wxPython利用pytesser模块实现图片文字识别

Pytesser——OCR in Python using the Tesseract engine from Google

pytesser是谷歌OCR开源项目的一个模块，在python中导入这个模块即可将图片中的文字转换成文本。

链接：https://code.google.com/p/pytesser/

pytesser 调用了 tesseract。在python中调用pytesser模块，pytesser又用tesseract识别图片中的文字。

下面是整个过程的实现步骤：

1、首先要在code.google.com下载pytesser。https://code.google.com/p/pytesser/downloads/detail?name=pytesser_v0.0.1.zip

这个是免安装的，可以放在python安装文件夹的\Lib\site-packages\  下直接使用

pytesser里包含了tesseract.exe和英语的数据包（默认只识别英文），还有一些示例图片，所以解压缩后即可使用。

可通过以下代码测试：

>>> from pytesser import *>>> image = Image.open('fnord.tif')  # Open image object using PIL>>> print image_to_string(image)     # Run tesseract.exe on imagefnord>>> print image_file_to_string('fnord.tif')fnord

from pytesser import * #im = Image.open('fnord.tif') #im = Image.open('phototest.tif') #im = Image.open('eurotext.tif')im = Image.open('fonts_test.png')text = image_to_string(im) print text

注：该模块需要PIL库的支持。

2、解决识别率低的问题

可以增强图片的显示效果，或者将其转换为黑白的，这样可以使其识别率提升不少：

enhancer = ImageEnhance.Contrast(image1)image2 = enhancer.enhance(4)

可以再对image2调用 image_to_string识别

3、识别其他语言

tesseract是一个命令行下运行的程序，参数如下：

tesseract  imagename outbase [-l  lang]  [-psm N]  [configfile...]

imagename是输入的image的名字

outbase是输出的文本的名字，默认为outbase.txt

-l  lang  是定义要识别的的语言，默认为英文

详见http://tesseract-ocr.googlecode.com/svn-history/r725/trunk/doc/tesseract.1.html

通过以下步骤可以识别其他语言：

（1）、下载其他语言数据包：

https://code.google.com/p/tesseract-ocr/downloads/list

将语言包放入pytesser的tessdata文件夹下

接下来修改pytesser.py的参数，下面是一个例子：

"""OCR in Python using the Tesseract engine from Googlehttp://code.google.com/p/pytesser/by Michael J.T. O'KellyV 0.0.2, 5/26/08"""import Imageimport subprocessimport osimport StringIOimport utilimport errorstesseract_exe_name = 'dlltest' # Name of executable to be called at command linescratch_image_name = "temp.bmp" # This file must be .bmp or other Tesseract-compatible formatscratch_text_name_root = "temp" # Leave out the .txt extension_cleanup_scratch_flag = True  # Temporary files cleaned up after OCR operation_language = "" # Tesseract uses English if language is not given_pagesegmode = "" # Tesseract uses fully automatic page segmentation if psm is not given (psm is available in v3.01)_working_dir = os.getcwd()def call_tesseract(input_filename, output_filename, language, pagesegmode):        """Calls external tesseract.exe on input file (restrictions on types),        outputting output_filename+'txt'"""        current_dir = os.getcwd()        error_stream = StringIO.StringIO()        try:                os.chdir(_working_dir)                args = [tesseract_exe_name, input_filename, output_filename]                if len(language) > 0:                        args.append("-l")                        args.append(language)                if len(str(pagesegmode)) > 0:                        args.append("-psm")                        args.append(str(pagesegmode))                try:                        proc = subprocess.Popen(args)                except (TypeError, AttributeError):                        proc = subprocess.Popen(args, shell=True)                retcode = proc.wait()                if retcode!=0:                        error_text = error_stream.getvalue()                        errors.check_for_errors(error_stream_text = error_text)        finally:  # Guarantee that we return to the original directory                error_stream.close()                os.chdir(current_dir)def image_to_string(im, lang = _language, psm = _pagesegmode, cleanup = _cleanup_scratch_flag):        """Converts im to file, applies tesseract, and fetches resulting text.        If cleanup=True, delete scratch files after operation."""        try:                util.image_to_scratch(im, scratch_image_name)                call_tesseract(scratch_image_name, scratch_text_name_root, lang, psm)                result = util.retrieve_result(scratch_text_name_root)        finally:                if cleanup:                        util.perform_cleanup(scratch_image_name, scratch_text_name_root)        return resultdef image_file_to_string(filename, lang = _language, psm = _pagesegmode, cleanup = _cleanup_scratch_flag, graceful_errors=True):        """Applies tesseract to filename; or, if image is incompatible and graceful_errors=True,        converts to compatible format and then applies tesseract.  Fetches resulting text.        If cleanup=True, delete scratch files after operation. Parameter lang specifies used language.        If lang is empty, English is used. Page segmentation mode parameter psm is available in Tesseract 3.01.        psm values are:        0 = Orientation and script detection (OSD) only.        1 = Automatic page segmentation with OSD.        2 = Automatic page segmentation, but no OSD, or OCR        3 = Fully automatic page segmentation, but no OSD. (Default)        4 = Assume a single column of text of variable sizes.        5 = Assume a single uniform block of vertically aligned text.        6 = Assume a single uniform block of text.        7 = Treat the image as a single text line.        8 = Treat the image as a single word.        9 = Treat the image as a single word in a circle.        10 = Treat the image as a single character."""        try:                try:                        call_tesseract(filename, scratch_text_name_root, lang, psm)                        result = util.retrieve_result(scratch_text_name_root)                except errors.Tesser_General_Exception:                        if graceful_errors:                                im = Image.open(filename)                                result = image_to_string(im, cleanup)                        else:                                raise        finally:                if cleanup:                        util.perform_cleanup(scratch_image_name, scratch_text_name_root)        return result        if __name__=='__main__':        im = Image.open('phototest.tif')        text = image_to_string(im, cleanup=False)        print text        text = image_to_string(im, psm=2, cleanup=False)        print text        try:                text = image_file_to_string('fnord.tif', graceful_errors=False)        except errors.Tesser_General_Exception, value:                print "fnord.tif is incompatible filetype.  Try graceful_errors=True"                #print value        text = image_file_to_string('fnord.tif', graceful_errors=True, cleanup=False)        print "fnord.tif contents:", text        text = image_file_to_string('fonts_test.png', graceful_errors=True)        print text        text = image_file_to_string('fonts_test.png', lang="eng", psm=4, graceful_errors=True)        print text

这个是source里面提供的，其实若只要识别其他语言只要添加一个language参数就行了，下面是我的例子：

"""OCR in Python using the Tesseract engine from Googlehttp://code.google.com/p/pytesser/by Michael J.T. O'KellyV 0.0.1, 3/10/07"""import Imageimport subprocessimport utilimport errorstesseract_exe_name = 'tesseract' # Name of executable to be called at command linescratch_image_name = "temp.bmp" # This file must be .bmp or other Tesseract-compatible formatscratch_text_name_root = "temp" # Leave out the .txt extensioncleanup_scratch_flag = True  # Temporary files cleaned up after OCR operationdef call_tesseract(input_filename, output_filename, language):"""Calls external tesseract.exe on input file (restrictions on types),outputting output_filename+'txt'"""args = [tesseract_exe_name, input_filename, output_filename, "-l", language]proc = subprocess.Popen(args)retcode = proc.wait()if retcode!=0:errors.check_for_errors()def image_to_string(im, cleanup = cleanup_scratch_flag, language = "eng"):"""Converts im to file, applies tesseract, and fetches resulting text.If cleanup=True, delete scratch files after operation."""try:util.image_to_scratch(im, scratch_image_name)call_tesseract(scratch_image_name, scratch_text_name_root,language)text = util.retrieve_text(scratch_text_name_root)finally:if cleanup:util.perform_cleanup(scratch_image_name, scratch_text_name_root)return textdef image_file_to_string(filename, cleanup = cleanup_scratch_flag, graceful_errors=True, language = "eng"):"""Applies tesseract to filename; or, if image is incompatible and graceful_errors=True,converts to compatible format and then applies tesseract.  Fetches resulting text.If cleanup=True, delete scratch files after operation."""try:try:call_tesseract(filename, scratch_text_name_root, language)text = util.retrieve_text(scratch_text_name_root)except errors.Tesser_General_Exception:if graceful_errors:im = Image.open(filename)text = image_to_string(im, cleanup)else:raisefinally:if cleanup:util.perform_cleanup(scratch_image_name, scratch_text_name_root)return textif __name__=='__main__':im = Image.open('phototest.tif')text = image_to_string(im)print texttry:text = image_file_to_string('fnord.tif', graceful_errors=False)except errors.Tesser_General_Exception, value:print "fnord.tif is incompatible filetype.  Try graceful_errors=True"print valuetext = image_file_to_string('fnord.tif', graceful_errors=True)print "fnord.tif contents:", texttext = image_file_to_string('fonts_test.png', graceful_errors=True)print text

在调用image_to_string函数时，只要加上相应的language参数就可以了，如简体中文最后一个参数即为 chi_sim， 繁体中文chi_tra,

也就是下载的语言包的 XXX.traineddata 文件的名字XXX，如下载的中文包是 chi_sim.traineddata， 参数就是chi_sim :

text = image_to_string(self.im, language = 'chi_sim')

至此，图片识别就完成了。

额外附加一句：有可能中文识别出来了，但是乱码，需要相应地将text转换为你所用的中文编码方式，如：

text.decode("utf8")就可以了