def extract_text(img_path, model_path):
ocr = pyclstm.ClstmOcr()
ocr.load(model_path)
imgFile = Image.open(img_path)
text = ocr.recognize(imgFile)
text.encode('utf-8')
chars = ocr.recognize_chars(imgFile)
prob = 1
index = 0
x = 0
#print text
if (text.find(u':') != -1 and text.index(u':') < 5):
index = text.index(u':') + 1
if (text.find(u' ') != -1 and (text.index(u' ') <= 3)):
if (len(text) > text.index(u' ') + 1):
index = text.index(u' ') + 1
for ind, j in enumerate(chars):
#print j
if ind >= index:
prob *= j.confidence
if j.char == u':':
if j.x_position > x:
x = j.x_position
#return text[index:], prob, index
return text, prob, index, x
def extract_text(img_path, model_path):
ocr = pyclstm.ClstmOcr()
ocr.load(model_path)
imgFile = Image.open(img_path)
text = ocr.recognize(imgFile)
text.encode('utf-8')
chars = ocr.recognize_chars(imgFile)
prob = 1
index = 0
# print text
if text.find(u':') != -1 and text.index(u':') < 3:
index = text.index(u':') + 1
if text.find(u' ') != -1 and (text.index(u' ') <= 3):
if (len(text) > text.index(u' ') + 1):
index = text.index(u' ') + 1
for ind, j in enumerate(chars):
if ind >= index:
prob *= j.confidence
return text, prob
def extract_text(img_path, model_path):
ocr = pyclstm.ClstmOcr()
ocr.load(model_path)
imgFile = Image.open(img_path)
text = ocr.recognize(imgFile)
#print text
text.encode('utf-8')
chars = ocr.recognize_chars(imgFile)
prob = 1
index = 0
#print text
# if(text.find(u':') != -1 and text.index(u':') < 5):
# index = text.index(u':')+1
# if(text.find(u' ') != -1 and (text.index(u' ') <= 3)):
# if(len(text)>text.index(u' ')+1):
# index = text.index(u' ')+1
for ind, j in enumerate(chars):
#print j
#print j
if ind >= 0:
prob *= j.confidence
#print index
return text[0:], prob, 0
