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https://github.com/andrealenzi11/py-poppleract

Python library and Web service based on Poppler Pdftotext utility and Tesseract OCR for extracting text from PDF documents
https://github.com/andrealenzi11/py-poppleract

ocr optical-character-recognition pdf-reader pdf-splitting pdf-to-text pdf2text pdftotext poppler poppleract py-poppleract tesseract tesseract-ocr text-extraction

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Python library and Web service based on Poppler Pdftotext utility and Tesseract OCR for extracting text from PDF documents

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# py-poppleract

Python library and Web service based on **Poppler Pdftotext** utility and **Tesseract OCR** 

for extracting text from PDF documents.



Often, many pdf documents are of mixed type and contain:

- machine-readable pages from which text can be extracted with pdf rendering libraries;

- **not** machine-readable pages (images) from which text can only be extracted with OCR engines.



With this tool (**Poppleract**), you can extract text from mixed documents efficiently and easily .



## How to extract text from an input pdf through the web service



### Run the Poppleract services

Build the Poppleract services image or pull it from Docker Hub:

```console

docker pull andrealenzi/poppleract-services:0.0.7

```



Run and expose on the desired port (ex. 50000) the Poppleract services:

```console

docker run -it --rm -p 50000:8080 andrealenzi/poppleract-services:0.0.7

```



See the APIs documentation:

```url

http://0.0.0.0:50000/docs

http://0.0.0.0:50000/redoc

```



### Call the Text Extraction Service

Perform a **CURL** to extract text from the specified input pdf doc:

```console

curl -X 'POST' \

  'http://0.0.0.0:50000/extract_text?minimum_chars_number=20&raw=false&physical=false&dpi=200&lang=eng&oem=3&psm=3&thresholding_method=0&preserve_interword_spaces=1' \

  -H 'accept: application/json' \

  -H 'Content-Type: multipart/form-data' \

  -F '[email protected];type=application/pdf'

```



Or perform a request with **Python**:

```python3

import requests



headers = {

    'accept': 'application/json'

}

params = {

    'minimum_chars_number': '20',

    'raw': 'false',

    'physical': 'false',

    'dpi': '200',

    'lang': 'eng',

    'oem': '3',

    'psm': '3',

    'tessdata_dir': None,

    'thresholding_method': '0',

    'preserve_interword_spaces': '1',

}

files = {

    'input_file': ('doc1.pdf', open('doc1.pdf', 'rb'), 'application/pdf')

}

response = requests.post(url='http://0.0.0.0:50000/extract_text',

                         params=params,

                         headers=headers,

                         files=files)

print(response.json())

```



Response body:

```json

{

  "file_name": "doc1.pdf", 

  "file_size_mb": 0.1771, 

  "num_extracted_chars": 762, 

  "extracted_text": "INTERNAL\n\nTEST DOC 1\nThis is a pdf document for test.\n\nThis page is machine-readable.\nThe second page of this document is NOT machine-readable, but it represents an image with text.\nThe third page of this document is again machine-readable.\n\nQwertyuiop\nAsdfghjkl\nZxcvbnm\n\nQWERTYUIOP\nASDFGHJKL\nZXCVBNM\n\n\x0c\n\n\n\nINTERNAL\n\nThis is a lot of 12 point text to test the\nocr code and see if it works on all types\nof file format.\n\nThe quick brown dog jumped over the\nlazy fox. The quick brown dog jumped\nover the lazy fox. The quick brown dog\njumped over the lazy fox. The quick\nbrown dog jumped over the lazy fox.\n\n\n\n\nINTERNAL\n\nThird and final page of this test document.\n\nQwertyuiop\nAsdfghjkl\nZxcvbnm\n\nQWERTYUIOP\nASDFGHJKL\nZXCVBNM\n\n\n\n\x0c"

}

```



## How to use programmatically *PoppleractPdfExtractor*



```python3

"""

Hybrid Approach for extract text from mixed PDFs: 

Pdftotext on machine-readable pages + Tesseract OCR on images pages

"""

from poppleract.text_extraction import PoppleractPdfExtractor



hybrid_extr_obj = PoppleractPdfExtractor(

    cache_folder="imgs/",  # Folder with doc images representing pages 

    preserve_cache=False  # Boolean flag for preserve the folder with doc images or not

)



hybrid_extr_obj.extract_text(

    in_pdf_file_path="doc1.pdf",  # Input pdf document path

    out_txt_file_path="doc1.txt",  # Output txt file path

    minimum_chars_number=20,  # For each page, we apply OCR only if we extract less than this threshold value 

    raw=False,  # Pdftotext parameter to keep strings in content stream order or not

    physical=False,  # Pdftotext parameter to maintain original physical layout or not

    dpi=200,  # Dots per Inch (DPI) used by Pdftocairo and Tesseract

    lang="eng+ita",  # Tesseract langs

    oem=3,  # Tesseract OCR Engine Mode 

    psm=3,  # Tesseract Page Segmentation Mode 

    tessdata_dir="/usr/local/share/tessdata/",  # Folder with Tesseract languages files

    thresholding_method=0,  # Tesseract parameter to select image thresholding method

    preserve_interword_spaces=1  # Tesseract option to preserve spaces

)

```



## How to use programmatically *PdfSplitter*



```python3

"""

Splitting of an input pdf document in the relative png pages

"""

from poppleract.pdf_splitting import PdfSplitter



pdf_splitter_obj = PdfSplitter()



pdf_splitter_obj.split_pdf_to_images(

    in_pdf_file_path="doc1.pdf",

    out_images_directory_path="imgs/",

    dpi=200,

    img_exportation_format="png",

    use_pdf_to_cairo=True,

    first_page=1,

    last_page=3,

    output_filename_prefix="page"

)

```