Package: pysseract
PysseractA Python binding toTesseract API. Tesseract is an open-source tool made available by Google for Optical Character Recognition (OCR) - that is, getting a computer to read the text in an image. Tesseract allows you to perform this task at a number of levels of granularity (one character at a time, one word at a time, and so on), by segmenting the page in a number of different ways (by assuming the whole page is one lump of text, or one line, or sparsely located throughout the source image), and with a number of different language models including ones you have built (pre-built models are available athttps://github.com/tesseract-ocr/tessdataamong other places).Pip 19.3.1 or greater is required if you're installing the wheel for this package, otherwise just install the source. On Linux, if you install the wheel Tesseract comes included. You will however need to provide the Tesseract models. An example of how you might do this with English on a linux system is as follows:curl-Ohttps://raw.githubusercontent.com/tesseract-ocr/tessdata_fast/4.0.0/eng.traineddata
mkdir-p/usr/local/share/tessdata/&&sudomveng.traineddata/usr/local/share/tessdata/The reason the file is being put in to/usr/local/share/tessdata/is because that is the default value forTESSDATA_PREFIX, an environment variable that Tesseract uses to locate model files. You're free to override the value ofTESSDATA_PREFIX, of course.Documentationis hosted onreadthedocs.Basic usageIn order to just get all the text from an image and concatenate it into a string, run the following:importpysseractt=pysseract.Pysseract()t.SetImageFromPath('tests/001-helloworld.png')print(t.utf8Text)If instead you want to iterate through the text boxes found in an image at the TEXTLINE level (coarser-grained than WORD, but also lower-level than BLOCK), then you might run the following:withpysseract.Pysseract()ast:boxes=[]text=[]conf=[]LEVEL=pysseract.PageIteratorLevel.TEXTLINEforbox,text,confidenceint.IterAt(LEVEL):lines.append(text)boxes.append(box)confidence.append(conf)A third possibility is that you may want to control how exactly the image is segmented. This is done before instantiating aResultIterator, as follows:withpysseract.Pysseract()ast:t.pageSegMode=pysseract.PageSegMode.SINGLE_BLOCKt.SetImageFromPath("002-quick-fox.jpg")t.SetSourceResolution(70)boxes=[]text=[]conf=[]LEVEL=pysseract.PageIteratorLevel.TEXTLINEforbox,text,confidenceint.IterAt(LEVEL):lines.append(text)boxes.append(box)confidence.append(conf)Finally, if you want to work with the low-level iterator built into Tesseract, the below code will work for you. This is primarily intended for people who want fine-grain control when searching through the results. For instance, if you want to look at the first paragraph, jump to the next word, then the next block after that, then the next symbol after that, you would use this approach:t=pysseract.Pysseract()t.SetImageFromPath("002-quick-fox.jpg")resIter=t.GetIterator()boxes=[]lines=[]confidence=[]# First, look at the paragraph levellevel=pysseract.PageIteratorLevel.PARAboxes.append(resIter.BoundingBox(level))lines.append(resIter.GetUTF8Text(level))confidence.append(resIter.Confidence(level))# Now the next word after the paragraph we just looked atlevel=pysseract.PageIteratorLevel.WORDresIter.Next(level)boxes.append(resIter.BoundingBox(level))lines.append(resIter.GetUTF8Text(level))confidence.append(resIter.Confidence(level))# Now the next blocklevel=pysseract.PageIteratorLevel.BLOCKresIter.Next(level)boxes.append(resIter.BoundingBox(level))lines.append(resIter.GetUTF8Text(level))confidence.append(resIter.Confidence(level))# Lastly, look at the next symbol after the block we just looked atlevel=pysseract.PageIteratorLevel.SYMBOLresIter.Next(level)boxes.append(resIter.BoundingBox(level))lines.append(resIter.GetUTF8Text(level))confidence.append(resIter.Confidence(level))Building the packageRequirementsgcc/clang with at least c++11 supportlibtesseract, libtesseract-dev (equivalent on non-Debian/Ubuntu systems)pybind11>=2.2python3setup.pybuildinstalltestBuilding the documentationpipinstallsphinxsphinx_rtd_themem2r
python3setup.pybuild_sphinxYou should find the generated html inbuild/sphinx.ContributeLook atTesseract BaseAPIand import those functions of interest topymodule.cpp.Please write a brief description in your wrapper function like those already inpymodule.cpp.Referencebasic pybind11class based pybind11compiling with pybind11LICENSEMIT