tesseract: Tesseract OCR
In tesseract: Open Source OCR Engine for R

Description Usage Arguments Details References See Also Examples

Extract text from an image. Requires that you have training data for the language you are reading. Works best for images with high contrast, little noise and horizontal text.

ocr(image, engine = tesseract("eng"))

tesseract(language = NULL, datapath = NULL, options = NULL,
  cache = TRUE)

`image`	file path, url, or raw vector to image (png, tiff, jpeg, etc)
`engine`	a tesseract engine created with `tesseract()`
`language`	string with language for training data. Usually defaults to `eng`
`datapath`	path with the training data for this language. Default uses the system library.
`options`	a named list with tesseract engine options
`cache`	use a cached version of this training data if available

Tesseract uses training data to perform OCR. Most systems default to English training data. To improve OCR performance for other langauges you can to install the training data from your distribution. For example to install the spanish training data:

tesseract-ocr-spa (Debian, Ubuntu)
tesseract-langpack-spa (Fedora, EPEL)

On Windows and MacOS you can install languages using the tesseract_download function which downloads training data directly from github and stores it in a the path on disk given by the TESSDATA_PREFIX variable.

Tesseract training data

Other tesseract: tesseract_download

# Simple example
text <- ocr("https://jeroen.github.io/images/testocr.png")
cat(text)

## Not run: 
# Full roundtrip test: render PDF to image and OCR it back to text
curl::curl_download("https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf", "R-intro.pdf")
orig <- pdftools::pdf_text("R-intro.pdf")[1]

# Render pdf to png image
img_file <- pdftools::pdf_convert("R-intro.pdf", format = 'tiff', pages = 1, dpi = 400)

# Extract text from png image
text <- ocr(img_file)
unlink(img_file)
cat(text)

## End(Not run)

engine <- tesseract(options = list(tessedit_char_whitelist = "0123456789"))