Abbyy Finereader Python ✦ Premium Quality

response = self.session.post( f"self.base_url/api/v1/tasks", files=files, data=data )

FineReader Server provides a REST API for distributed OCR.

# Recognize with specific language doc.Recognize(language)

# Parse line items from full text full_text = self.fr.get_recognized_text(image_path) line_items = self._extract_line_items(full_text) abbyy finereader python

Args: input_path: Path to image or PDF output_path: Output file path (without extension) output_format: pdf, docx, xlsx, txt, html """ fine_cmd = r"C:\Program Files (x86)\ABBYY FineReader\FineReaderCmd.exe"

# Initialize (choose method) fr = FineReaderCOM() # Requires Windows

Let's combine everything. You have 1,000 scanned invoices. You need: response = self

For users with the FineReader Corporate Edition, you can use Python’s subprocess module to trigger OCR tasks via the command line. This "black-box" approach involves dropping files into a "Hot Folder" and picking up processed results from an output directory. Setting Up the Cloud OCR SDK in Python

But how do you integrate an enterprise-grade desktop tool into an automated, server-side Python workflow? This is where the magic happens.

# 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() You need: For users with the FineReader Corporate

import hashlib import pickle

result = subprocess.run(cmd, capture_output=True, text=True)

for pdf_path in Path(pdf_folder).glob("*.pdf"): doc = app.CreateDocument() doc.AddImageFile(str(pdf_path), 0, "") doc.Recognize(["English"], None)

with open(temp_txt, 'r') as f: text = f.read()