README.md
In soodoku/recognize: Assess Quality of OCR
Recognize: Assess OCR Quality
Testing Quality
Say you run 10,000 documents through an OCR software. And now you want to know how well did the software do in recognizing the text. To do that -- a simple solution exists. Take a random sample of the documents. Get humans to transcribe the sample. Call the human transcriptions, the gold standard. Compare the OCR text to the gold standard. In particular, calculate the edit distance between the two documents.
Small courtesies may be neccessary --- removing extra spaces for one. Whenever there are images in the document with no text, OCR software typically add loads of extra space. We would want to account for that.
More complex formulations of this simple plan are easily apprehended. The above method doesn't take account of text decorations, headers etc. And capturing these may be essential. Extensions to unicode would also be useful. Analysis of how well we have done with regards to more complex data structures like tables needs further thought. But a start.
Installation
To get the current development version from github:
# install.packages("devtools")
devtools::install_github("soodoku/recognize")
The package depends on readr and RecordLinkage
Usage
setwd(path.package("recognize"))
compare_txt("inst/extdata/abbyyR_wisc_out/PA_Casey_Auditor_General", "inst/extdata/gold_wisc_out/PA_Casey_Auditor_General")
## 163
License
Scripts are released under GNU V3.
soodoku/recognize documentation built on May 30, 2019, 6:30 a.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Recognize: Assess OCR Quality
Testing Quality
Say you run 10,000 documents through an OCR software. And now you want to know how well did the software do in recognizing the text. To do that -- a simple solution exists. Take a random sample of the documents. Get humans to transcribe the sample. Call the human transcriptions, the gold standard. Compare the OCR text to the gold standard. In particular, calculate the edit distance between the two documents.
Small courtesies may be neccessary --- removing extra spaces for one. Whenever there are images in the document with no text, OCR software typically add loads of extra space. We would want to account for that.
More complex formulations of this simple plan are easily apprehended. The above method doesn't take account of text decorations, headers etc. And capturing these may be essential. Extensions to unicode would also be useful. Analysis of how well we have done with regards to more complex data structures like tables needs further thought. But a start.
Installation
To get the current development version from github:
# install.packages("devtools")
devtools::install_github("soodoku/recognize")
The package depends on readr and RecordLinkage
Usage
setwd(path.package("recognize"))
compare_txt("inst/extdata/abbyyR_wisc_out/PA_Casey_Auditor_General", "inst/extdata/gold_wisc_out/PA_Casey_Auditor_General")
## 163
License
Scripts are released under GNU V3.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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