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form-tools-0.1.2
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-
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | form-tools-0.1.2 |
| نام | form-tools |
| نسخه کتابخانه | 0.1.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | gwionap |
| ایمیل نویسنده | gwion.aprhobat@justice.gov.uk |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/form-tools/ |
| مجوز | - |
# form-tools
The raw data for many case management and data systems exist as paper forms. `form-tools` is a package to help with preprocessing scanned images of these paper forms for further analysis and / or processing. It does this by making use of a template for the form to match and align scanned versions of the document to it, before taking thumbnails of the fields in the scanned document.
## Before you begin
* `form-tools` makes use of the [`pdf2image`](https://github.com/Belval/pdf2image) package for converting document images stored as pdf to image files. As such, you'll need to install `poppler`. See the `pdf2image` readme for guidance on how to do so.
* The current default OCR engine for matching pages in a form template to its scanned image is [`tesseract`](https://github.com/tesseract-ocr/tesseract). Please follow the instructions at the link for how to install it.
* Computer vision is performed by using the `opencv` library. This project makes use of the pre-compiled python library for `opencv` which will be installed by default but you may wish to install `opencv` from source instead.
On Ubuntu, you can install all the necessary packages by running
```
sudo apt-get install tesseract-ocr libtesseract-dev libleptonica-dev pkg-config poppler-utils
```
## Installation
To install the library run:
```
pip install form-tools
```
## Basic use
### Extracting form metadata
Say you have a form with a pdf template `my_form.pdf`. To pre-process scanned copies of the form you'll first need to create an image directory for your template as well as a `FormMetadata` compliant json file.
To do this from the command line and output the metadata to `my_form_meta.json` and your images to a directory `template_images` you would run:
```
form-tools extract-meta my_form.pdf my_form_meta.json --form-image-directory template_images
```
To interact with the API directly in python you should use the built in `PdfFormMetaExtractor` class.
```py
from form_tools.form_meta.extractors.pdf_form_extractor import PdfFormMetaExtractor
# Instantiate extractor
pfme = PdfFormMetaExtractor()
# Create FormMetadata object and populate
# image directory template_images
form_metadata = pfme.extract_meta(
form_template_path="my_form.pdf",
form_image_dir="template_images"
)
# Write FormMetadata to json file
form_metadata.to_json(
"my_form_meta.json",
)
```
The output metadata should contain bounding box coordinates for each field in the form that correspond to regions in the images outputted to `template_images`.
**Note**: The output metadata will not be able to be used immediately to align a scanned image to the template as the `form_identifier` key and `identifier` key for each `form_page` in the metadata will need to be populated with a valid regular expression so that the correct page in the scanned image can be compared with the correct page in the template images.
### Aligning scanned images to a template
Once you have a complete form metadata file for your template and a populated image directory you can attempt to align a scanned form, say `my_scanned_form.pdf` to the template and extract field thumbnails.
You will first need to prepare a config file to specify the `opencv` algorithms to use for the alignment process. An example `config.yaml` would be as follows:
```yaml
detector:
name: SIFT
matcher:
id: FLANN
args:
- algorithm: 1
trees: 5
- check: 50
knn: 2
proportion: 0.7
ocr_options:
rotation_engine: tesseract
text_extraction_engine: tesseract
pass_directory: s3://my-bucket/pass_directory
fail_directory: s3://my-bucket/fail_directory
form_metadata_directory: metadata
```
This config specifies that the `SIFT` algorithm should be used for keypoint detection and the `FLANN` algorithm should be used for keypoint matching, with 70% of the best keypoints kept (using KNN to decide on which of these are best). Also, note that we've put the output metadata in a `metadata` subdirectory in our working directory.
To align the scanned image from the command line you would then run:
```
form-tools process-form my_scanned_form.pdf config.yaml
```
To interact with the API directly in python you would use the `FormOperator` class.
```py
from form_tools.form_operators import FormOperator
form_operator = FormOperator.create_from_config("config.yaml")
_ = form_operator.run_full_pipeline(
form_path="my_scanned_form.pdf",
pass_dir="s3://my-bucket/pass_directory",
fail_dir="s3://my-bucket/fail_directory",
form_meta_directory="metadata",
)
```
> **Note**: The scanned image could be stored in an AWS S3 bucket. In that case you would pass the S3 path (e.g. `s3://my-bucket/my_scanned_form.pdf`). Only the config and metadata directory need to be located in your local working directory.
## Running documentation locally
`mkdocs` is used to document `form-tools`. To run the documentation locally, run `mkdocs serve` on the command line and follow the link to the local host.
نیازمندی
| مقدار | نام |
|---|---|
| >=2.17.0,<3.0.0 | awswrangler |
| >=1.4.1,<2.0.0 | dataengineeringutils3 |
| >=9.2.0,<10.0.0 | Pillow |
| >=4.6.0.66,<5.0.0.0 | opencv-python |
| >=1.16.0,<2.0.0 | pdf2image |
| >=0.3.9,<0.4.0 | pytesseract |
| >=20220524,<20220525 | pdfminer-six |
| >=4.7.2,<5.0.0 | jsonschema |
| >=1.10.2,<2.0.0 | mojap-metadata |
| >=1.10.2,<2.0.0 | pydantic |
| >=2.1.0,<3.0.0 | charset-normalizer |
| >=v2.5.2,<3.0.0 | tesserocr |
| >=v1.3.3,<2.0.0 | arrow-pd-parser |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.9,<3.11 | Python |
نحوه نصب
نصب پکیج whl form-tools-0.1.2:
pip install form-tools-0.1.2.whl
نصب پکیج tar.gz form-tools-0.1.2:
pip install form-tools-0.1.2.tar.gz