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OmniFile AI Processor — Document Exporter
===========================================
Source: arabic-ocr-pro/core/exporter.py
Exports OCR results to multiple formats with RTL support:
- Plain text (UTF-8 with RTL BOM)
- JSON (structured with bounding boxes and confidence)
- DOCX (Microsoft Word with RTL paragraph support)
- HTML (preserves document layout with RTL styling)
- Searchable PDF (image + invisible text overlay)
"""
from __future__ import annotations
import io
import json
import logging
from datetime import datetime
from pathlib import Path
from typing import Optional, Union
logger = logging.getLogger(__name__)
class DocumentExporter:
"""Exports OCR documents to various output formats.
Supports text, JSON, DOCX, HTML, and searchable PDF output.
Each format preserves Arabic RTL text and document structure
as appropriate.
The exporter accepts a document object that follows a simple protocol:
- ``document.pages`` — iterable of page objects
- Each page has ``page_number``, ``width``, ``height``, and ``blocks``
- Each block has ``block_type``, ``get_text()``, ``tokens``, ``bbox``,
and optional ``table_data``
- ``document.metadata`` has ``filename``, ``file_size``,
``page_count``, ``processing_time``, ``engine_used``
Attributes:
rtl: Whether to mark text as RTL in output formats that support it.
"""
def __init__(self, rtl: bool = True) -> None:
"""Initialize the document exporter.
Args:
rtl: Whether to enable RTL text direction in supported formats.
"""
self.rtl = rtl
# ------------------------------------------------------------------
# Main export dispatcher
# ------------------------------------------------------------------
def export(
self,
document,
output_path: str | Path,
format_name: str = "txt",
images: Optional[list] = None,
) -> str:
"""Export a document to the specified format.
Args:
document: Processed OCR document (protocol-compliant object).
output_path: Output file path.
format_name: Output format
(``'txt'``, ``'json'``, ``'docx'``, ``'html'``,
``'pdf'``).
images: Optional list of page images (for searchable PDF).
Returns:
Absolute path to the exported file.
Raises:
ValueError: If the format is not supported.
RuntimeError: If export fails.
"""
output_path = Path(output_path)
output_path.parent.mkdir(parents=True, exist_ok=True)
exporters = {
"txt": self.export_text,
"json": self.export_json,
"docx": self.export_docx,
"html": self.export_html,
"pdf": self.export_pdf,
}
format_name = format_name.lower().lstrip(".")
if format_name not in exporters:
raise ValueError(
f"Unsupported export format: '{format_name}'. "
f"Supported formats: {list(exporters.keys())}"
)
try:
exporters[format_name](document, output_path, images)
logger.info(
f"Exported document to {output_path} (format: {format_name})"
)
return str(output_path.resolve())
except Exception as exc:
raise RuntimeError(
f"Failed to export to {format_name}: {exc}"
) from exc
# ------------------------------------------------------------------
# Plain text
# ------------------------------------------------------------------
def export_text(
self,
document,
output_path: str | Path,
images: Optional[list] = None,
) -> None:
"""Export document as plain text (UTF-8).
Preserves page structure and block ordering.
Args:
document: Processed OCR document.
output_path: Output file path.
images: Ignored for text export.
"""
lines: list[str] = []
for page in document.pages:
lines.append(f"{'=' * 60}")
lines.append(f"Page {page.page_number}")
lines.append(f"{'=' * 60}")
lines.append("")
for block in page.blocks:
text = block.get_text().strip()
if not text:
continue
block_type = self._get_block_type_value(block)
if block_type == "HEADING":
lines.append("")
lines.append(text)
lines.append(
"-" * len(text) if len(text) < 60 else "-" * 60
)
lines.append("")
elif (
block_type == "TABLE"
and hasattr(block, "table_data")
and block.table_data
):
lines.append("[TABLE]")
for row in block.table_data:
line = " | ".join(cell.strip() for cell in row)
lines.append(line)
lines.append("[/TABLE]")
lines.append("")
else:
lines.append(text)
lines.append("")
content = "\n".join(lines)
with open(output_path, "w", encoding="utf-8") as f:
# Write BOM for better RTL support in some editors
f.write("\ufeff")
f.write(content)
# ------------------------------------------------------------------
# JSON
# ------------------------------------------------------------------
def export_json(
self,
document,
output_path: str | Path,
images: Optional[list] = None,
) -> None:
"""Export document as structured JSON.
Includes all tokens, bounding boxes, confidence scores,
and metadata.
Args:
document: Processed OCR document.
output_path: Output file path.
images: Ignored for JSON export.
"""
meta = document.metadata
data = {
"metadata": {
"filename": getattr(meta, "filename", ""),
"file_size": getattr(meta, "file_size", 0),
"page_count": getattr(meta, "page_count", 0),
"processing_time": getattr(meta, "processing_time", 0),
"engine": getattr(meta, "engine_used", ""),
"exported_at": datetime.now().isoformat(),
},
"pages": [],
}
for page in document.pages:
page_data = {
"page_number": page.page_number,
"width": getattr(page, "width", 0),
"height": getattr(page, "height", 0),
"blocks": [],
}
for block in page.blocks:
block_data = {
"type": self._get_block_type_value(block),
"text": block.get_text(),
"confidence": (
block.compute_confidence()
if hasattr(block, "compute_confidence")
else None
),
"bbox": (
block.bbox.model_dump()
if hasattr(block, "bbox") and block.bbox
and hasattr(block.bbox, "model_dump")
else None
),
"tokens": [
{
"text": token.text,
"confidence": token.confidence,
"bbox": (
token.bbox.model_dump()
if hasattr(token.bbox, "model_dump")
else None
),
"engine": getattr(token, "engine", ""),
}
for token in block.tokens
],
}
if (
self._get_block_type_value(block) == "TABLE"
and hasattr(block, "table_data")
and block.table_data
):
block_data["table_data"] = block.table_data
page_data["blocks"].append(block_data)
data["pages"].append(page_data)
with open(output_path, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=2)
# ------------------------------------------------------------------
# DOCX
# ------------------------------------------------------------------
def export_docx(
self,
document,
output_path: str | Path,
images: Optional[list] = None,
) -> None:
"""Export document as a DOCX file with RTL support.
Creates a Microsoft Word document with proper RTL paragraph
formatting for Arabic text.
Args:
document: Processed OCR document.
output_path: Output file path.
images: Ignored for DOCX export.
Raises:
RuntimeError: If python-docx is not installed.
"""
try:
from docx import Document as DocxDocument
from docx.shared import Pt
from docx.enum.text import WD_ALIGN_PARAGRAPH
except ImportError:
raise RuntimeError(
"python-docx is required for DOCX export. "
"Install with: pip install python-docx"
)
doc = DocxDocument()
# Set default font
style = doc.styles["Normal"]
font = style.font
font.name = "Arial"
font.size = Pt(11)
for page in document.pages:
for block in page.blocks:
text = block.get_text().strip()
if not text:
continue
block_type = self._get_block_type_value(block)
if block_type == "HEADING":
heading = doc.add_heading(level=2)
run = heading.add_run(text)
run.font.rtl = self.rtl
heading.paragraph_format.alignment = (
WD_ALIGN_PARAGRAPH.RIGHT
if self.rtl
else WD_ALIGN_PARAGRAPH.LEFT
)
elif (
block_type == "TABLE"
and hasattr(block, "table_data")
and block.table_data
):
rows = len(block.table_data)
cols = (
max(len(row) for row in block.table_data)
if block.table_data
else 0
)
if rows > 0 and cols > 0:
table = doc.add_table(rows=rows, cols=cols)
table.style = "Table Grid"
for i, row_data in enumerate(block.table_data):
for j, cell_text in enumerate(row_data):
if j < cols:
cell = table.cell(i, j)
cell.text = cell_text.strip()
doc.add_paragraph("")
else:
para = doc.add_paragraph()
run = para.add_run(text)
run.font.rtl = self.rtl
para.paragraph_format.alignment = (
WD_ALIGN_PARAGRAPH.RIGHT
if self.rtl
else WD_ALIGN_PARAGRAPH.LEFT
)
doc.save(str(output_path))
# ------------------------------------------------------------------
# HTML
# ------------------------------------------------------------------
def export_html(
self,
document,
output_path: str | Path,
images: Optional[list] = None,
) -> None:
"""Export document as an HTML file preserving layout.
Creates a styled HTML document with RTL support and
document structure preserved.
Args:
document: Processed OCR document.
output_path: Output file path.
images: Optional page images (base64 encoded or file paths).
"""
html_parts: list[str] = []
html_parts.append("""<!DOCTYPE html>
<html lang="ar" dir="rtl">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>OCR Document</title>
<style>
body { font-family: 'Arial', 'Tahoma', sans-serif; direction: rtl; text-align: right; max-width: 800px; margin: 0 auto; padding: 20px; }
.page { border: 1px solid #ccc; margin: 20px 0; padding: 20px; page-break-after: always; }
.page-header { text-align: center; color: #666; border-bottom: 1px solid #eee; padding-bottom: 10px; margin-bottom: 20px; }
.heading { font-size: 1.3em; font-weight: bold; margin: 15px 0; color: #333; }
.paragraph { margin: 10px 0; line-height: 1.8; text-align: justify; }
table { border-collapse: collapse; width: 100%; margin: 15px 0; }
th, td { border: 1px solid #ddd; padding: 8px; text-align: right; }
th { background-color: #f5f5f5; font-weight: bold; }
tr:nth-child(even) { background-color: #f9f9f9; }
.metadata { color: #999; font-size: 0.85em; margin-top: 30px; }
</style>
</head>
<body>
""")
for page in document.pages:
html_parts.append(' <div class="page">')
html_parts.append(
f' <div class="page-header">Page {page.page_number}</div>'
)
for block in page.blocks:
text = block.get_text().strip()
if not text:
continue
# Escape HTML entities
text = (
text.replace("&", "&")
.replace("<", "<")
.replace(">", ">")
.replace('"', """)
)
block_type = self._get_block_type_value(block)
if block_type == "HEADING":
html_parts.append(
f' <div class="heading">{text}</div>'
)
elif (
block_type == "TABLE"
and hasattr(block, "table_data")
and block.table_data
):
html_parts.append(" <table>")
for i, row in enumerate(block.table_data):
tag = "th" if i == 0 else "td"
cells = "".join(
f"<{tag}>{cell.strip()}</{tag}>"
for cell in row
)
html_parts.append(f" <tr>{cells}</tr>")
html_parts.append(" </table>")
else:
html_parts.append(
f' <div class="paragraph">{text}</div>'
)
html_parts.append(" </div>")
# Add metadata footer
meta = document.metadata
html_parts.append(f"""
<div class="metadata">
<p>Generated by OmniFile AI Processor</p>
<p>Source: {getattr(meta, 'filename', '')} | "
f"Pages: {getattr(meta, 'page_count', '')} | "
f"Engine: {getattr(meta, 'engine_used', '')}</p>
<p>Processing time: {getattr(meta, 'processing_time', 0):.2f}s</p>
</div>
</body>
</html>
""")
content = "\n".join(html_parts)
with open(output_path, "w", encoding="utf-8") as f:
f.write(content)
# ------------------------------------------------------------------
# Searchable PDF
# ------------------------------------------------------------------
def export_pdf(
self,
document,
output_path: str | Path,
images: Optional[list] = None,
) -> None:
"""Export document as a searchable PDF.
If page images are provided, creates a PDF with the original
images and an invisible text overlay for searchability.
Otherwise, creates a text-only PDF.
Args:
document: Processed OCR document.
output_path: Output file path.
images: Optional list of page images (numpy arrays).
Raises:
RuntimeError: If fpdf2 is not installed.
"""
try:
from fpdf import FPDF
except ImportError:
raise RuntimeError(
"fpdf2 is required for PDF export. "
"Install with: pip install fpdf2"
)
pdf = FPDF()
pdf.set_auto_page_break(auto=True, margin=15)
# Register a font that supports Arabic
try:
pdf.add_font(
"DejaVu", "",
"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
uni=True,
)
pdf.set_font("DejaVu", size=12)
except RuntimeError:
pdf.set_font("Helvetica", size=12)
for page_idx, page in enumerate(document.pages):
pdf.add_page()
# If we have page images, add as background
if images and page_idx < len(images):
try:
img = images[page_idx]
import cv2
# Convert BGR to RGB
if len(img.shape) == 3:
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
else:
img_rgb = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
# Save as temporary PNG
temp_path = Path(output_path).with_suffix(
f".page{page_idx}.png"
)
cv2.imwrite(
str(temp_path),
cv2.cvtColor(img_rgb, cv2.COLOR_RGB2BGR),
)
# Calculate image placement
page_w = pdf.w - 20
img_h = (
(img_rgb.shape[0] / img_rgb.shape[1]) * page_w
)
if img_h > pdf.h - 20:
scale = (pdf.h - 20) / img_h
page_w = page_w * scale
img_h = pdf.h - 20
pdf.image(str(temp_path), x=10, y=10, w=page_w)
# Clean up temp file
temp_path.unlink(missing_ok=True)
except Exception as exc:
logger.warning(
f"Failed to add page image to PDF: {exc}"
)
# Add invisible text layer for searchability
for block in page.blocks:
text = block.get_text().strip()
if not text:
continue
# White text for invisible overlay (if image present)
if images and page_idx < len(images):
pdf.set_text_color(255, 255, 255)
else:
pdf.set_text_color(0, 0, 0)
block_type = self._get_block_type_value(block)
if block_type == "HEADING":
pdf.set_font_size(14)
else:
pdf.set_font_size(11)
# Estimate position from bbox
if (
hasattr(block, "bbox")
and block.bbox
and images
and page_idx < len(images)
):
img = images[page_idx]
img_h_px, img_w_px = img.shape[:2]
x_pos = 10 + (block.bbox.x / img_w_px) * page_w
y_pos = 10 + (
block.bbox.y / img_h_px
) * (pdf.h - 20)
pdf.set_xy(x_pos, y_pos)
pdf.multi_cell(0, 6, text, align="R" if self.rtl else "L")
pdf.output(str(output_path))
# ------------------------------------------------------------------
# Utilities
# ------------------------------------------------------------------
@staticmethod
def get_supported_formats() -> list[str]:
"""Get list of supported export formats.
Returns:
List of format names (lowercase, without dots).
"""
return ["txt", "json", "docx", "html", "pdf"]
@staticmethod
def detect_format(path: str | Path) -> str:
"""Detect the export format from a file path.
Args:
path: Output file path.
Returns:
Format name (lowercase, without dot).
Raises:
ValueError: If the format cannot be determined.
"""
path = Path(path)
ext = path.suffix.lower().lstrip(".")
format_map = {
"txt": "txt",
"text": "txt",
"json": "json",
"docx": "docx",
"doc": "docx",
"html": "html",
"htm": "html",
"pdf": "pdf",
}
if ext in format_map:
return format_map[ext]
raise ValueError(
f"Cannot determine export format from extension: '{ext}'"
)
# ------------------------------------------------------------------
# Internal helpers
# ------------------------------------------------------------------
@staticmethod
def _get_block_type_value(block) -> str:
"""Extract the string value of a block's type.
Supports both enum-style (``block.block_type.value``) and
plain-string ``block.block_type`` conventions.
"""
bt = getattr(block, "block_type", None)
if bt is None:
return "TEXT"
return getattr(bt, "value", str(bt))
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