Tool to scan and process documents to paperless
Scan and prepare your document for Paperless
The main goal of this project is to have some productive process from the document scanning to
For that we need to prepare the documents some tools that need many resources, then the idea to do it
in the background and ideally on another host like a NAS.
A consequence of that it's a not easy to put it in place, but then you will be really productive.
The interface between the user and the process is the
scan command to do the initial scan, and the file system
to verify that the result is OK (and do some advance operations describe below) and validate it.
- Scan the images optionally by using the Automatic Document Feeder
- Easily scan double-sided images using the Automatic Document Feeder
- Change the images levels
- Deskew the images
- Crop the images
- Sharpen the images (disable by default)
- Dither the images (disable by default)
- Auto rotate the images by using tesseract (To have the text on the right side)
- Assisted split, used to split a prospectus page in more pages (Requires to modify the YAML...)
- Append credit cart, used to have the two faces of a credit cart on the same page
- Be able to copy the OCR result from the PDF
On the desktop:
- Python >= 3.6
- The scanimage command, on Windows it should be able to use another command,
but it's never be tested.
This command would be an adapter that interpret the following arguments:
On the NAS:
On the desktop
$ python3 -m pip install scan-to-paperless $ sudo activate-global-python-argcomplete # optional $ echo PATH=$PATH:~/venv/bin >> ~/.bashrc
Create the configuration file on
<home_config>/scan-to-paperless.yaml (on Linux it's
# yaml-language-server: $schema=https://raw.githubusercontent.com/sbrunner/scan-to-paperless/master/scan_to_paperless/config_schema.json scan_folder: /home/sbrunner/Paperless/scan/ scanimage_arguments: # Additional argument passed to the scanimage command - --device=... # Use `scanimage --list` to get the possible values - --format=png - --mode=color - --resolution=300 default_args: ## Level # true: => do level on 15% - 85% (under 15 % will be black above 85% will be white) # false: => 0% - 100% # <number>: => (0 + <number>)% - (100 - number)% level: # If no level specified, do auto level auto_level: False # min level if no level end no auto level min_level: 15 # max level if no level end no auto level max_level: 95 ## Crop no_crop: False # Don't do any crop marging_horizontal: 9 # mm, the horizontal margin used on autodetect content marging_vertical: 6 # mm, the vertical margin used on autodetect content dpi: 300 # The DPI used to convert the mm to pixel # Sharpen sharpen: False # Do the sharpen # Dither dither: False # Do the dither ## OCR tesseract: True # Use tesseract to to an OCR on the document tesseract_lang: fra+eng # The used language
On the NAS
The Docker support is required, Personally I use a Synology DiskStation DS918+, and you can get the *.syno.json files to configure your Docker services.
docker run --name=scan-to-paperless --restart=unless-stopped --detatch \ --volume=<scan_folder>:/source \ --volume=<consume_folder>:/destination \ sbrunner/scan-to-paperless
You can set the environment variable
TRUE to get all the intermediate images.
To stop run:
docker stop scan-to-paperless docker rm scan-to-paperless
You should find a way to synchronize or using sharing to link the scan folder on your desktop and on your NAS.
You should also link the consume folder to
paperless-ngx probably just by using the same folder.
scancommand to import your document, to scan your documents.
The document is transferred to your NAS (I use Syncthing).
The documents will be processed on the NAS.
scan-process-statusto know the status of your documents.
Validate your documents.
If your happy with that remove the
REMOVE_TO_CONTINUEfile. (To restart the process remove one of the generated images, to cancel the job just remove the folder).
The process will continue his job and import the document in
Job config file
config.yaml file present in the document folder, you can find some information generated during
the processing and some can be modified.
E.g. you can modify an image angle to fix the skew, then remove a generated image for force to regenerate the images.
Add a mask
If your scanner add some margin around the scanned image it will relay case some issue the deskew and the content detection.
To solve that you can add a black and white image named
mask.png in the root folder and draw in black the
part that should not be taken in account.
Double sized scanning
Pour your sheets on the Automatic Document Feeder.
scanwith the option
Press enter to start scanning the first side of all sheets.
Put again all your sheets on the Automatic Document Feeder without turning them.
The scan utils will rotate and reorder all the sheets to get a good document.
Credit card scanning
--append-credit-card will append all the sheets vertically to have the booth face of the credit card on the same page.
Do your scan as usual with the extra option
After the process do his first pass you will have images with lines and numbers. The lines represent the detected potential split of the image, the length indicate the strength of the detection. In your config you will have something like:
assisted_split: - destinations: - 4 # Page number of the left part of the image - 1 # Same for the right page of the image image: image-1.png # name of the image limits: - margin: 0 # Margin around the split name: 0 # Number visible on the generated image value: 375 # The position of the split (can be manually edited) vertical: true # Will split the image vertically - ... source: /source/975468/7-assisted-split/image-1.png - ...
Edit your config file, you should have one more destination than the limits. If you put destination like that: 2.1, it means that it will be the first part of the page 2 and the 2.2 will be the second part.
Delete the file
After the process do his first pass you will have the final generated images.
If it's OK delete the file
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