def ocr():
import cv2.cv as cv
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
image = cv.LoadImage("eurotext.jpg", cv.CV_LOAD_IMAGE_GRAYSCALE)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
print(text, len(text))
print("Cofidence Level: %d %%" % conf)
print("Confidences of All words")
header("Method 1", "*" * 10)
confOfText = api.AllWordConfidences()
print(confOfText)
print("Number of Words:")
print("counted by tesseract: %d" % len(confOfText))
print("counted by me: %d[%d]" % (countWords(text), countWords2(text)))
if len(confOfText) != countWords(text):
print("Why the words counted by tesseract are different from mine!!!!")
header("Method 2", "*" * 10)
confs = tesseract.AllWordConfidences(api)
print(confs, len(confs))
def ocr_receipt(window,image):
"""string_int=('tesseract ' + 'TempBin' + file_name + ' '
+ RECEIPT_PATH + file_name[:-4] + '_int1')
string_int2=('tesseract ' + 'TempBin2' + file_name + ' '
+ RECEIPT_PATH + file_name[:-4] + '_int2')
string_final = ('tesseract ' + 'Final.Bin' + file_name + ' '
+ RECEIPT_PATH + file_name[:-4] + '_final')
temp = subprocess.call(string_int,shell=True)
temp = subprocess.call(string_int2,shell=True)
temp = subprocess.call(string_final,shell=True)
os.system(string_final)
print string_final"""
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist", "0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ=-,.\/:")
api.SetPageSegMode(tesseract.PSM_AUTO)
img_file = "test.png"
cv2.imwrite(img_file,image)
mbuffer=open(img_file,"rb").read()
result = tesseract.ProcessPagesBuffer(mbuffer,len(mbuffer),api)
#tesseract.SetCvImage(ocr_img,api)
#text=api.GetUTF8Text()
conf=api.MeanTextConf()
conf2=api.AllWordConfidences()
print('Result: ')
print(result)
def leerPlaca(self, binarizado):
"""
Args:
img: imagen que contiene el texto, obtenida con la
funcion cv2.imread.
Returns:
El string del texto en la imagen.
"""
cvmat_image = cv.fromarray(binarizado)
imgbincv = cv.GetImage(cvmat_image)
# GetImage fuente de un error, revisar
# Configuración del tesseract
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetVariable('tessedit_char_whitelist',
'0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ')
# PSM_SINGLE_CHAR para lectura caracter a caracter
api.SetPageSegMode(tesseract.PSM_SINGLE_CHAR)
# Enviando imagen binarizada al tesseract
tesseract.SetCvImage(imgbincv, api)
text = api.GetUTF8Text()
text = re.sub(r'\W+', '', text)
return text
def ocr(self):
if self.last_image is not None:
image = self.last_image
# Add border to keep the characters off the edges
offset = 20
height, width, channel = image.shape
image = cv2.copyMakeBorder(image,
offset,
offset,
offset,
offset,
cv2.BORDER_CONSTANT,
value=(255, 255, 255))
# Init and configure tesseract api
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
api.SetVariable("tessedit_char_whitelist", self.white_list)
# Convert to cv image to to pass to tess api
# Derived from example code here: http://blog.mimvp.com/2015/11/python-ocr-recognition/
height, width, channel = image.shape
iplimage = cv.CreateImageHeader((width, height), cv.IPL_DEPTH_8U,
channel)
cv.SetData(iplimage, image.tostring(),
image.dtype.itemsize * channel * (width))
tesseract.SetCvImage(iplimage, api)
api.Recognize(None)
ri = api.GetIterator()
level = tesseract.RIL_WORD
if (ri):
word = ri.GetUTF8Text(level)
return word
def house_add_votes_from_image(self, vote_file, vote):
# Extract the image.
with cd('/tmp'):
sh.pdfimages(vote_file, vote_file)
# Convert it to .png
image_file = vote_file + '-000.pbm'
with open(image_file, 'rb') as f:
data = f.read()
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_SINGLE_BLOCK)
whitelist = ("abcdefghijklmnopqrstuvwxyz',-.*"
"ABCDEFGHIJKLMNOPQRSTUVWXYZ ")
api.SetVariable("tessedit_char_whitelist", whitelist)
text = tesseract.ProcessPagesBuffer(data, len(data), api)
# Parse the text into a tree.
tree = with_image.Rollcall.parse(with_image.Lexer(text))
# Visit the tree and add rollcall votes to the vote object.
visitor = with_image.VoteVisitor(vote).visit(tree)
os.remove(image_file)
def __init__(self):
self.Corr = cv.CV_TM_CCORR_NORMED
self.MinCorr = 0.97
path = os.path.join(os.path.dirname(__file__), 'templates')
self.SuitTemplates = dict()
for suit in ['h', 'd', 'c', 's']:
template = cv2.imread(path + '/suits/' + suit + '.png')
if template == None:
raise Exception('Template for suit %s not found\n' % suit)
self.SuitTemplates[suit] = template
self.NumTemplates = dict()
for num in xrange(1, 13 + 1):
template = cv2.imread(path + '/numbers/%d.png' % num)
if template == None:
raise Exception('Template for number %d not found\n' % num)
self.NumTemplates[num] = template
# tesseract
if True:
self.ocr_api = tesseract.TessBaseAPI()
self.ocr_api.Init(".", "eng", tesseract.OEM_DEFAULT)
self.ocr_api.SetPageSegMode(tesseract.PSM_AUTO)
def ocr():
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
mImgFile = "eurotext.jpg"
pixImage = tesseract.pixRead(mImgFile)
api.SetImage(pixImage)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
print(text, len(text))
print("Cofidence Level: %d %%" % conf)
print("Confidences of All words")
header("Method 1", "*" * 10)
confOfText = api.AllWordConfidences()
print(confOfText)
print("Number of Words:")
print("counted by tesseract: %d" % len(confOfText))
print("counted by me: %d[%d]" % (countWords(text), countWords2(text)))
if len(confOfText) != countWords(text):
print("Why the words counted by tesseract are different from mine!!!!")
header("Method 2", "*" * 10)
confs = tesseract.AllWordConfidences(api)
print(confs, len(confs))
def __init__(self):
""""""
super(Application, self).__init__()
self.file_roots_and_names = []
self.potential_problem_files = []
self.searchable_files = []
self.tesseract_api = tesseract.TessBaseAPI()
self.tesseract_api.Init(".", "eng", tesseract.OEM_DEFAULT)
self.tesseract_api.SetPageSegMode(tesseract.PSM_AUTO)
def tesseract_cv_ocr(imgname):
image = cv.LoadImage(imgname)
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
#api.SetPageSegMode(tesseract.PSM_SINGLE_WORD)
api.SetPageSegMode(tesseract.PSM_AUTO)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
return text
def __init__(self):
'''
初始化tess
'''
self.tessApi = tesseract.TessBaseAPI()
self.tessApi.Init(config.TESSDATA_PREFIX, config.TESSDATA_LANG,
tesseract.OEM_DEFAULT)
self.tessApi.SetVariable("tessedit_char_whitelist",
config.TESSDATA_UNICHARSET)
self.tessApi.SetPageSegMode(tesseract.PSM_SINGLE_LINE)
def ocr_number(img):
api = tesseract.TessBaseAPI()
api.Init("C:\Program Files (x86)\Tesseract-OCR", "eng",
tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist", "0123456789+-")
api.SetPageSegMode(tesseract.PSM_SINGLE_LINE)
cv_im = convert_to_IplImage(img)
tesseract.SetCvImage(cv_im, api)
return api.GetUTF8Text().split("\n")[0] # OCR結果から余計な改行を取り除く
def auto_search():
# click search button
genymotion_session.console.mouse.put_mouse_event_absolute(660,290,0,0,0)
genymotion_session.console.mouse.put_mouse_event_absolute(660,290,0,0,1)
genymotion_session.console.mouse.put_mouse_event_absolute(660,290,0,0,0)
sleep(10)
# processing
subprocess.call("adb shell screencap -p /sdcard/screen.png", shell=True)
subprocess.call("adb pull /sdcard/screen.png /tmp/screen.png", shell=True)
im = Image.open("/tmp/screen.png")
#box = (60, 80, 165, 180)
#box = (53, 72, 140, 165)
box = (57, 75, 140, 138)
loot = im.crop(box).convert('L')
loot = ImageOps.invert(loot)
loot.save("/tmp/loot.png", "png")
api = tesseract.TessBaseAPI()
api.Init("/home/mrtux/app/bin/", "coc",tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist", "0123456789")
api.SetPageSegMode(tesseract.PSM_AUTO)
image = cv.LoadImage("/tmp/loot.png", cv.CV_LOAD_IMAGE_UNCHANGED)
tesseract.SetCvImage(image,api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
total_loot = text.splitlines()
gold_loot, elixir_loot = total_loot[0:2]
gold_loot_text_element = gold_loot.split(" ")
elixir_loot_text_element = elixir_loot.split(" ")
for i in range(len(gold_loot_text_element)):
if len(gold_loot_text_element[i]) > 3:
gold_loot_text_element[i] = gold_loot_text_element[i][1:]
for i in range(len(elixir_loot_text_element)):
if len(elixir_loot_text_element[i]) > 3:
elixir_loot_text_element[i] = elixir_loot_text_element[i][1:]
gold_expr = gold_loot.find(" ") == 3 and int(gold_loot_text_element[0]) >= 200
elixir_expr = elixir_loot.find(" ") == 3 and int(elixir_loot_text_element[0]) >= 200
print gold_loot
print gold_loot_text_element
print elixir_loot
print elixir_loot_text_element
if gold_expr and elixir_expr:
subprocess.call("mplayer /home/mrtux/app/bin/gun.mp3", shell=True)
api.End()
return True
return False
def recognize(image):
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_SINGLE_BLOCK)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
image = None
print text
print "Confidence: " + str(conf)
return text, conf
def ocr(self, image):
"""Return OCR result."""
api = tesseract.TessBaseAPI()
api.Init(".", "big", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_SINGLE_BLOCK)
h, w = image.shape
w_step = w * image.dtype.itemsize
iplimage = cv.CreateImageHeader((w, h), cv.IPL_DEPTH_8U, 1)
cv.SetData(iplimage, image.tostring(), image.dtype.itemsize * (w))
tesseract.SetCvImage(iplimage, api)
hocr = api.GetHOCRText(0)
return hocr
def detect(self):
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist", "0123456789 ")
api.SetPageSegMode(tesseract.PSM_AUTO)
f = open(self.tempFile, "rb")
mBuffer = f.read()
f.close()
self.result = tesseract.ProcessPagesBuffer(mBuffer, len(mBuffer), api)
return self
def recognize(mImgFile):
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
eng = "0123456789abcdefghijklmnopqrstuvwxyz."
digit = "0123456789"
api.SetVariable("tessedit_char_whitelist", digit)
api.SetPageSegMode(tesseract.PSM_AUTO)
mBuffer = open(mImgFile, "rb").read()
result = tesseract.ProcessPagesBuffer(mBuffer, len(mBuffer), api)
print "result(ProcessPagesBuffer)=", result
api.End()
def getCaptcha():
grayScale = cv.LoadImage(
'https://my.ebharatgas.com/bharatgas/MyCaptcha.png',
cv.CV_LOAD_IMAGE_GRAYSCALE)
cv.Threshold(gray, gray, 231, 255, cv.CV_THRESH_BINARY)
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist",
"0123456789abcdefghijklmnopqrstuvwxyz")
api.SetPageSegMode(tesseract.PSM_SINGLE_WORD)
tesseract.SetCvImage(gray, api)
print(api.GetUTF8Text())
def updateOCR(frame):
api = tesseract.TessBaseAPI()
api.SetVariable("tessedit_char_whitelist", WHITELIST)
api.Init("C:\Program Files (x86)\Tesseract-OCR", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
bitmap = cv2.cv.CreateImageHeader((frame.shape[1], frame.shape[0]), cv2.IPL_DEPTH_8U, 3)
cv2.cv.SetData(bitmap, frame.tostring(), frame.dtype.itemsize * 3 * frame.shape[1])
tesseract.SetCvImage(bitmap, api)
text = api.GetUTF8Text()
confidence = api.MeanTextConf()
charMatrix = api.GetBoxText(0).split('\n')
return text, confidence, charMatrix
def ocr(self, image, area, factor):
api = tesseract.TessBaseAPI()
api.Init(".", "big", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_SINGLE_BLOCK)
h, w = image.shape
w_step = w * image.dtype.itemsize
iplimage = cv.CreateImageHeader((w, h), cv.IPL_DEPTH_8U, 1)
cv.SetData(iplimage, image.tostring(), image.dtype.itemsize * (w))
tesseract.SetCvImage(iplimage, api)
api.SetRectangle(int(area[0][0] * factor), int(area[0][1] * factor),
int(area[1][0] * factor) - int(area[0][0] * factor),
int(area[1][1] * factor) - int(area[0][1] * factor))
res = self.hocrToObject(api.GetHOCRText(0), area, factor)
return res
def img2text_method2(image_path):
print "Using method 2 to generate text from image..."
api = tesseract.TessBaseAPI()
api.SetOutputName("outputName")
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
image = cv.LoadImage(image_path, cv.CV_LOAD_IMAGE_GRAYSCALE)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
word_list = text.split()
print word_list
return word_list
def convert_file(filename):
#path = str(app.config['UPLOAD_FOLDER']+filename)
path = str('/home/engineer/htdocs/stop/webapi/uploads/' + filename).lower()
try:
image = cv.LoadImage(path, cv.CV_LOAD_IMAGE_GRAYSCALE)
except Exception as e:
return str("Error ") + str(e)
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
return jsonify({'output': str(text)})
def tesseract_ocr(imgname, type='PagesWrapper'):
api = tesseract.TessBaseAPI()
api.SetOutputName("outputName")
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
if type == 'PagesWrapper':
result = tesseract.ProcessPagesWrapper(imgname, api)
elif type == 'PagesFileStream':
result = tesseract.ProcessPagesFileStream(mImgFile, api)
elif type == 'PagesRaw':
result = tesseract.ProcessPagesRaw(mImgFile, api)
elif type == 'PagesBuffer':
mBuffer = open(imgname).read()
result = tesseract.ProcessPagesBuffer(mBuffer, len(mBuffer), api)
return result
def ocr_udemae(img):
img = binarize(img)
img = erode(img)
# cv2.imshow('ocr_udemae', img)
# cv2.waitKey(500)
api = tesseract.TessBaseAPI()
api.Init("C:\Program Files (x86)\Tesseract-OCR", "eng",
tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist", "SABC+-")
api.SetPageSegMode(tesseract.PSM_SINGLE_LINE)
cv_im = convert_to_IplImage(img)
tesseract.SetCvImage(cv_im, api)
return api.GetUTF8Text().split("\n")[0] # OCR結果から余計な改行を取り除く
def ocr_img(self, imgname):
"""
To use a non-standard language pack named foo.traineddata, set the TESSDATA_PREFIX environment variable so the file can be found at TESSDATA_PREFIX/tessdata/foo.traineddata and give Tesseract the argument -l foo.
"""
image = cv.LoadImage(imgname, cv.CV_LOAD_IMAGE_GRAYSCALE)
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
return text
def __init__(self):
api = tesseract.TessBaseAPI()
# For some reason, passing the path to Init() was not working,
# but setting the environment variable seems to be a workaround.
this_directory = os.path.dirname(os.path.realpath(__file__))
os.putenv("TESSDATA_PREFIX", this_directory)
api.Init(".", "ibge", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
api.SetVariable("tessedit_char_whitelist", "-0123456789°'\"")
api.SetVariable("chs_leading_punct", "-")
api.SetVariable("numeric_punctuation", "-°'\"")
self._api = api
def read_text(img):
"""
**SUMMARY**
This function will return any text it can find using OCR on the
image.
Please note that it does not handle rotation well, so if you need
it in your application try to rotate and/or crop the area so that
the text would be the same way a document is read
**RETURNS**
A String
**EXAMPLE**
>>> img = Imgae("somethingwithtext.png")
>>> text = img.read_text()
>>> print text
**NOTE**
If you're having run-time problems I feel bad for your son,
I've got 99 problems but dependencies ain't one:
http://code.google.com/p/tesseract-ocr/
http://code.google.com/p/python-tesseract/
"""
if not OCR_ENABLED:
return "Please install the correct OCR library required - " \
"http://code.google.com/p/tesseract-ocr/ " \
"http://code.google.com/p/python-tesseract/"
api = tesseract.TessBaseAPI()
api.SetOutputName("outputName")
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_AUTO)
jpgdata = StringIO()
convert.to_pil_image(img).save(jpgdata, "jpeg")
jpgdata.seek(0)
stringbuffer = jpgdata.read()
result = tesseract.ProcessPagesBuffer(stringbuffer, len(stringbuffer), api)
return result
def ocr_sxx(filename):
#####Image preprocess#####
im = cv2.imread(filename)
#convert to grayscale and apply Gaussian filtering
im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
#cv2.imshow('result1',im_gray)
# Threshold the image
ret, im_th = cv2.threshold(im_gray, 70, 255, cv2.THRESH_BINARY)
#cv2.imshow('result2',im_th)
#remove noise
im_th = cv2.medianBlur(im_th, 3)
#check result
#cv2.imshow('result',im_th)
#save the image in local computer
cv2.imwrite('result.png', im_th)
cv2.waitKey(0) # Waits forever for user to press any key
cv2.destroyAllWindows()
#########----OCR Part----########
image = cv.LoadImage("result.png", cv.CV_LOAD_IMAGE_GRAYSCALE)
directory = "tessdata/"
########choose language############
InputLan = "eng"
api = tesseract.TessBaseAPI()
fileName = InputLan + '.traineddata'
fullPath = directory + fileName
api.Init(".", InputLan, tesseract.OEM_DEFAULT)
#api.SetPageSegMode(tesseract.PSM_SINGLE_WORD)
api.SetPageSegMode(tesseract.PSM_AUTO)
tesseract.SetCvImage(image, api)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
timage = None
print len(text)
#text = text.decode('utf-8') #from str to unicode
print text.decode('utf-8')
#print conf
########delete /n ############
line = text.replace('\n', ' ')
#line = line.decode('utf-8')
print line.decode('utf-8')
def ocr(self, image, area, factor):
api = tesseract.TessBaseAPI()
#print self.lang
if self.lang == "big" or self.lang == "eng":
api.Init(".","big",tesseract.OEM_DEFAULT)
else:
api.Init(".", str(self.lang), tesseract.OEM_DEFAULT)
api.SetPageSegMode(tesseract.PSM_SINGLE_BLOCK)
h,w = image.shape
w_step = w*image.dtype.itemsize
iplimage = cv.CreateImageHeader((w,h), cv.IPL_DEPTH_8U, 1)
cv.SetData(iplimage, image.tostring(),image.dtype.itemsize * (w))
tesseract.SetCvImage(iplimage,api)
ocr_x2 = int((area[1][0]-int((area[1][0]-area[0][0])*0.17))*factor)
api.SetRectangle(int(area[0][0]*factor), int(area[0][1]*factor),
ocr_x2-int(area[0][0]*factor),
int(area[1][1]*factor)-int(area[0][1]*factor))
res = self.hocrToObject(api.GetHOCRText(0).decode('utf-8'), area, factor)
return res
def guess(img_data):
try:
api = tesseract.TessBaseAPI()
api.Init(".", "eng", tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist",
"0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ")
im = Image.open(StringIO.StringIO(img_data))
im.load()
if im.mode == 'RGBA':
r, g, b, a = im.split()
im = Image.merge("RGB", (r, g, b))
color_sep(im, 3)
color_fil(im)
contents = get_pil_string(im)
result = tesseract.ProcessPagesBuffer(contents, len(contents), api)
if result == None: result = ''
result = result.strip().replace(' ', '')
return result
except Exception, e:
e
def tesseract_native(fpath, lang, block=True):
"""
Use tesseract Python API to process `fpath`
pre-segmented image
"""
api = tesseract.TessBaseAPI()
api.Init(".", lang, tesseract.OEM_DEFAULT)
if block:
api.SetPageSegMode(tesseract.PSM_SINGLE_BLOCK)
else:
api.SetPageSegMode(tesseract.PSM_AUTO)
for opt, val in tesseract_opts.items():
api.SetVariable(opt, val)
img = cv.LoadImage(fpath, iscolor=False)
tesseract.SetCvImage(img, api)
text = api.GetUTF8Text()
return text
