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=================
Document Content Extraction Project
=================
Introduction
====================
Document content extraction aiming to extract all information of document file and convert it to computer readable result(such as markdown file). It's subtasks including layout detection, formula detection, formula recognition, OCR and other tasks.
Project Usage
====================
With the environment properly set up, simply run the project by executing ``project/pdf2markdown/scripts/run_project.py`` .
.. code:: shell
$ python project/pdf2markdown/scripts/run_project.py --config project/pdf2markdown/configs/pdf2markdown.yaml
Project Configuration
--------------------
.. code:: yaml
inputs: assets/demo/formula_detection
outputs: outputs/pdf2markdown
visualize: True
merge2markdown: True
tasks:
layout_detection:
model: layout_detection_yolo
model_config:
img_size: 1024
conf_thres: 0.25
iou_thres: 0.45
model_path: models/Layout/YOLO/doclayout_yolo_ft.pt
formula_detection:
model: formula_detection_yolo
model_config:
img_size: 1280
conf_thres: 0.25
iou_thres: 0.45
batch_size: 1
model_path: models/MFD/YOLO/yolo_v8_ft.pt
formula_recognition:
model: formula_recognition_unimernet
model_config:
batch_size: 128
cfg_path: pdf_extract_kit/configs/unimernet.yaml
model_path: models/MFR/unimernet_tiny
ocr:
model: ocr_ppocr
model_config:
lang: ch
show_log: True
det_model_dir: models/OCR/PaddleOCR/det/ch_PP-OCRv4_det
rec_model_dir: models/OCR/PaddleOCR/rec/ch_PP-OCRv4_rec
det_db_box_thresh: 0.3
- inputs/outputs: Define the input path and the output path, respectively.
- visualize: Whether to visualize the project results. Visualized results will be saved in the outputs directory.
- merge2markdown: Whether to merge the results into markdown documents. Only simple single-column text is supported. For markdown conversion of more complex layout documents, please refer to `MinerU <https://github.com/opendatalab/MinerU>`_ .
- tasks: Define the task types, PDF document extraction includes layout detection, formula detection, formula recognition, and OCR tasks.
- For details about the parameter meanings of each task and model, see the tutorial documentation of each task.
Diverse Input Support
--------------------
The Document content extraction script in PDF-Extract-Kit supports various input formats such as ``a single image/PDF``, ``a directory of image/PDF files``.
Output result
--------------------
The extracted results of PDF documents are stored in the outputs path in the form of json. The format of json is as follows:
.. code:: json
[
{
"layout_dets": [
{
"category_type": "text",
"poly": [
380.6792698635707,
159.85058512958923,
765.1419999999998,
159.85058512958923,
765.1419999999998,
192.51073013642917,
380.6792698635707,
192.51073013642917
],
"text": "this is an example text",
"score": 0.97
},
...
],
"page_info": {
"page_no": 0,
"height": 2339,
"width": 1654,
}
},
...
]
- layout_dets: Single page of PDF or image content extraction results
- category_type: The attribution of a single piece of content, such as headings, images, inline formulas, and so on
- poly: The location coordinates of a single content block
- text: Text content of a single content block
- score: Confidence score
- page_info: Page information, including page number and page size
- page_no: Page number, counting from 0
- height: Page size: height
- width: Page size: width
If the ``merge2markdown`` parameter is True, an additional markdown file will be saved. |