_and_normalize(y_coords, threshold)
|
||
|
||
# Create normalized cell boxes
|
||
normalized_boxes = []
|
||
for i, box in enumerate(cell_boxes):
|
||
x1_norm = x_mapping.get((i, True), box[0])
|
||
x2_norm = x_mapping.get((i, False), box[2])
|
||
y1_norm = y_mapping.get((i, True), box[1])
|
||
y2_norm = y_mapping.get((i, False), box[3])
|
||
normalized_boxes.append([x1_norm, y1_norm, x2_norm, y2_norm])
|
||
|
||
logger.debug(f"[TABLE] Normalized {len(cell_boxes)} cell boxes to grid")
|
||
return normalized_boxes
|
||
|
||
def _draw_table_with_cell_boxes(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
table_element: Dict,
|
||
page_height: float,
|
||
scale_w: float = 1.0,
|
||
scale_h: float = 1.0,
|
||
result_dir: Optional[Path] = None
|
||
):
|
||
"""
|
||
Draw table borders using cell_boxes for accurate positioning.
|
||
|
||
LAYERED RENDERING APPROACH:
|
||
- This method ONLY draws cell borders and embedded images
|
||
- Text is rendered separately using raw OCR positions (via GapFillingService)
|
||
- This decouples visual structure (borders) from content (text)
|
||
|
||
FALLBACK: If cell_boxes are incomplete, always draws the outer table
|
||
border using the table's bbox to ensure table boundaries are visible.
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
table_element: Table element dict with cell_boxes
|
||
page_height: Height of page in PDF coordinates
|
||
scale_w: Scale factor for X coordinates
|
||
scale_h: Scale factor for Y coordinates
|
||
result_dir: Directory containing result files (for embedded images)
|
||
"""
|
||
try:
|
||
cell_boxes = table_element.get('cell_boxes', [])
|
||
|
||
# Always draw outer table border first (fallback for incomplete cell_boxes)
|
||
table_bbox = table_element.get('bbox', [])
|
||
if table_bbox and len(table_bbox) >= 4:
|
||
# Handle different bbox formats (list or dict)
|
||
if isinstance(table_bbox, dict):
|
||
tx1 = float(table_bbox.get('x0', 0))
|
||
ty1 = float(table_bbox.get('y0', 0))
|
||
tx2 = float(table_bbox.get('x1', 0))
|
||
ty2 = float(table_bbox.get('y1', 0))
|
||
else:
|
||
tx1, ty1, tx2, ty2 = table_bbox[:4]
|
||
|
||
# Apply scaling
|
||
tx1_scaled = tx1 * scale_w
|
||
ty1_scaled = ty1 * scale_h
|
||
tx2_scaled = tx2 * scale_w
|
||
ty2_scaled = ty2 * scale_h
|
||
|
||
table_width = tx2_scaled - tx1_scaled
|
||
table_height = ty2_scaled - ty1_scaled
|
||
|
||
# Transform Y coordinate (PDF uses bottom-left origin)
|
||
pdf_x = tx1_scaled
|
||
pdf_y = page_height - ty2_scaled # Bottom of table in PDF coords
|
||
|
||
# Draw outer table border (slightly thicker for visibility)
|
||
pdf_canvas.setStrokeColor(colors.black)
|
||
pdf_canvas.setLineWidth(1.0)
|
||
pdf_canvas.rect(pdf_x, pdf_y, table_width, table_height, stroke=1, fill=0)
|
||
logger.info(f"[TABLE] Drew outer table border at [{int(tx1)},{int(ty1)},{int(tx2)},{int(ty2)}]")
|
||
|
||
if not cell_boxes:
|
||
logger.warning("[TABLE] No cell_boxes available, only outer border drawn")
|
||
# Still draw embedded images even without cell borders
|
||
embedded_images = table_element.get('embedded_images', [])
|
||
if embedded_images and result_dir:
|
||
for emb_img in embedded_images:
|
||
self._draw_embedded_image(
|
||
pdf_canvas, emb_img, page_height, result_dir, scale_w, scale_h
|
||
)
|
||
return True # Outer border drawn successfully
|
||
|
||
# Normalize cell boxes to create aligned grid
|
||
cell_boxes = self._normalize_cell_boxes_to_grid(cell_boxes)
|
||
|
||
logger.info(f"[TABLE] Drawing {len(cell_boxes)} cell borders (layered mode, grid-aligned)")
|
||
|
||
# Draw each cell border
|
||
for box in cell_boxes:
|
||
x1, y1, x2, y2 = box[0], box[1], box[2], box[3]
|
||
|
||
# Apply scaling
|
||
x1_scaled = x1 * scale_w
|
||
y1_scaled = y1 * scale_h
|
||
x2_scaled = x2 * scale_w
|
||
y2_scaled = y2 * scale_h
|
||
|
||
cell_width = x2_scaled - x1_scaled
|
||
cell_height = y2_scaled - y1_scaled
|
||
|
||
# Transform Y coordinate (PDF uses bottom-left origin)
|
||
pdf_x = x1_scaled
|
||
pdf_y = page_height - y2_scaled # Bottom of cell in PDF coords
|
||
|
||
# Draw cell border only (no fill, no text)
|
||
pdf_canvas.setStrokeColor(colors.black)
|
||
pdf_canvas.setLineWidth(0.5)
|
||
pdf_canvas.rect(pdf_x, pdf_y, cell_width, cell_height, stroke=1, fill=0)
|
||
|
||
logger.info(f"[TABLE] Drew {len(cell_boxes)} cell borders")
|
||
|
||
# Draw embedded images
|
||
embedded_images = table_element.get('embedded_images', [])
|
||
if embedded_images and result_dir:
|
||
logger.info(f"[TABLE] Drawing {len(embedded_images)} embedded images")
|
||
for emb_img in embedded_images:
|
||
self._draw_embedded_image(
|
||
pdf_canvas, emb_img, page_height, result_dir, scale_w, scale_h
|
||
)
|
||
|
||
return True
|
||
|
||
except Exception as e:
|
||
logger.warning(f"[TABLE] Failed to draw cell borders: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return False
|
||
|
||
def draw_image_region(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
region: Dict,
|
||
page_height: float,
|
||
result_dir: Path,
|
||
scale_w: float = 1.0,
|
||
scale_h: float = 1.0
|
||
):
|
||
"""
|
||
Draw an image region by embedding the extracted image
|
||
|
||
Handles images extracted by PP-StructureV3 (tables, figures, charts, etc.)
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
region: Image metadata dict with image_path and bbox
|
||
page_height: Height of page (for coordinate transformation)
|
||
result_dir: Directory containing result files
|
||
scale_w: Scale factor for X coordinates (PDF width / OCR width)
|
||
scale_h: Scale factor for Y coordinates (PDF height / OCR height)
|
||
"""
|
||
try:
|
||
image_path_str = region.get('image_path', '')
|
||
if not image_path_str:
|
||
return
|
||
|
||
# Construct full path to image
|
||
# saved_path is relative to result_dir (e.g., "imgs/element_id.png")
|
||
image_path = result_dir / image_path_str
|
||
|
||
# Fallback for legacy data
|
||
if not image_path.exists():
|
||
image_path = result_dir / Path(image_path_str).name
|
||
|
||
if not image_path.exists():
|
||
logger.warning(f"Image not found: {image_path_str} (in {result_dir})")
|
||
return
|
||
|
||
# Get bbox for positioning
|
||
bbox = region.get('bbox', [])
|
||
if not bbox:
|
||
logger.warning(f"No bbox for image {image_path_str}")
|
||
return
|
||
|
||
# Handle different bbox formats
|
||
if isinstance(bbox, dict):
|
||
# Dict format from UnifiedDocument: {"x0": ..., "y0": ..., "x1": ..., "y1": ...}
|
||
if 'x0' in bbox and 'y0' in bbox and 'x1' in bbox and 'y1' in bbox:
|
||
ocr_x_left_raw = float(bbox['x0'])
|
||
ocr_y_top_raw = float(bbox['y0'])
|
||
ocr_x_right_raw = float(bbox['x1'])
|
||
ocr_y_bottom_raw = float(bbox['y1'])
|
||
else:
|
||
logger.warning(f"Dict bbox missing required keys for image: {bbox}")
|
||
return
|
||
elif isinstance(bbox, list):
|
||
if len(bbox) < 4:
|
||
logger.warning(f"List bbox too short for image: {bbox}")
|
||
return
|
||
# Polygon format [[x,y], [x,y], [x,y], [x,y]]
|
||
if isinstance(bbox[0], list):
|
||
ocr_x_left_raw = bbox[0][0]
|
||
ocr_y_top_raw = bbox[0][1]
|
||
ocr_x_right_raw = bbox[2][0]
|
||
ocr_y_bottom_raw = bbox[2][1]
|
||
# Simple list format [x0, y0, x1, y1]
|
||
elif isinstance(bbox[0], (int, float)):
|
||
ocr_x_left_raw = bbox[0]
|
||
ocr_y_top_raw = bbox[1]
|
||
ocr_x_right_raw = bbox[2]
|
||
ocr_y_bottom_raw = bbox[3]
|
||
else:
|
||
logger.warning(f"Unexpected bbox list format for image: {bbox}")
|
||
return
|
||
else:
|
||
logger.warning(f"Invalid bbox format for image: {bbox}")
|
||
return
|
||
|
||
logger.info(f"[圖片] '{image_path_str}' OCR原始座標: L={ocr_x_left_raw:.0f}, T={ocr_y_top_raw:.0f}, R={ocr_x_right_raw:.0f}, B={ocr_y_bottom_raw:.0f}")
|
||
|
||
# Apply scaling
|
||
ocr_x_left = ocr_x_left_raw * scale_w
|
||
ocr_y_top = ocr_y_top_raw * scale_h
|
||
ocr_x_right = ocr_x_right_raw * scale_w
|
||
ocr_y_bottom = ocr_y_bottom_raw * scale_h
|
||
|
||
# Calculate bbox dimensions (after scaling)
|
||
bbox_width = abs(ocr_x_right - ocr_x_left)
|
||
bbox_height = abs(ocr_y_bottom - ocr_y_top)
|
||
|
||
# Transform coordinates: OCR (top-left origin) → PDF (bottom-left origin)
|
||
# CRITICAL: Y-axis flip!
|
||
# For images, we position at bottom-left corner
|
||
pdf_x_left = ocr_x_left
|
||
pdf_y_bottom = page_height - ocr_y_bottom # Flip Y-axis
|
||
|
||
logger.info(f"[圖片] '{image_path_str}' → PDF位置: ({pdf_x_left:.1f}, {pdf_y_bottom:.1f}), 寬x高: {bbox_width:.0f}x{bbox_height:.0f}")
|
||
|
||
# Draw image using ReportLab
|
||
# drawImage expects: (path, x, y, width, height)
|
||
# where (x, y) is the bottom-left corner of the image
|
||
pdf_canvas.drawImage(
|
||
str(image_path),
|
||
pdf_x_left,
|
||
pdf_y_bottom,
|
||
width=bbox_width,
|
||
height=bbox_height,
|
||
preserveAspectRatio=True,
|
||
mask='auto' # Handle transparency
|
||
)
|
||
|
||
logger.info(f"[圖片] ✓ 成功繪製 '{image_path_str}'")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Failed to draw image region: {e}")
|
||
|
||
def generate_layout_pdf(
|
||
self,
|
||
json_path: Path,
|
||
output_path: Path,
|
||
source_file_path: Optional[Path] = None
|
||
) -> bool:
|
||
"""
|
||
Generate layout-preserving PDF from OCR JSON data
|
||
|
||
Args:
|
||
json_path: Path to OCR JSON file
|
||
output_path: Path to save generated PDF
|
||
source_file_path: Optional path to original source file for dimension extraction
|
||
|
||
Returns:
|
||
True if successful, False otherwise
|
||
"""
|
||
try:
|
||
# Load JSON data
|
||
ocr_data = self.load_ocr_json(json_path)
|
||
if not ocr_data:
|
||
return False
|
||
|
||
# Check if this is new UnifiedDocument format (has 'pages' with elements)
|
||
# vs old OCR format (has 'text_regions')
|
||
if 'pages' in ocr_data and isinstance(ocr_data.get('pages'), list):
|
||
# New UnifiedDocument format - convert and use Direct track rendering
|
||
logger.info("Detected UnifiedDocument JSON format, using Direct track rendering")
|
||
unified_doc = self._json_to_unified_document(ocr_data, json_path.parent)
|
||
if unified_doc:
|
||
return self.generate_from_unified_document(
|
||
unified_doc=unified_doc,
|
||
output_path=output_path,
|
||
source_file_path=source_file_path
|
||
)
|
||
else:
|
||
logger.error("Failed to convert JSON to UnifiedDocument")
|
||
return False
|
||
else:
|
||
# Old OCR format - use legacy generation
|
||
logger.info("Detected legacy OCR JSON format, using OCR track rendering")
|
||
return self._generate_pdf_from_data(
|
||
ocr_data=ocr_data,
|
||
output_path=output_path,
|
||
source_file_path=source_file_path,
|
||
json_parent_dir=json_path.parent
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to generate PDF: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return False
|
||
|
||
def _json_to_unified_document(self, json_data: Dict, result_dir: Path) -> Optional['UnifiedDocument']:
|
||
"""
|
||
Convert JSON dict to UnifiedDocument object.
|
||
|
||
Args:
|
||
json_data: Loaded JSON dictionary in UnifiedDocument format
|
||
result_dir: Directory containing image files
|
||
|
||
Returns:
|
||
UnifiedDocument object or None if conversion fails
|
||
"""
|
||
try:
|
||
from datetime import datetime
|
||
|
||
# Parse metadata
|
||
metadata_dict = json_data.get('metadata', {})
|
||
|
||
# Parse processing track
|
||
track_str = metadata_dict.get('processing_track', 'direct')
|
||
try:
|
||
processing_track = ProcessingTrack(track_str)
|
||
except ValueError:
|
||
processing_track = ProcessingTrack.DIRECT
|
||
|
||
# Create DocumentMetadata
|
||
metadata = DocumentMetadata(
|
||
filename=metadata_dict.get('filename', ''),
|
||
file_type=metadata_dict.get('file_type', 'pdf'),
|
||
file_size=metadata_dict.get('file_size', 0),
|
||
created_at=datetime.fromisoformat(metadata_dict.get('created_at', datetime.now().isoformat()).replace('Z', '+00:00')),
|
||
processing_track=processing_track,
|
||
processing_time=metadata_dict.get('processing_time', 0),
|
||
language=metadata_dict.get('language'),
|
||
title=metadata_dict.get('title'),
|
||
author=metadata_dict.get('author'),
|
||
subject=metadata_dict.get('subject'),
|
||
keywords=metadata_dict.get('keywords'),
|
||
producer=metadata_dict.get('producer'),
|
||
creator=metadata_dict.get('creator'),
|
||
creation_date=datetime.fromisoformat(metadata_dict['creation_date'].replace('Z', '+00:00')) if metadata_dict.get('creation_date') else None,
|
||
modification_date=datetime.fromisoformat(metadata_dict['modification_date'].replace('Z', '+00:00')) if metadata_dict.get('modification_date') else None,
|
||
)
|
||
|
||
# Parse pages
|
||
pages = []
|
||
for page_dict in json_data.get('pages', []):
|
||
# Parse page dimensions
|
||
dims = page_dict.get('dimensions', {})
|
||
if not dims:
|
||
# Fallback dimensions
|
||
dims = {'width': 595.32, 'height': 841.92}
|
||
dimensions = Dimensions(
|
||
width=dims.get('width', 595.32),
|
||
height=dims.get('height', 841.92),
|
||
dpi=dims.get('dpi')
|
||
)
|
||
|
||
# Parse elements
|
||
elements = []
|
||
for elem_dict in page_dict.get('elements', []):
|
||
element = self._json_to_document_element(elem_dict)
|
||
if element:
|
||
elements.append(element)
|
||
|
||
page = Page(
|
||
page_number=page_dict.get('page_number', 1),
|
||
dimensions=dimensions,
|
||
elements=elements,
|
||
metadata=page_dict.get('metadata', {})
|
||
)
|
||
pages.append(page)
|
||
|
||
# Create UnifiedDocument
|
||
unified_doc = UnifiedDocument(
|
||
document_id=json_data.get('document_id', ''),
|
||
metadata=metadata,
|
||
pages=pages,
|
||
processing_errors=json_data.get('processing_errors', [])
|
||
)
|
||
|
||
logger.info(f"Converted JSON to UnifiedDocument: {len(pages)} pages, track={processing_track.value}")
|
||
return unified_doc
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to convert JSON to UnifiedDocument: {e}")
|
||
import traceback
|
||
traceback.print_exc()
|
||
return None
|
||
|
||
def _json_to_document_element(self, elem_dict: Dict) -> Optional['DocumentElement']:
|
||
"""
|
||
Convert JSON dict to DocumentElement.
|
||
|
||
Args:
|
||
elem_dict: Element dictionary from JSON
|
||
|
||
Returns:
|
||
DocumentElement or None if conversion fails
|
||
"""
|
||
try:
|
||
# Parse element type
|
||
type_str = elem_dict.get('type', 'text')
|
||
try:
|
||
elem_type = ElementType(type_str)
|
||
except ValueError:
|
||
# Fallback to TEXT for unknown types
|
||
elem_type = ElementType.TEXT
|
||
logger.warning(f"Unknown element type '{type_str}', falling back to TEXT")
|
||
|
||
# Content-based HTML table detection: reclassify text elements with HTML table content
|
||
content = elem_dict.get('content', '')
|
||
if elem_type == ElementType.TEXT and isinstance(content, str) and '<table' in content.lower():
|
||
logger.info(f"Reclassifying element from TEXT to TABLE due to HTML table content")
|
||
elem_type = ElementType.TABLE
|
||
|
||
# Parse bounding box
|
||
bbox_dict = elem_dict.get('bbox', {})
|
||
bbox = BoundingBox(
|
||
x0=bbox_dict.get('x0', 0),
|
||
y0=bbox_dict.get('y0', 0),
|
||
x1=bbox_dict.get('x1', 0),
|
||
y1=bbox_dict.get('y1', 0)
|
||
)
|
||
|
||
# Parse style if present
|
||
style = None
|
||
if 'style' in elem_dict and elem_dict['style']:
|
||
style_dict = elem_dict['style']
|
||
style = StyleInfo(
|
||
font_name=style_dict.get('font_name'),
|
||
font_size=style_dict.get('font_size'),
|
||
font_weight=style_dict.get('font_weight'),
|
||
font_style=style_dict.get('font_style'),
|
||
text_color=style_dict.get('text_color'),
|
||
bg_color=style_dict.get('bg_color') or style_dict.get('background_color'),
|
||
alignment=style_dict.get('alignment'),
|
||
)
|
||
|
||
# Parse children (spans)
|
||
children = []
|
||
for child_dict in elem_dict.get('children', []):
|
||
child = self._json_to_document_element(child_dict)
|
||
if child:
|
||
children.append(child)
|
||
|
||
# Process content based on element type
|
||
content = elem_dict.get('content', '')
|
||
|
||
# For TABLE elements, convert dict content to TableData object
|
||
if elem_type == ElementType.TABLE and isinstance(content, dict) and 'cells' in content:
|
||
try:
|
||
content = TableData.from_dict(content)
|
||
logger.debug(f"Converted table dict to TableData: {content.rows}x{content.cols}, {len(content.cells)} cells")
|
||
except Exception as e:
|
||
logger.warning(f"Failed to convert table dict to TableData: {e}")
|
||
# Keep original dict as fallback
|
||
|
||
# Create element
|
||
element = DocumentElement(
|
||
element_id=elem_dict.get('element_id', ''),
|
||
type=elem_type,
|
||
content=content,
|
||
bbox=bbox,
|
||
confidence=elem_dict.get('confidence'),
|
||
style=style,
|
||
metadata=elem_dict.get('metadata', {}),
|
||
children=children
|
||
)
|
||
|
||
return element
|
||
|
||
except Exception as e:
|
||
logger.warning(f"Failed to convert element: {e}")
|
||
return None
|
||
|
||
def _is_list_item_fallback(self, element: 'DocumentElement') -> bool:
|
||
"""
|
||
Fallback detection for list items not marked with ElementType.LIST_ITEM.
|
||
|
||
Checks metadata and text patterns to identify list items.
|
||
|
||
Args:
|
||
element: Document element to check
|
||
|
||
Returns:
|
||
True if element appears to be a list item
|
||
"""
|
||
# Skip if already categorized as table or image
|
||
if element.type in [ElementType.TABLE, ElementType.IMAGE, ElementType.FIGURE,
|
||
ElementType.CHART, ElementType.DIAGRAM]:
|
||
return False
|
||
|
||
# Check metadata for list-related fields
|
||
if element.metadata:
|
||
# Check for list_level metadata
|
||
if 'list_level' in element.metadata:
|
||
return True
|
||
# Check for parent_item (indicates list hierarchy)
|
||
if 'parent_item' in element.metadata:
|
||
return True
|
||
# Check for children (could be parent list item)
|
||
if 'children' in element.metadata and element.metadata['children']:
|
||
return True
|
||
|
||
# Check text content for list patterns
|
||
if element.is_text:
|
||
text = element.get_text().lstrip()
|
||
# Ordered list pattern: starts with number followed by . or )
|
||
if re.match(r'^\d+[\.\)]\s', text):
|
||
return True
|
||
# Unordered list pattern: starts with bullet character
|
||
if re.match(r'^[•·▪▫◦‣⁃\-\*]\s', text):
|
||
return True
|
||
|
||
return False
|
||
|
||
def _draw_list_elements_direct(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
list_elements: List['DocumentElement'],
|
||
page_height: float
|
||
):
|
||
"""
|
||
Draw list elements with proper sequential numbering and formatting.
|
||
|
||
This method processes all list items on a page, groups them into lists,
|
||
and assigns proper sequential numbering to ordered lists.
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
list_elements: List of LIST_ITEM elements
|
||
page_height: Page height for coordinate transformation
|
||
"""
|
||
if not list_elements:
|
||
return
|
||
|
||
# Sort list items by position (top to bottom, left to right)
|
||
sorted_items = sorted(list_elements, key=lambda e: (e.bbox.y0, e.bbox.x0))
|
||
|
||
# Group list items into lists based on proximity and level
|
||
list_groups = []
|
||
current_group = []
|
||
prev_y = None
|
||
prev_level = None
|
||
max_gap = 30 # Maximum vertical gap between items in same list (in points)
|
||
|
||
for item in sorted_items:
|
||
level = item.metadata.get('list_level', 0) if item.metadata else 0
|
||
y_pos = item.bbox.y0
|
||
|
||
# Check if this item belongs to current group
|
||
if current_group and prev_y is not None:
|
||
gap = abs(y_pos - prev_y)
|
||
# Start new group if gap is too large or level changed significantly
|
||
if gap > max_gap or (prev_level is not None and level != prev_level):
|
||
list_groups.append(current_group)
|
||
current_group = []
|
||
|
||
current_group.append(item)
|
||
prev_y = y_pos
|
||
prev_level = level
|
||
|
||
if current_group:
|
||
list_groups.append(current_group)
|
||
|
||
# Process each list group
|
||
for group in list_groups:
|
||
# Detect list type from first item
|
||
first_item = group[0]
|
||
text_content = first_item.get_text()
|
||
text_stripped = text_content.lstrip()
|
||
|
||
list_type = None
|
||
list_counter = 1
|
||
|
||
# Determine list type
|
||
if re.match(r'^\d+[\.\)]\s', text_stripped):
|
||
list_type = 'ordered'
|
||
# Extract starting number
|
||
match = re.match(r'^(\d+)[\.\)]\s', text_stripped)
|
||
if match:
|
||
list_counter = int(match.group(1))
|
||
elif re.match(r'^[•·▪▫◦‣⁃]\s', text_stripped):
|
||
list_type = 'unordered'
|
||
|
||
# Draw each item in the group with proper spacing
|
||
# Track cumulative Y offset to apply spacing_after between items
|
||
cumulative_y_offset = 0
|
||
|
||
for item_idx, item in enumerate(group):
|
||
# Prepare list marker based on type
|
||
if list_type == 'ordered':
|
||
list_marker = f"{list_counter}. "
|
||
list_counter += 1
|
||
elif list_type == 'unordered':
|
||
list_marker = "• "
|
||
else:
|
||
list_marker = "" # No marker if type unknown
|
||
|
||
# Store list marker in item metadata for _draw_text_element_direct
|
||
if not item.metadata:
|
||
item.metadata = {}
|
||
item.metadata['_list_marker'] = list_marker
|
||
item.metadata['_list_type'] = list_type
|
||
|
||
# Add default list item spacing if not specified
|
||
# This ensures consistent spacing between list items
|
||
desired_spacing_after = item.metadata.get('spacing_after', 0)
|
||
if desired_spacing_after == 0:
|
||
# Default list item spacing: 3 points between items (except last item)
|
||
if item_idx < len(group) - 1:
|
||
desired_spacing_after = 3.0
|
||
item.metadata['spacing_after'] = desired_spacing_after
|
||
|
||
# Draw the list item with cumulative Y offset
|
||
self._draw_text_element_direct(pdf_canvas, item, page_height, y_offset=cumulative_y_offset)
|
||
|
||
# Calculate spacing to add after this item
|
||
if item_idx < len(group) - 1 and desired_spacing_after > 0:
|
||
next_item = group[item_idx + 1]
|
||
|
||
# Calculate actual vertical gap between items (in document coordinates)
|
||
# Note: Y increases downward in document coordinates
|
||
actual_gap = next_item.bbox.y0 - item.bbox.y1
|
||
|
||
# If actual gap is less than desired spacing, add offset to push next item down
|
||
if actual_gap < desired_spacing_after:
|
||
additional_spacing = desired_spacing_after - actual_gap
|
||
cumulative_y_offset -= additional_spacing # Negative because PDF Y increases upward
|
||
logger.debug(f"Adding {additional_spacing:.1f}pt spacing after list item {item.element_id} "
|
||
f"(actual_gap={actual_gap:.1f}pt, desired={desired_spacing_after:.1f}pt)")
|
||
|
||
def _draw_text_with_spans(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
spans: List['DocumentElement'],
|
||
line_x: float,
|
||
line_y: float,
|
||
default_font_size: float,
|
||
max_width: float = None
|
||
) -> float:
|
||
"""
|
||
Draw text with inline span styling (mixed styles within a line).
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
spans: List of span DocumentElements
|
||
line_x: Starting X position
|
||
line_y: Y position
|
||
default_font_size: Default font size if span has none
|
||
max_width: Maximum width available (for scaling if needed)
|
||
|
||
Returns:
|
||
Total width of drawn text
|
||
"""
|
||
if not spans:
|
||
return 0
|
||
|
||
# First pass: calculate total width with original sizes
|
||
total_width = 0
|
||
span_data = [] # Store (span, text, font, size) for rendering
|
||
|
||
for span in spans:
|
||
span_text = span.get_text()
|
||
if not span_text:
|
||
continue
|
||
|
||
# Apply span-specific styling to get font and size
|
||
if span.style:
|
||
self._apply_text_style(pdf_canvas, span.style, default_size=default_font_size)
|
||
else:
|
||
font_name = self.font_name if self.font_registered else 'Helvetica'
|
||
pdf_canvas.setFont(font_name, default_font_size)
|
||
|
||
current_font = pdf_canvas._fontname
|
||
current_size = pdf_canvas._fontsize
|
||
|
||
# Calculate span width
|
||
span_width = pdf_canvas.stringWidth(span_text, current_font, current_size)
|
||
total_width += span_width
|
||
|
||
span_data.append((span, span_text, current_font, current_size, span_width))
|
||
|
||
# Calculate scale factor if needed
|
||
scale_factor = 1.0
|
||
if max_width and total_width > max_width:
|
||
scale_factor = (max_width / total_width) * 0.95 # 95% to leave margin
|
||
logger.debug(f"Scaling spans: total_width={total_width:.1f}pt > max_width={max_width:.1f}pt, scale={scale_factor:.2f}")
|
||
|
||
# Second pass: draw spans with scaling
|
||
x_pos = line_x
|
||
|
||
for span, span_text, font_name, original_size, span_width in span_data:
|
||
# Apply scaled font size
|
||
scaled_size = original_size * scale_factor
|
||
scaled_size = max(scaled_size, 3) # Minimum 3pt
|
||
|
||
# Set font with scaled size
|
||
pdf_canvas.setFont(font_name, scaled_size)
|
||
|
||
# Draw this span
|
||
pdf_canvas.drawString(x_pos, line_y, span_text)
|
||
|
||
# Calculate actual width with scaled size and advance position
|
||
actual_width = pdf_canvas.stringWidth(span_text, font_name, scaled_size)
|
||
x_pos += actual_width
|
||
|
||
return total_width * scale_factor
|
||
|
||
def _draw_text_element_direct(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
element: 'DocumentElement',
|
||
page_height: float,
|
||
y_offset: float = 0
|
||
):
|
||
"""
|
||
Draw text element with Direct track rich formatting.
|
||
FIXED: Correctly handles multi-line blocks and spans coordinates.
|
||
|
||
Prioritizes span-based rendering (using precise bbox from each span),
|
||
falls back to block-level rendering with corrected Y-axis logic.
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
element: DocumentElement with text content
|
||
page_height: Page height for coordinate transformation
|
||
y_offset: Optional Y coordinate offset (for list spacing), in PDF coordinates
|
||
"""
|
||
try:
|
||
text_content = element.get_text()
|
||
if not text_content:
|
||
return
|
||
|
||
# Get bounding box
|
||
bbox = element.bbox
|
||
if not bbox:
|
||
logger.warning(f"No bbox for text element {element.element_id}")
|
||
return
|
||
|
||
bbox_width = bbox.x1 - bbox.x0
|
||
bbox_height = bbox.y1 - bbox.y0
|
||
|
||
# --- FIX 1: Prioritize Span-based Drawing (Precise Layout) ---
|
||
# DirectExtractionEngine provides children (spans) with precise bboxes.
|
||
# Using these preserves exact layout, kerning, and multi-column positioning.
|
||
if element.children and len(element.children) > 0:
|
||
for span in element.children:
|
||
span_text = span.get_text()
|
||
if not span_text:
|
||
continue
|
||
|
||
# Use span's own bbox for positioning
|
||
s_bbox = span.bbox
|
||
if not s_bbox:
|
||
continue
|
||
|
||
# Calculate font size from span style or bbox
|
||
s_font_size = 10 # default
|
||
if span.style and span.style.font_size:
|
||
s_font_size = span.style.font_size
|
||
else:
|
||
# Estimate from bbox height
|
||
s_font_size = (s_bbox.y1 - s_bbox.y0) * 0.75
|
||
s_font_size = max(min(s_font_size, 72), 4)
|
||
|
||
# Apply span style
|
||
if span.style:
|
||
self._apply_text_style(pdf_canvas, span.style, default_size=s_font_size)
|
||
else:
|
||
font_name = self.font_name if self.font_registered else 'Helvetica'
|
||
pdf_canvas.setFont(font_name, s_font_size)
|
||
|
||
# Transform coordinates
|
||
# PyMuPDF y1 is bottom of text box. ReportLab draws at baseline.
|
||
# Using y1 with a small offset (20% of font size) approximates baseline position.
|
||
span_pdf_x = s_bbox.x0
|
||
span_pdf_y = page_height - s_bbox.y1 + (s_font_size * 0.2)
|
||
|
||
pdf_canvas.drawString(span_pdf_x, span_pdf_y + y_offset, span_text)
|
||
|
||
# If we drew spans, we are done. Do not draw the block text on top.
|
||
logger.debug(f"Drew {len(element.children)} spans using precise bbox positioning")
|
||
return
|
||
|
||
# --- FIX 2: Block-level Fallback (Corrected Y-Axis Logic) ---
|
||
# Used when no spans are available (e.g. filtered text or modified structures)
|
||
|
||
# Calculate font size from bbox height
|
||
font_size = bbox_height * 0.75
|
||
font_size = max(min(font_size, 72), 4) # Clamp 4-72pt
|
||
|
||
# Apply style if available
|
||
alignment = 'left' # Default alignment
|
||
if hasattr(element, 'style') and element.style:
|
||
self._apply_text_style(pdf_canvas, element.style, default_size=font_size)
|
||
# Get alignment from style
|
||
if hasattr(element.style, 'alignment') and element.style.alignment:
|
||
alignment = element.style.alignment
|
||
else:
|
||
# Use default font
|
||
font_name = self.font_name if self.font_registered else 'Helvetica'
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
|
||
# Detect list items and extract list properties
|
||
is_list_item = (element.type == ElementType.LIST_ITEM)
|
||
list_level = element.metadata.get('list_level', 0) if element.metadata else 0
|
||
|
||
# Get pre-computed list marker from metadata (set by _draw_list_elements_direct)
|
||
list_marker = element.metadata.get('_list_marker', '') if element.metadata else ''
|
||
list_type = element.metadata.get('_list_type') if element.metadata else None
|
||
|
||
# If no pre-computed marker, remove original marker from text
|
||
if is_list_item and list_marker:
|
||
# Remove original marker from text content
|
||
text_stripped = text_content.lstrip()
|
||
# Remove ordered list marker
|
||
text_content = re.sub(r'^\d+[\.\)]\s', '', text_stripped)
|
||
# Remove unordered list marker
|
||
text_content = re.sub(r'^[•·▪▫◦‣⁃]\s', '', text_content)
|
||
|
||
# Get indentation from metadata (in points)
|
||
indent = element.metadata.get('indent', 0) if element.metadata else 0
|
||
first_line_indent = element.metadata.get('first_line_indent', indent) if element.metadata else indent
|
||
|
||
# Apply list indentation (20pt per level)
|
||
if is_list_item:
|
||
list_indent = list_level * 20 # 20pt per level
|
||
indent += list_indent
|
||
first_line_indent += list_indent
|
||
|
||
# Get paragraph spacing
|
||
paragraph_spacing_before = element.metadata.get('spacing_before', 0) if element.metadata else 0
|
||
paragraph_spacing_after = element.metadata.get('spacing_after', 0) if element.metadata else 0
|
||
|
||
# --- CRITICAL FIX: Start from TOP of block (y0), not bottom (y1) ---
|
||
pdf_x = bbox.x0
|
||
pdf_y_top = page_height - bbox.y0 - paragraph_spacing_before + y_offset
|
||
|
||
# Handle line breaks
|
||
lines = text_content.split('\n')
|
||
line_height = font_size * 1.2 # 120% of font size
|
||
|
||
# Calculate list marker width for multi-line alignment
|
||
marker_width = 0
|
||
if is_list_item and list_marker:
|
||
# Use current font to calculate marker width
|
||
marker_width = pdf_canvas.stringWidth(list_marker, pdf_canvas._fontname, font_size)
|
||
|
||
# Draw each line with alignment
|
||
for i, line in enumerate(lines):
|
||
if not line.strip():
|
||
# Empty line: skip
|
||
continue
|
||
|
||
# Calculate Y position: Start from top, move down by line_height for each line
|
||
# The first line's baseline is approx 1 line_height below the top
|
||
line_y = pdf_y_top - ((i + 1) * line_height) + (font_size * 0.25) # 0.25 adjust for baseline
|
||
|
||
# Get current font info
|
||
font_name = pdf_canvas._fontname
|
||
current_font_size = pdf_canvas._fontsize
|
||
|
||
# Calculate line indentation
|
||
line_indent = first_line_indent if i == 0 else indent
|
||
|
||
# For list items: align subsequent lines with text after marker
|
||
if is_list_item and i > 0 and marker_width > 0:
|
||
line_indent += marker_width
|
||
|
||
# Prepend list marker to first line
|
||
rendered_line = line
|
||
if is_list_item and i == 0 and list_marker:
|
||
rendered_line = list_marker + line
|
||
|
||
# Calculate text width
|
||
text_width = pdf_canvas.stringWidth(rendered_line, font_name, current_font_size)
|
||
available_width = bbox_width - line_indent
|
||
|
||
# Scale font if needed
|
||
if text_width > available_width and available_width > 0:
|
||
scale_factor = available_width / text_width
|
||
scaled_size = current_font_size * scale_factor * 0.95
|
||
scaled_size = max(scaled_size, 3)
|
||
pdf_canvas.setFont(font_name, scaled_size)
|
||
text_width = pdf_canvas.stringWidth(rendered_line, font_name, scaled_size)
|
||
current_font_size = scaled_size
|
||
|
||
# Calculate X position based on alignment
|
||
line_x = pdf_x + line_indent
|
||
|
||
if alignment == 'center':
|
||
line_x = pdf_x + (bbox_width - text_width) / 2
|
||
elif alignment == 'right':
|
||
line_x = pdf_x + bbox_width - text_width
|
||
elif alignment == 'justify' and i < len(lines) - 1:
|
||
# Justify: distribute extra space between words (except last line)
|
||
words = rendered_line.split()
|
||
if len(words) > 1:
|
||
total_word_width = sum(pdf_canvas.stringWidth(word, font_name, current_font_size) for word in words)
|
||
extra_space = available_width - total_word_width
|
||
if extra_space > 0:
|
||
word_spacing = extra_space / (len(words) - 1)
|
||
|
||
# Draw words with calculated spacing
|
||
x_pos = pdf_x + line_indent
|
||
for word in words:
|
||
pdf_canvas.drawString(x_pos, line_y, word)
|
||
word_width = pdf_canvas.stringWidth(word, font_name, current_font_size)
|
||
x_pos += word_width + word_spacing
|
||
|
||
# Reset font for next line and skip normal drawString
|
||
if text_width > available_width:
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
continue
|
||
|
||
# Draw the line at calculated position
|
||
pdf_canvas.drawString(line_x, line_y, rendered_line)
|
||
|
||
# Reset font size for next line
|
||
if text_width > available_width:
|
||
pdf_canvas.setFont(font_name, font_size)
|
||
|
||
# Calculate actual text height used
|
||
actual_text_height = len(lines) * line_height
|
||
bbox_bottom_margin = bbox_height - actual_text_height - paragraph_spacing_before
|
||
|
||
# Note: For list items, spacing_after is applied via y_offset in _draw_list_elements_direct
|
||
# For other elements, spacing is inherent in element positioning (bbox-based layout)
|
||
list_info = f", list={list_type}, level={list_level}" if is_list_item else ""
|
||
y_offset_info = f", y_offset={y_offset:.1f}pt" if y_offset != 0 else ""
|
||
logger.debug(f"Drew text element (fallback): {text_content[:30]}... "
|
||
f"({len(lines)} lines, align={alignment}, indent={indent}{list_info}{y_offset_info}, "
|
||
f"spacing_before={paragraph_spacing_before}, spacing_after={paragraph_spacing_after}, "
|
||
f"actual_height={actual_text_height:.1f}, bbox_bottom_margin={bbox_bottom_margin:.1f})")
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to draw text element {element.element_id}: {e}")
|
||
|
||
def _build_rows_from_cells_dict(self, content: dict) -> list:
|
||
"""
|
||
Build row structure from cells dict (from Direct extraction JSON).
|
||
|
||
The cells structure from Direct extraction:
|
||
{
|
||
"rows": 6,
|
||
"cols": 2,
|
||
"cells": [
|
||
{"row": 0, "col": 0, "content": "..."},
|
||
{"row": 0, "col": 1, "content": "..."},
|
||
...
|
||
]
|
||
}
|
||
|
||
Returns format compatible with HTMLTableParser output:
|
||
[
|
||
{"cells": [{"text": "..."}, {"text": "..."}]}, # row 0
|
||
{"cells": [{"text": "..."}, {"text": "..."}]}, # row 1
|
||
...
|
||
]
|
||
"""
|
||
try:
|
||
num_rows = content.get('rows', 0)
|
||
num_cols = content.get('cols', 0)
|
||
cells = content.get('cells', [])
|
||
|
||
if not cells or num_rows == 0 or num_cols == 0:
|
||
return []
|
||
|
||
# Initialize rows structure
|
||
rows_data = []
|
||
for _ in range(num_rows):
|
||
rows_data.append({'cells': [{'text': ''} for _ in range(num_cols)]})
|
||
|
||
# Fill in cell content
|
||
for cell in cells:
|
||
row_idx = cell.get('row', 0)
|
||
col_idx = cell.get('col', 0)
|
||
cell_content = cell.get('content', '')
|
||
|
||
if 0 <= row_idx < num_rows and 0 <= col_idx < num_cols:
|
||
rows_data[row_idx]['cells'][col_idx]['text'] = str(cell_content) if cell_content else ''
|
||
|
||
logger.debug(f"Built {num_rows} rows from cells dict")
|
||
return rows_data
|
||
|
||
except Exception as e:
|
||
logger.error(f"Error building rows from cells dict: {e}")
|
||
return []
|
||
|
||
def _draw_table_element_direct(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
element: 'DocumentElement',
|
||
page_height: float
|
||
):
|
||
"""
|
||
Draw table element with Direct track positioning.
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
element: DocumentElement with table content
|
||
page_height: Page height for coordinate transformation
|
||
"""
|
||
try:
|
||
# Get table data - can be TableData object or dict from JSON
|
||
rows_data = None
|
||
|
||
if isinstance(element.content, TableData):
|
||
# Direct TableData object - convert to HTML then parse
|
||
html_content = element.content.to_html()
|
||
parser = HTMLTableParser()
|
||
parser.feed(html_content)
|
||
if parser.tables and parser.tables[0]['rows']:
|
||
rows_data = parser.tables[0]['rows']
|
||
elif isinstance(element.content, dict):
|
||
# Dict from JSON - check if it has cells structure (from Direct extraction)
|
||
if 'cells' in element.content:
|
||
# Build rows from cells structure directly (avoid HTML round-trip)
|
||
rows_data = self._build_rows_from_cells_dict(element.content)
|
||
elif 'html' in element.content:
|
||
# Has HTML content - parse it
|
||
html_content = element.content['html']
|
||
parser = HTMLTableParser()
|
||
parser.feed(html_content)
|
||
if parser.tables and parser.tables[0]['rows']:
|
||
rows_data = parser.tables[0]['rows']
|
||
|
||
if not rows_data:
|
||
logger.warning(f"No table data for {element.element_id}")
|
||
return
|
||
|
||
rows = rows_data
|
||
|
||
# Get bbox
|
||
bbox = element.bbox
|
||
if not bbox:
|
||
logger.warning(f"No bbox for table {element.element_id}")
|
||
return
|
||
|
||
# Transform coordinates
|
||
pdf_x = bbox.x0
|
||
# Use exact bbox position (no buffer) - scaling will ensure table fits
|
||
pdf_y = page_height - bbox.y1 # Bottom of table (ReportLab Y coordinate)
|
||
|
||
table_width = bbox.x1 - bbox.x0
|
||
table_height = bbox.y1 - bbox.y0
|
||
|
||
# Build table data for ReportLab
|
||
table_content = []
|
||
for row in rows:
|
||
row_data = [cell['text'].strip() for cell in row['cells']]
|
||
table_content.append(row_data)
|
||
|
||
# Create table
|
||
from reportlab.platypus import Table, TableStyle
|
||
from reportlab.lib import colors
|
||
|
||
# Determine number of rows and columns for cell_boxes calculation
|
||
num_rows = len(rows)
|
||
max_cols = max(len(row['cells']) for row in rows) if rows else 0
|
||
|
||
# Use original column widths from extraction if available
|
||
# Otherwise try to compute from cell_boxes (from PP-StructureV3)
|
||
col_widths = None
|
||
if element.metadata and 'column_widths' in element.metadata:
|
||
col_widths = element.metadata['column_widths']
|
||
logger.debug(f"Using extracted column widths: {col_widths}")
|
||
elif element.metadata and 'cell_boxes' in element.metadata:
|
||
# Use cell_boxes from PP-StructureV3 for accurate column/row sizing
|
||
cell_boxes = element.metadata['cell_boxes']
|
||
cell_boxes_source = element.metadata.get('cell_boxes_source', 'unknown')
|
||
table_bbox_list = [bbox.x0, bbox.y0, bbox.x1, bbox.y1]
|
||
logger.info(f"[TABLE] Using {len(cell_boxes)} cell boxes from {cell_boxes_source}")
|
||
|
||
computed_col_widths, computed_row_heights = self._compute_table_grid_from_cell_boxes(
|
||
cell_boxes, table_bbox_list, num_rows, max_cols
|
||
)
|
||
if computed_col_widths:
|
||
col_widths = computed_col_widths
|
||
logger.info(f"[TABLE] Computed {len(col_widths)} column widths from cell_boxes")
|
||
|
||
# NOTE: Don't use rowHeights from extraction - it causes content overlap
|
||
# The extracted row heights are based on cell boundaries, not text content height.
|
||
# When text wraps or uses different font sizes, the heights don't match.
|
||
# Let ReportLab auto-calculate row heights based on content, then use scaling
|
||
# to fit within the bbox (same approach as old commit ba8ddf2b).
|
||
|
||
# Create table without rowHeights - let ReportLab auto-calculate
|
||
t = Table(table_content, colWidths=col_widths)
|
||
|
||
# Apply style with minimal padding to reduce table extension
|
||
# Use Chinese font to support special characters (℃, μm, ≦, ×, Ω, etc.)
|
||
font_for_table = self.font_name if self.font_registered else 'Helvetica'
|
||
style = TableStyle([
|
||
('GRID', (0, 0), (-1, -1), 0.5, colors.grey),
|
||
('FONTNAME', (0, 0), (-1, -1), font_for_table),
|
||
('FONTSIZE', (0, 0), (-1, -1), 8),
|
||
('ALIGN', (0, 0), (-1, -1), 'LEFT'),
|
||
('VALIGN', (0, 0), (-1, -1), 'TOP'),
|
||
# Set minimal padding to prevent table from extending beyond bbox
|
||
# User reported padding=1 was still insufficient
|
||
('TOPPADDING', (0, 0), (-1, -1), 0),
|
||
('BOTTOMPADDING', (0, 0), (-1, -1), 0),
|
||
('LEFTPADDING', (0, 0), (-1, -1), 1),
|
||
('RIGHTPADDING', (0, 0), (-1, -1), 1),
|
||
])
|
||
t.setStyle(style)
|
||
|
||
# Use canvas scaling as fallback to fit table within bbox
|
||
# With proper row heights, scaling should be minimal (close to 1.0)
|
||
|
||
# Step 1: Wrap to get actual rendered size
|
||
actual_width, actual_height = t.wrapOn(pdf_canvas, table_width * 10, table_height * 10)
|
||
logger.info(f"Table natural size: {actual_width:.1f} × {actual_height:.1f}pt, bbox: {table_width:.1f} × {table_height:.1f}pt")
|
||
|
||
# Step 2: Calculate scale factor to fit within bbox
|
||
scale_x = table_width / actual_width if actual_width > table_width else 1.0
|
||
scale_y = table_height / actual_height if actual_height > table_height else 1.0
|
||
scale = min(scale_x, scale_y, 1.0) # Never scale up, only down
|
||
|
||
logger.info(f"Scale factor: {scale:.3f} (x={scale_x:.3f}, y={scale_y:.3f})")
|
||
|
||
# Step 3: Draw with scaling using canvas transform
|
||
pdf_canvas.saveState()
|
||
pdf_canvas.translate(pdf_x, pdf_y)
|
||
pdf_canvas.scale(scale, scale)
|
||
t.drawOn(pdf_canvas, 0, 0)
|
||
pdf_canvas.restoreState()
|
||
|
||
logger.info(f"Drew table at ({pdf_x:.1f}, {pdf_y:.1f}) with scale {scale:.3f}, final size: {actual_width * scale:.1f} × {actual_height * scale:.1f}pt")
|
||
|
||
logger.debug(f"Drew table element: {len(rows)} rows")
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to draw table element {element.element_id}: {e}")
|
||
|
||
def _draw_image_element_direct(
|
||
self,
|
||
pdf_canvas: canvas.Canvas,
|
||
element: 'DocumentElement',
|
||
page_height: float,
|
||
result_dir: Path
|
||
):
|
||
"""
|
||
Draw image element with Direct track positioning.
|
||
|
||
Args:
|
||
pdf_canvas: ReportLab canvas object
|
||
element: DocumentElement with image content
|
||
page_height: Page height for coordinate transformation
|
||
result_dir: Directory containing image files
|
||
"""
|
||
try:
|
||
# Get image path
|
||
image_path_str = self._get_image_path(element)
|
||
if not image_path_str:
|
||
logger.warning(f"No image path for element {element.element_id}")
|
||
return
|
||
|
||
# Construct full path to image
|
||
# saved_path is relative to result_dir (e.g., "document_id_p1_img0.png")
|
||
image_path = result_dir / image_path_str
|
||
|
||
# Fallback for legacy data
|
||
if not image_path.exists():
|
||
image_path = result_dir / Path(image_path_str).name
|
||
|
||
if not image_path.exists():
|
||
logger.warning(f"Image not found: {image_path_str} (in {result_dir})")
|
||
return
|
||
|
||
# Get bbox
|
||
bbox = element.bbox
|
||
if not bbox:
|
||
logger.warning(f"No bbox for image {element.element_id}")
|
||
return
|
||
|
||
# Transform coordinates
|
||
pdf_x = bbox.x0
|
||
pdf_y = page_height - bbox.y1 # Bottom of image
|
||
|
||
image_width = bbox.x1 - bbox.x0
|
||
image_height = bbox.y1 - bbox.y0
|
||
|
||
# Draw image
|
||
pdf_canvas.drawImage(
|
||
str(image_path),
|
||
pdf_x,
|
||
pdf_y,
|
||
width=image_width,
|
||
height=image_height,
|
||
preserveAspectRatio=True
|
||
)
|
||
|
||
logger.debug(f"Drew image: {image_path} (from: {image_path_str})")
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to draw image element {element.element_id}: {e}")
|
||
|
||
|
||
# Singleton instance
|
||
pdf_generator_service = PDFGeneratorService()
|