OCR toolkit for arabic PDFs and directories
Project description
TRK FTZ OCR
TRK FTZ OCR is a lightweight OCR toolkit for extracting text from PDFs and folders of PDFs.
It supports single-page extraction, full PDF processing, directory processing, parallel execution, and multiple output formats.
🚀 Features
- 📄 Extract text from a single page
- 📚 Process full PDF files
- 📁 Process directories of PDFs
- ⚡ Parallel processing for speed
- 🧠 Adaptive OCR pipeline (PSM-based)
- 📊 Export results to:
- Dictionary (Python)
- TXT files (per page / per file)
- Excel (.xlsx)
📦 Installation
pip install trk-ftz-ocr
🖥️ CLI Usage
After installation, use:
trk-ftz-ocr --help
📄 Process a single PDF
Return text (default)
trk-ftz-ocr file.pdf --mode dict
Save as folder (per-page TXT files)
trk-ftz-ocr file.pdf --mode folder --output output/
Save as single Excel file
trk-ftz-ocr file.pdf --mode excel --output output.xlsx
📁 Process a directory
trk-ftz-ocr pdfs/ --mode folder --output output/
This creates:
output/
file1/
file1_page_1.txt
file1_page_2.txt
file2/
file2_page_1.txt
⚙️ Options
| Option | Description |
|---|---|
--page |
Extract a single page |
--output |
Output path (file or folder) |
--lang |
OCR language (default: ara) |
--zoom |
Render quality (default: 6) |
--parallel |
Enable parallel processing |
--mode |
Output mode: dict, file, folder, excel |
📊 Output Modes
dict
Returns Python dictionary:
{page_number: text}
file
Saves all text into a single .txt file.
folder
Saves each page as a separate .txt file.
excel
Saves results as:
file | page | text
🧠 Example (Python API)
from trk_ftz_ocr.pipeline import process
result = process(
path="file.pdf",
output_path="output/",
mode="dict",
parallel=True
)
print(result)
⚡ Performance
- Parallel page processing (ThreadPool)
- Parallel directory processing
- Lightweight preprocessing pipeline
- Adaptive OCR configuration
📌 Requirements
- Python >= 3.12
- Tesseract OCR installed on system
🛠️ Dependencies
- PyMuPDF
- pytesseract
- pillow
- tqdm
- pandas
- openpyxl
📄 License
MIT License
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