https://github.com/tesseract-ocr/tesseract/wiki
https://github.com/UB-Mannheim/tesseract/wiki
C:\Users\Public\py36\Lib\site-packages\pytesseract
#!/usr/bin/env python
\'\'\'
Python-tesseract. For more information: https://github.com/madmaze/pytesseract
\'\'\'
try:
import Image
except ImportError:
from PIL import Image
import os
import sys
import subprocess
from pkgutil import find_loader
import tempfile
import shlex
from glob import iglob
numpy_installed = True if find_loader(\'numpy\') is not None else False
if numpy_installed:
from numpy import ndarray
__all__ = [\'image_to_string\']
# CHANGE THIS IF TESSERACT IS NOT IN YOUR PATH, OR IS NAMED DIFFERENTLY
#tesseract_cmd = \'tesseract\'
#tesseract_cmd = \'C:\Users\Public\py36\Lib\site-packages\pytesseract\gImageReader_3.2.1_qt5_x86_64_tesseract4.0.0.git2f10be5.exe\'
tesseract_cmd = \'C:/Users/Public/py36/Lib/site-packages/pytesseract/gImageReader_3.2.1_qt5_x86_64_tesseract4.0.0.git2f10be5.exe\'
tesseract_cmd = \'C:/Program Files (x86)/gImageReader/gimagereader-qt5.exe\'
tesseract_cmd = \'C:\Program Files (x86)\Tesseract-OCR\tesseract.exe\'
tesseract_cmd = \'C:/Program Files (x86)/Tesseract-OCR/tesseract.exe\'
class TesseractError(Exception):
def __init__(self, status, message):
self.status = status
self.message = message
self.args = (status, message)
def get_errors(error_string):
return u\' \'.join(
line for line in error_string.decode(\'utf-8\').splitlines()
).strip()
def cleanup(temp_name):
\'\'\' Tries to remove files by filename wildcard path. \'\'\'
for filename in iglob(temp_name + \'*\'):
try:
os.remove(filename)
except OSError:
pass
def run_tesseract(input_filename,
output_filename_base,
lang=None,
boxes=False,
config=None,
nice=0):
\'\'\'
runs the command:
`tesseract_cmd` `input_filename` `output_filename_base`
returns the exit status of tesseract, as well as tesseract\'s stderr output
\'\'\'
command = []
if not sys.platform.startswith(\'win32\') and nice != 0:
command += (\'nice\', \'-n\', str(nice))
command += (tesseract_cmd, input_filename, output_filename_base)
if lang is not None:
command += (\'-l\', lang)
if config:
command += shlex.split(config)
if boxes:
command += (\'batch.nochop\', \'makebox\')
proc = subprocess.Popen(command, stderr=subprocess.PIPE)
status_code, error_string = proc.wait(), proc.stderr.read()
proc.stderr.close()
return status_code, error_string
def prepare(image):
if isinstance(image, Image.Image):
return image
if numpy_installed and isinstance(image, ndarray):
return Image.fromarray(image)
raise TypeError(\'Unsupported image object\')
def image_to_string(image, lang=None, boxes=False, config=None, nice=0):
\'\'\'
Runs tesseract on the specified image. First, the image is written to disk,
and then the tesseract command is run on the image. Tesseract\'s result is
read, and the temporary files are erased.
Also supports boxes and config:
if boxes=True
"batch.nochop makebox" gets added to the tesseract call
if config is set, the config gets appended to the command.
ex: config="-psm 6"
If nice is not set to 0, Tesseract process will run with changed priority.
Not supported on Windows. Nice adjusts the niceness of unix-like processes.
\'\'\'
image = prepare(image)
if len(image.getbands()) == 4:
# In case we have 4 channels, lets discard the Alpha.
image = image.convert(\'RGB\')
temp_name = tempfile.mktemp(prefix=\'tess_\')
input_file_name = temp_name + \'.bmp\'
output_file_name_base = temp_name + \'_out\'
output_file_name = output_file_name_base + \'.txt\'
if boxes:
output_file_name = output_file_name_base + \'.box\'
try:
image.save(input_file_name)
status, error_string = run_tesseract(input_file_name,
output_file_name_base,
lang=lang,
boxes=boxes,
config=config,
nice=nice)
if status:
raise TesseractError(status, get_errors(error_string))
with open(output_file_name, \'rb\') as output_file:
return output_file.read().decode(\'utf-8\').strip()
finally:
cleanup(temp_name)
def main():
if len(sys.argv) == 2:
filename, lang = sys.argv[1], None
elif len(sys.argv) == 4 and sys.argv[1] == \'-l\':
filename, lang = sys.argv[3], sys.argv[2]
else:
sys.stderr.write(\'Usage: python pytesseract.py [-l lang] input_file\n\')
exit(2)
try:
print(image_to_string(Image.open(filename), lang=lang))
except IOError:
sys.stderr.write(\'ERROR: Could not open file "%s"\n\' % filename)
exit(1)
if __name__ == \'__main__\':
main()
from PIL import Image
import pytesseract
import os.path
img_dir = \'C:\\Users\\sas\\PycharmProjects\\py_win_to_unix\\crontab_chk_url\\personas\\trunk\\plugins\\pyos\\\'
img_n = \'en1.PNG\'
img_n = \'en1.PNG\'
img = \'{}{}\'.format(img_dir, img_n)
chk_exist=os.path.isfile(img)
# d=Image.open(\'pil0.PNG\')
# 上面都是导包，只需要下面这一行就能实现图片文字识别
text = pytesseract.image_to_string(Image.open(img), lang=\'eng\') #chi_sim
print(text)
d = 5
Python人工智能之图片识别，Python3一行代码实现图片文字识别 - 邱石的专栏 - CSDN博客 http://blog.csdn.net/qiushi_1990/article/details/78041375
对新浪验证码的识别结果为空字符串】
for i in range(1, 9):
img = \'t0 (1).png\'.replace(\'1\', str(i))
print(img)
img = \'{}{}\'.format(img_dir, img)
print(os.path.isfile(img))
text = pytesseract.image_to_string(Image.open(img), lang=\'chi_sim\') # chi_sim eng
print(text)
text = pytesseract.image_to_string(Image.open(img), lang=\'jpn\') # chi_sim eng jpn
q爽UAG
影像输入
-
二值化：由于彩色图像所含信息量过于巨大，在对图像中印刷体字符进行识别处理前，需要对图像进行二值化处理，使图像只包含黑色的前景信息和白色的背景信息，提升识别处理的效率和精确度。
-
图像降噪：由于待识别图像的品质受限于输入设备、环境、以及文档的印刷质量，在对图像中印刷体字符进行识别处理前，需要根据噪声的特征对待识别图像进行去噪处理，提升识别处理的精确度。
对比识别
人工校正
结果输出