ocr-document

# OCR & Document Processing Extract text from PDFs, scanned images, and documents. ## PDF Text Extraction (PyMuPDF) Best choice for text-based PDFs: ```bash pip install pymupdf ``` ```python import pymupdf doc = pymupdf.open("file.pdf") for page in doc: text = page.get_text() print(text) # All pages at once full_text = "\n".join(page.get_text() for page in doc) ``` ## PDF → Markdown (marker-pdf) High-quality conversion preserving structure: ```bash pip install marker-pdf marker_single file.pdf output_dir/ --output_format markdown ``` ## Image OCR ### Surya OCR (Modern ML-based, best for Chinese) ```bash pip install surya-ocr surya_ocr image.png --langs zh,en ``` ### Pytesseract (Traditional, widely available) ```bash # Install Tesseract engine first brew install tesseract tesseract-lang # macOS apt install tesseract-ocr tesseract-ocr-chi-sim # Linux pip install pytesseract Pillow ``` ```python import pytesseract from PIL import Image text = pytesseract.image_to_string( Image.open("scan.png"), lang="chi_sim+eng" ) ``` ## Script ```bash python3 scripts/extract_document.py document.pdf python3 scripts/extract_document.py scan.png python3 scripts/extract_document.py report.pdf --output extracted.txt ``` Auto-detects format by extension: PDF → pymupdf, DOCX → python-docx, Image → pytesseract. OCR language is controlled by system Tesseract config (e.g., `chi_sim+eng` default). ## Tips - For scanned PDFs, extract images first then OCR each page - Preprocessing (deskew, contrast) improves OCR accuracy - Chinese OCR: surya-ocr > pytesseract for accuracy