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What is Unified OCR?

The Unified OCR system in Upsonic provides a consistent interface for optical character recognition across multiple OCR engines. Instead of learning different APIs for each OCR provider, you use a single OCR class that works seamlessly with EasyOCR, RapidOCR, Tesseract, DeepSeek, and PaddleOCR. The OCR class serves as a high-level orchestrator that:
  • Manages multiple OCR provider backends with a unified API
  • Handles image preprocessing (rotation correction, contrast enhancement, noise reduction)
  • Converts PDFs to images with configurable DPI
  • Tracks confidence scores and bounding box detection
  • Collects performance metrics and processing statistics
  • Provides provider-specific features and optimizations
from upsonic.ocr import OCR
from upsonic.ocr.easyocr import EasyOCR

# Create OCR instance
ocr = OCR(EasyOCR, languages=['en'], rotation_fix=True)

# Extract text
text = ocr.get_text('document.pdf')
print(text)

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How Unified OCR Works

The OCR system follows a clear processing pipeline:
  1. File Preparation: Validates file existence and format (supports .png, .jpg, .jpeg, .bmp, .tiff, .tif, .webp, .pdf)
  2. PDF Conversion: If the file is a PDF, converts each page to images at the specified DPI
  3. Image Preprocessing: Optionally applies rotation correction, contrast enhancement, and noise reduction
  4. OCR Processing: Processes each image through the selected provider’s engine
  5. Result Aggregation: Combines results from multiple pages, calculates average confidence scores
  6. Metrics Tracking: Updates processing statistics for performance analysis
from upsonic.ocr import OCR
from upsonic.ocr.rapidocr import RapidOCR

# Create OCR with preprocessing
ocr = OCR(
    RapidOCR,
    languages=['en'],
    rotation_fix=True,
    enhance_contrast=True,
    pdf_dpi=300
)

# Process file - returns detailed results
result = ocr.process_file('document.pdf')

print(f"Text: {result.text}")
print(f"Confidence: {result.confidence:.2%}")
print(f"Pages: {result.page_count}")
print(f"Processing time: {result.processing_time_ms:.2f}ms")