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Add docs for file processing
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website/site/content/docs/joex/file-processing.md
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website/site/content/docs/joex/file-processing.md
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title = "File Processing"
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description = "How Docspell processes files."
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weight = 20
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insert_anchor_links = "right"
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[extra]
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mktoc = true
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+++
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When uploading a file, it is only saved to the database together with
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the given meta information. The file is not visible in the ui yet.
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Then joex takes the next such file (or files in case you uploaded
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many) and starts processing it. When processing finished, it the item
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and its files will show up in the ui.
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If an error occurs during processing, the item will be created
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anyways, so you can see it. Depending on the error, some information
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may not be available.
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Processing files may require some resources, like memory and cpu. Many
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things can be configured in the config file to adapt it to the machine
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it is running on.
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Important is the setting `docspell.joex.scheduler.pool-size` which
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defines how many tasks can run in parallel on the machine running
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joex. For machines that are not very strong, choosing a `1` is
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recommended.
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# Stages
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```
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DuplicateCheck ->
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Extract Archives ->
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Conversion to PDF ->
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Text Extraction ->
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Generate Previews ->
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Text Analysis
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```
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These steps are executed sequentially. There are many config options
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available for each step.
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## External Commands
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External programs are all configured the same way. You can change the
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command (add, remove options etc) in the config file. As an example,
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here is the `wkhtmltopdf` command that is used to convert html files
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to pdf:
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``` conf
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docspell.joex.convert {
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wkhtmlpdf {
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command = {
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program = "wkhtmltopdf"
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args = [
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"-s",
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"A4",
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"--encoding",
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"{{encoding}}",
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"--load-error-handling", "ignore",
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"--load-media-error-handling", "ignore",
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"-",
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"{{outfile}}"
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]
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timeout = "2 minutes"
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}
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working-dir = ${java.io.tmpdir}"/docspell-convert"
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}
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}
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```
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Strings in `{{…}}` are replaced by docspell with the appropriate
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values at runtime. However, based on your use case you can just set
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constant values or add other options. This might be necessary when
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there are different version installed where changes in the command
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line are required. As you see for `wkhtmltopdf` the page size is fixed
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to DIN A4. Other commands are configured like this as well.
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For the default values, please see the [configuration
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page](@/docs/configure/_index.md#joex).
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## Duplicate Check
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If specified, the uploaded file is checked via a sha256 hash, if it
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has been uploaded before. If so, it is removed from the set of
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uploaded files. You can define this with the upload metadata.
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If this results in an empty set, the processing ends.
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## Extract Archives
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If a file is a `zip` or `eml` (e-mail) file, it is extracted and its
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entries are added to the file set. The original (archive) file is kept
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in the database, but removed from further processing.
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## Conversion to PDF
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All files are converted to a PDF file. How this is done depends on the
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file type. External programs are required, which must be installed on
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the machine running joex. The config file allows to specify the exact
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commands used.
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See the section `docspell.joex.convert` in the config file.
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The following config options apply to the conversion as a whole:
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``` conf
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docspell.joex.convert {
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converted-filename-part = "converted"
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max-image-size = ${docspell.joex.extraction.ocr.max-image-size}
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}
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```
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The first setting defines a suffix that is appended to the original
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file name to name the converted file. You can set an empty string to
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keep the same filename as the original. The extension is always
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changed to `.pdf`, of course.
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The second option defines a limit for reading images. Some images may
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be small as a file but uncompressed very large. To avoid allocating
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too much memory, there is a limit. It defaults to 14mp.
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### Html
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Html files are converted with the external tool
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[wkhtmltopdf](https://wkhtmltopdf.org/). It produces quite nice
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results by using the webkit rendering engine. So the resulting PDF
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looks just like in a browser.
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### Images
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Images are converted using
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[tesseract](https://github.com/tesseract-ocr).
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This might be interesting, if you want to try a different language
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that is not available in docspell's settings yet. Tesseract also adds
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the extracted text as a separate layer to the PDF.
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For images, tesseract is configured to create a text and a pdf file.
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### Text
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Plaintext files are treated as markdown. You can modify the results by
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providing some custom css.
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The resulting HTML files are then converted to PDF via `wkhtmltopdf`
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as described above.
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### Office
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To convert office files, [Libreoffice](https://www.libreoffice.org/)
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is required and used via the command line tool
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[unoconv](https://github.com/unoconv/unoconv).
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To improve performance, it is recommended to start a libreoffice
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listener by running `unoconv -l` in a separate process.
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### PDF
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PDFs can be converted into PDFs, which may sound silly at first. But
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PDFs come in many different flavors and may not contain a separate
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text layer, making it impossible to "copy & paste" text in them. So
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you can optionally use the tool
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[ocrmypdf](https://github.com/jbarlow83/OCRmyPDF) to create a PDF/A
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type PDF file containing a text layer with the extracted text.
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It is recommended to install ocrympdf, but it also is optional. If it
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is enabled but fails, the error is not fatal and the processing will
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continue using the original pdf for extracting text. You can also
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disable it to remove the errors from the processing logs.
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The `--skip-text` option is necessary to not fail on "text" pdfs
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(where ocr is not necessary). In this case, the pdf will be converted
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to PDF/A.
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## Text Extraction
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Text extraction also depends on the file type. Some tools from the
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convert section are used here, too.
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Text is tried to extract from the original file. If that can't be done
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or results in an error, the converted file is tried next.
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### Html
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Html files are not used directly, but the converted PDF file is used
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to extract the text. This makes sure that the text is extracted you
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actually see. The conversion is done anyways and the resulting PDF
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already has a text layer.
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### Images
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For images, [tesseract](https://github.com/tesseract-ocr) is used
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again. In most cases this step is not executed, because the text has
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already been extracted in the conversion step. But if the conversion
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would have failed for some reason, tesseract is called here (with
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different options).
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### Text
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This is obviously trivial :)
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### Office
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MS Office files are processed using a library without any external
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tool. It uses [apache poi](https://poi.apache.org/) which is well
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known for these tasks.
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A rich text file (`.rtf`) is procssed by Java "natively" (using their
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standard library).
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OpenDocument files are proecessed using the ODS/ODT/ODF parser from
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tika.
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### PDF
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PDF files are first checked for a text layer. If this returns some
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text that is greater than the configured minimum length, it is used.
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Otherwise, OCR is started for the whole pdf file page by page.
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```conf
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docspell.joex {
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extraction {
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pdf {
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min-text-len = 500
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}
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}
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}
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```
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After OCR both texts are compared and the longer is used. Since PDFs
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can contain text and images, it might be safer to always do OCR, but
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this is something to choose by the user.
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PDF ocr is comprised of multiple steps. At first only the first
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`page-range` pages are extracted to avoid too long running tasks
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(someone submit an ebook for example). But you can disable this limit
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by setting a `-1`. After all, text that is not extracted, won't be
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indexed either and is therefore not searchable. It depends on your
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machine/setup.
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Another limit is `max-image-size` which defines the size of an image
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in pixel (`width * height`) where processing is skipped.
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Then [ghostscript](http://pages.cs.wisc.edu/~ghost/) is used to
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extract single pages into image files and
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[unpaper](https://github.com/Flameeyes/unpaper) is used to optimize
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the images for ocr. Unpaper is optional, if it is not found, it is
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skipped, which may be a compromise on slow machines.
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```conf
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docspell.joex {
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extraction {
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ocr {
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max-image-size = 14000000
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page-range {
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begin = 10
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}
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ghostscript {
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command {
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program = "gs"
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args = [ "-dNOPAUSE"
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, "-dBATCH"
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, "-dSAFER"
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, "-sDEVICE=tiffscaled8"
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, "-sOutputFile={{outfile}}"
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, "{{infile}}"
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]
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timeout = "5 minutes"
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}
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working-dir = ${java.io.tmpdir}"/docspell-extraction"
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}
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unpaper {
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command {
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program = "unpaper"
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args = [ "{{infile}}", "{{outfile}}" ]
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timeout = "5 minutes"
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}
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}
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tesseract {
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command {
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program = "tesseract"
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args = ["{{file}}"
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, "stdout"
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, "-l"
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, "{{lang}}"
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]
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timeout = "5 minutes"
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}
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}
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}
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}
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}
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```
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# Generating Previews
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Previews are generated from the converted PDF of every file. The first
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page of each file is converted into an image file. The config file
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allows to specify a dpi which is used to render the pdf page. The
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default is set to 32dpi, which results roughly in a 200x300px image.
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For comparison, a standard A4 is usually rendered at 96dpi, which
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results in a 790x1100px image.
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```conf
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docspell.joex {
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extraction {
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preview {
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dpi = 32
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}
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}
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}
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```
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{% infobubble(mode="warning", title="Please note") %}
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When this is changed, you must re-generate all preview images. Check
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the api for this, there is an endpoint to regenerate all preview
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images for a collective. There is also a bash script provided in the
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`tools/` directory that can be used to call this endpoint.
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{% end %}
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# Text Analysis
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This uses the extracted text to find what could be attached to the new
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item. There are multiple things provided.
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## Classification
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If you enabled classification in the config file, a model is trained
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periodically from your files. This is now used to guess a tag for the
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item.
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## Natural Language Processing
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NLP is used to find out which terms in the text may be a company or
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person that is later used to find metadata to attach to. It also uses
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your address book to match terms in the text.
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This requires to load language model files in memory, which is quite a
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lot. Also, the number of languages is much more restricted than for
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tesseract. Currently English, German and French are supported.
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Another feature that is planned, but not yet provided is to propose
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new companies/people you don't have yet in your address book.
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The config file allows some settings. You can specify a limit for
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texts. Large texts result in higher memory consumption. By default,
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the first 10'000 characters are taken into account.
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The setting `clear-stanford-nlp-interval` allows to define an idle
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time after which the model files are cleared from memory. This allows
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to be reclaimed by the OS. The timer starts after the last file has
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been processed. If you can afford it, it is recommended to disable it
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by setting it to `0`.
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