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Tesseract Update: Options and Languages

A few weeks ago we announced the first release of the tesseract package: a high quality OCR engine in R. We have now released an update with extra features.

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Installing Training Data

As explained in the first post, the tesseract system is powered by language specific training data. By default only English training data is installed. Version 1.3 adds utilities to make it easier to install additional training data.

# Download French training data
tesseract_download("fra")

Note that this function is not needed on Linux. Here you should install training data via your system package manager instead. For example on Debian/Ubuntu:

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High Performance CommonMark and Github Markdown Rendering in R

This week the folks at Github have open sourced their fork of libcmark (based on the extensive PR by Mathieu Duponchelle), which they use to render markdown text within documents, issues, comments and anything else on the Github website. The new release of the commonmark R package incorporates this library so that we can take advantage of Github quality markdown rendering in R.

The most exciting change is that the library has gained an extension mechanism to provide optional rendering features which are missing from the commonmark spec. Most notably, Github has added extentions for rendering GFM style tables and autolinks, both very useful features for R users.

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The rOpenSci geospatial suite

Geospatial data - data embedded in a spatial context - is used across disciplines, whether it be history, biology, business, tech, public health, etc. Along with community contributors, we’re working on a suite of tools to make working with spatial data in R as easy as possible.

If you’re not familiar with geospatial tools, it’s helpful to see what people do with them in the real world.

Example 1

One of our geospatial packages, geonames, is used for geocoding, the practice of either sorting out place names from geographic data, or vice versa. geonames interfaces with the open database of the same name: https://www.geonames.org/. A recent paper in PlosONE highlights a common use case. Harsch & HilleRisLambers1 asked how plant species distributions have shifted due to climate warming. They used the GNsrtm3() function in geonames, which uses Shuttle Radar Topography Mission elevation data, to fill in missing or incorrect elevation values in their dataset.

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fauxpas - HTTP conditions package

HTTP, or Hypertext Transfer Protocol is a protocol by which most of us interact with the web. When we do requests to a website in a browser on desktop or mobile, or get some data from a server in R, all of that is using HTTP.

HTTP has a rich suite of status codes describing different HTTP conditions, ranging from Success to various client errors, to server errors. R has a few HTTP client libraries - crul, curl, httr, and RCurl - each of which is slightly different. I thought it would be nice if there was a single way to do HTTP exception handling across these libraries.

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The new Tesseract package: High Quality OCR in R

Optical character recognition (OCR) is the process of extracting written or typed text from images such as photos and scanned documents into machine-encoded text. The new rOpenSci package tesseract brings one of the best open-source OCR engines to R. This enables researchers or journalists, for example, to search and analyze vast numbers of documents that are only available in printed form.

People looking to extract text and metadata from pdf files in R should try our pdftools package.

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