Abbyy Finereader Python -

def get_task_status(self, task_id): """Check task status.""" response = self.session.get(f"self.base_url/api/v1/tasks/task_id") return response.json()

image_files = list(input_folder.glob("*.png,jpg,jpeg,tiff,bmp"))

@ocr_with_retry(max_retries=3) def robust_ocr(input_path): # Your OCR implementation pass | Limitation | Alternative | |------------|-------------| | Windows-only (COM method) | Use CLI or Server API | | License required | Tesseract (free), Google Cloud Vision | | Slow for large batches | Use FineReader Server (distributed) | | Complex layout handling | Adobe Extract API | 11. Complete Working Example # full_pipeline.py import os from pathlib import Path import json from datetime import datetime def main(): # Setup input_folder = "./input_scans" output_folder = "./ocr_results" os.makedirs(output_folder, exist_ok=True) abbyy finereader python

def __del__(self): self.app.Quit() pythoncom.CoUninitialize() fr = FineReaderCOM() text = fr.get_recognized_text("invoice.jpg") print(text[:500]) Zonal OCR example (extract specific invoice fields) zones = [(100, 200, 400, 230), # Invoice number (100, 300, 400, 330), # Date (500, 500, 800, 800)] # Total amount invoice_data = fr.zonal_ocr("invoice.jpg", zones) print(invoice_data) Advanced: PDF Searchable Creation def create_searchable_pdf(input_pdf_path, output_pdf_path): """Convert image-only PDF to searchable PDF/A.""" fr = FineReaderCOM() doc = fr.app.CreateDocument() # Load PDF pages doc.AddImageFile(input_pdf_path, 0)

def process_invoice(self, image_path): """Extract structured data from invoice image.""" # Extract text from zones extracted = {} for field, zone in self.zones.items(): text = self.fr.zonal_ocr(image_path, [zone])[0] extracted[field] = text.strip() # Parse line items from full text full_text = self.fr.get_recognized_text(image_path) line_items = self._extract_line_items(full_text) # Parse and clean invoice = 'number': self._clean_invoice_number(extracted['invoice_number']), 'date': self._parse_date(extracted['invoice_date']), 'due_date': self._parse_date(extracted['due_date']), 'total': self._parse_amount(extracted['total_amount']), 'vendor': extracted['vendor_name'], 'vendor_address': extracted['vendor_address'], 'line_items': line_items, 'processed_at': datetime.now().isoformat() return invoice def get_task_status(self, task_id): """Check task status

# Configure PDF export settings export_params = "PDFExportMode": 1, # 1 = Text and pictures (searchable) "PDFAComplianceMode": 1, # PDF/A-1b "PreserveOriginalPageSize": True

result = subprocess.run(cmd, capture_output=True, text=True) # Invoice number (100

def submit_ocr_task(self, file_path, output_format="pdf"): """Submit a file for OCR processing.""" with open(file_path, 'rb') as f: files = 'file': (Path(file_path).name, f) data = 'outputFormat': output_format, 'language': 'English', 'recognitionAccuracy': 'high', 'documentProcessingMode': 'auto' response = self.session.post( f"self.base_url/api/v1/tasks", files=files, data=data ) return response.json()['taskId']

return result import logging from functools import wraps logging.basicConfig(level=logging.INFO) logger = logging.getLogger( name )

def zonal_ocr(self, input_path, zones, language="English"): """ OCR only specific zones (regions) on the page. Args: zones: list of (x1, y1, x2, y2) tuples in pixels """ doc = self.app.CreateDocument() page = doc.AddImageFile(input_path, 0) # Clear auto-detected regions page.Regions.Clear() # Add custom zones for (x1, y1, x2, y2) in zones: region = page.Regions.Add(x1, y1, x2, y2) region.Type = 1 # 1 = Text region # Recognize only these zones doc.Recognize(language) results = [] for region in page.Regions: results.append(region.Text) doc.Close() return results