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 image
fnord
>>> 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:输入的image的名字
outbase: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 Google
http://code.google.com/p/pytesser/
by Michael J.T. O'Kelly
V 0.0.2, 5/26/08"""
 
 

import Image
import subprocess
import os
import StringIO
 
import util
import errors
 
 
tesseract_exe_name = 'dlltest' # Name of executable to be called at command line
scratch_image_name = "temp.bmp" # This file must be .bmp or other Tesseract-compatible format
scratch_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 result
 
def 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 Google
http://code.google.com/p/pytesser/
by Michael J.T. O'Kelly
V 0.0.1, 3/10/07"""
 
import Image
import subprocess
import util
import errors
 
tesseract_exe_name = 'tesseract' # Name of executable to be called at command line
scratch_image_name = "temp.bmp" # This file must be .bmp or other Tesseract-compatible format
scratch_text_name_root = "temp" # Leave out the .txt extension
cleanup_scratch_flag = True  # Temporary files cleaned up after OCR operation
 
def 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 text
 
def 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:
                raise
    finally:
        if cleanup:
            util.perform_cleanup(scratch_image_name, scratch_text_name_root)
    return text
    
 
if __name__=='__main__':
    im = Image.open('phototest.tif')
    text = image_to_string(im)
    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)
    print "fnord.tif contents:", text
    text = 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