Name | docling-parse JSON |
Version |
3.4.0
JSON |
| download |
home_page | None |
Summary | Simple package to extract text with coordinates from programmatic PDFs |
upload_time | 2025-02-18 10:59:01 |
maintainer | Peter Staar |
docs_url | None |
author | Peter Staar |
requires_python | <4.0,>=3.9 |
license | MIT |
keywords |
docling
pdf
parser
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
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coveralls test coverage |
No coveralls.
|
# Docling Parse
[](https://pypi.org/project/docling-parse/)
[](https://pypi.org/project/docling-parse/)
[](https://python-poetry.org/)
[](https://github.com/pybind/pybind11/)
[](https://github.com/DS4SD/docling-parse/)
[](https://opensource.org/licenses/MIT)
Simple package to extract text, paths and bitmap images with coordinates from programmatic PDFs. This package is used in the [Docling](https://github.com/DS4SD/docling) PDF conversion. Below, we show a few output of the latest parser with char, word and line level output for text, in addition to the extracted paths and bitmap resources.
To do the visualizations yourself, simply run (change `word` into `char` or `line`),
```sh
poetry run python ./docling_parse/visualize.py -i <path-to-pdf-file> -c word --interactive
```
<table>
<tr>
<th>original</th>
<th>char</th>
<th>word</th>
<th>line</th>
</tr>
<tr>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_1.orig.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_1.char.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_1.word.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_1.line.png" alt="screenshot" width="170"/></td>
</tr>
<tr>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_3.orig.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_3.char.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_3.word.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_3.line.png" alt="screenshot" width="170"/></td>
</tr>
<tr>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_4.orig.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_4.char.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_4.word.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/ligatures_01.pdf.page_4.line.png" alt="screenshot" width="170"/></td>
</tr>
<tr>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_1.orig.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_1.char.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_1.word.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_1.line.png" alt="screenshot" width="170"/></td>
</tr>
<tr>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_4.orig.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_4.char.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_4.word.png" alt="screenshot" width="170"/></td>
<td><img src="./docs/visualisations/table_of_contents_01.pdf.page_4.line.png" alt="screenshot" width="170"/></td>
</tr>
</table>
## Quick start
Install the package from Pypi
```sh
pip install docling-parse
```
Convert a PDF (look in the [visualize.py](docling_parse/visualize.py) for a more detailed information)
```python
from docling_parse.document import SegmentedPdfPageLabel
from docling_parse.pdf_parser import DoclingPdfParser, PdfDocument
parser = DoclingPdfParser()
pdf_doc: PdfDocument = parser.load(
path_or_stream="<path-to-pdf>"
)
# PdfDocument.iterate_pages() will automatically populate pages as they are yielded.
for page_no, pred_page in pdf_doc.iterate_pages():
# iterate over the word-cells
for word in pred_page.yield_cells(label=SegmentedPdfPageLabel.WORD):
print(word.rect, ": ", word.text)
# create a PIL image with the char cells
img = pred_page.render(label=SegmentedPdfPageLabel.CHAR)
img.show()
```
Use the CLI
```sh
$ docling-parse -h
usage: docling-parse [-h] -p PDF
Process a PDF file.
options:
-h, --help show this help message and exit
-p PDF, --pdf PDF Path to the PDF file
```
## Performance Benchmarks
### Characteristics of different parser versions
<table>
<tr>
<th>Version</th>
<th>Original</th>
<th>Word-level</th>
<th>Snippet-level</th>
<th>Performance</th>
</tr>
<tr>
<th>V1</th>
<td rowspan="2"><img src="./docs/example_visualisations/2305.14962v1.pdf_page=0.png" alt="screenshot" width="100"/></td>
<td>Not Supported</td>
<td><img src="./docs/example_visualisations/2305.14962v1.pdf_page=0.v1.png" alt="v1 snippet" width="100"/></td>
<td>~0.250 sec/page </td>
</tr>
<tr>
<th>V2</th>
<!-- The "Original" column image spans from the previous row -->
<td><img src="./docs/example_visualisations/2305.14962v1.pdf_page=0.v2.original.png" alt="v1 word" width="100"/></td>
<td><img src="./docs/example_visualisations/2305.14962v1.pdf_page=0.v2.sanitized.png" alt="v2 snippet" width="100"/></td>
<td>~0.050 sec/page <br><br>[~5-10X faster than v1]</td>
</tr>
</table>
### Timings of different parser versions
We ran the v1 and v2 parser on [DocLayNet](https://huggingface.co/datasets/ds4sd/DocLayNet-v1.1). We found the following overall behavior

## Development
### CXX
To build the parse, simply run the following command in the root folder,
```sh
rm -rf build; cmake -B ./build; cd build; make
```
You can run the parser from your build folder. Example from parse_v1,
```sh
% ./parse_v1.exe -h
A program to process PDF files or configuration files
Usage:
PDFProcessor [OPTION...]
-i, --input arg Input PDF file
-c, --config arg Config file
--create-config arg Create config file
-o, --output arg Output file
-l, --loglevel arg loglevel [error;warning;success;info]
-h, --help Print usage
```
Example from parse_v2,
```sh
% ./parse_v2.exe -h
program to process PDF files or configuration files
Usage:
PDFProcessor [OPTION...]
-i, --input arg Input PDF file
-c, --config arg Config file
--create-config arg Create config file
-p, --page arg Pages to process (default: -1 for all) (default:
-1)
-o, --output arg Output file
-l, --loglevel arg loglevel [error;warning;success;info]
-h, --help Print usage
```
If you dont have an input file, then a template input file will be printed on the terminal.
### Python
To build the package, simply run (make sure [poetry](https://python-poetry.org/) is [installed](https://python-poetry.org/docs/#installing-with-the-official-installer)),
```
poetry install
```
To test the package, run:
```
poetry run pytest ./tests -v -s
```
## Contributing
Please read [Contributing to Docling Parse](https://github.com/DS4SD/docling-parse/blob/main/CONTRIBUTING.md) for details.
## References
If you use Docling in your projects, please consider citing the following:
```bib
@techreport{Docling,
author = {Deep Search Team},
month = {8},
title = {Docling Technical Report},
url = {https://arxiv.org/abs/2408.09869},
eprint = {2408.09869},
doi = {10.48550/arXiv.2408.09869},
version = {1.0.0},
year = {2024}
}
```
## License
The Docling Parse codebase is under MIT license.
For individual model usage, please refer to the model licenses found in the original packages.
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"description": "# Docling Parse\n\n[](https://pypi.org/project/docling-parse/)\n[](https://pypi.org/project/docling-parse/)\n[](https://python-poetry.org/)\n[](https://github.com/pybind/pybind11/)\n[](https://github.com/DS4SD/docling-parse/)\n[](https://opensource.org/licenses/MIT)\n\nSimple package to extract text, paths and bitmap images with coordinates from programmatic PDFs. This package is used in the [Docling](https://github.com/DS4SD/docling) PDF conversion. Below, we show a few output of the latest parser with char, word and line level output for text, in addition to the extracted paths and bitmap resources.\n\nTo do the visualizations yourself, simply run (change `word` into `char` or `line`),\n\n```sh\npoetry run python ./docling_parse/visualize.py -i <path-to-pdf-file> -c word --interactive\n```\n\n<table>\n <tr>\n <th>original</th>\n <th>char</th>\n <th>word</th>\n <th>line</th>\n </tr>\n <tr>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_1.orig.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_1.char.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_1.word.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_1.line.png\" alt=\"screenshot\" width=\"170\"/></td>\n </tr>\n <tr>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_3.orig.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_3.char.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_3.word.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_3.line.png\" alt=\"screenshot\" width=\"170\"/></td>\n </tr>\n <tr>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_4.orig.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_4.char.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_4.word.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/ligatures_01.pdf.page_4.line.png\" alt=\"screenshot\" width=\"170\"/></td>\n </tr>\n <tr>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_1.orig.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_1.char.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_1.word.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_1.line.png\" alt=\"screenshot\" width=\"170\"/></td>\n </tr>\n <tr>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_4.orig.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_4.char.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_4.word.png\" alt=\"screenshot\" width=\"170\"/></td>\n <td><img src=\"./docs/visualisations/table_of_contents_01.pdf.page_4.line.png\" alt=\"screenshot\" width=\"170\"/></td>\n </tr> \n</table>\n\n## Quick start\n\nInstall the package from Pypi\n\n```sh\npip install docling-parse\n```\n\nConvert a PDF (look in the [visualize.py](docling_parse/visualize.py) for a more detailed information)\n\n```python\nfrom docling_parse.document import SegmentedPdfPageLabel\nfrom docling_parse.pdf_parser import DoclingPdfParser, PdfDocument\n\nparser = DoclingPdfParser()\n\npdf_doc: PdfDocument = parser.load(\n path_or_stream=\"<path-to-pdf>\"\n)\n\n# PdfDocument.iterate_pages() will automatically populate pages as they are yielded.\nfor page_no, pred_page in pdf_doc.iterate_pages():\n\n # iterate over the word-cells\n for word in pred_page.yield_cells(label=SegmentedPdfPageLabel.WORD):\n print(word.rect, \": \", word.text) \n\n # create a PIL image with the char cells\n img = pred_page.render(label=SegmentedPdfPageLabel.CHAR)\n img.show()\n```\n\nUse the CLI\n\n```sh\n$ docling-parse -h\nusage: docling-parse [-h] -p PDF\n\nProcess a PDF file.\n\noptions:\n -h, --help show this help message and exit\n -p PDF, --pdf PDF Path to the PDF file\n```\n\n\n## Performance Benchmarks\n\n### Characteristics of different parser versions\n\n<table>\n <tr>\n <th>Version</th>\n <th>Original</th>\n <th>Word-level</th>\n <th>Snippet-level</th>\n <th>Performance</th>\n </tr>\n <tr>\n <th>V1</th>\n <td rowspan=\"2\"><img src=\"./docs/example_visualisations/2305.14962v1.pdf_page=0.png\" alt=\"screenshot\" width=\"100\"/></td>\n <td>Not Supported</td>\n <td><img src=\"./docs/example_visualisations/2305.14962v1.pdf_page=0.v1.png\" alt=\"v1 snippet\" width=\"100\"/></td>\n <td>~0.250 sec/page </td>\n </tr>\n <tr>\n <th>V2</th>\n <!-- The \"Original\" column image spans from the previous row -->\n <td><img src=\"./docs/example_visualisations/2305.14962v1.pdf_page=0.v2.original.png\" alt=\"v1 word\" width=\"100\"/></td>\n <td><img src=\"./docs/example_visualisations/2305.14962v1.pdf_page=0.v2.sanitized.png\" alt=\"v2 snippet\" width=\"100\"/></td>\n <td>~0.050 sec/page <br><br>[~5-10X faster than v1]</td>\n </tr>\n</table>\n\n### Timings of different parser versions\n\nWe ran the v1 and v2 parser on [DocLayNet](https://huggingface.co/datasets/ds4sd/DocLayNet-v1.1). We found the following overall behavior\n\n\n\n## Development\n\n### CXX\n\nTo build the parse, simply run the following command in the root folder,\n\n```sh\nrm -rf build; cmake -B ./build; cd build; make\n```\n\nYou can run the parser from your build folder. Example from parse_v1,\n\n```sh\n% ./parse_v1.exe -h\nA program to process PDF files or configuration files\nUsage:\n PDFProcessor [OPTION...]\n\n -i, --input arg Input PDF file\n -c, --config arg Config file\n --create-config arg Create config file\n -o, --output arg Output file\n -l, --loglevel arg loglevel [error;warning;success;info]\n -h, --help Print usage\n```\n\nExample from parse_v2,\n\n```sh\n% ./parse_v2.exe -h\nprogram to process PDF files or configuration files\nUsage:\n PDFProcessor [OPTION...]\n\n -i, --input arg Input PDF file\n -c, --config arg Config file\n --create-config arg Create config file\n -p, --page arg Pages to process (default: -1 for all) (default:\n -1)\n -o, --output arg Output file\n -l, --loglevel arg loglevel [error;warning;success;info]\n -h, --help Print usage\n```\n\nIf you dont have an input file, then a template input file will be printed on the terminal.\n\n\n### Python\n\nTo build the package, simply run (make sure [poetry](https://python-poetry.org/) is [installed](https://python-poetry.org/docs/#installing-with-the-official-installer)),\n\n```\npoetry install\n```\n\nTo test the package, run:\n\n```\npoetry run pytest ./tests -v -s\n```\n\n\n## Contributing\n\nPlease read [Contributing to Docling Parse](https://github.com/DS4SD/docling-parse/blob/main/CONTRIBUTING.md) for details.\n\n\n## References\n\nIf you use Docling in your projects, please consider citing the following:\n\n```bib\n@techreport{Docling,\n author = {Deep Search Team},\n month = {8},\n title = {Docling Technical Report},\n url = {https://arxiv.org/abs/2408.09869},\n eprint = {2408.09869},\n doi = {10.48550/arXiv.2408.09869},\n version = {1.0.0},\n year = {2024}\n}\n```\n\n## License\n\nThe Docling Parse codebase is under MIT license.\nFor individual model usage, please refer to the model licenses found in the original packages.\n\n",
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