def ocrImage(tagDest,tessdataPrefix,lang,charWhitelist,pageMode):
destOcrImg = "/tmp/"+genymotion_vm_name+"-"+tagDest+".png"
print "OCR : "+str(destOcrImg)
#OCR Def
tr = Tesseract(tessdataPrefix, lang)
tr.set_variable("tessedit_char_whitelist", charWhitelist)
tr.set_page_seg_mode(pageMode)
#OCR
image = Image.open(destOcrImg)
tr.set_image(image)
return tr.get_utf8_text()
def ocr_text(img):
tr = Tesseract(lang='eng')
tr.clear()
pil_image = pil.Image.fromarray(img)
# Turn off OCR word dictionaries
tr.set_variable('load_system_dawg', "F")
tr.set_variable('load_freq_dawg', "F")
tr.set_variable('-psm', "7") # treat image as single line
tr.set_variable('tessedit_char_whitelist', "ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789")
tr.set_image(pil_image)
utf8_text = tr.get_text()
return unicode(utf8_text)
#much stuff got commented in the end, staying here for a while for educational reasons only
#need to add connection to video from robot
import numpy as np
import vision_definitions
from time import sleep
import cv2
#from pytesser import *
from tesserwrap import Tesseract
from PIL import Image
from naoqi import ALProxy
ocr = Tesseract()
ocr.set_variable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ") #since we use upper cased text only
#ocr.set_variable("classify_enable_learning", "0")
#ocr.set_variable("classify_enable_adaptive_matcher", "0")
#cap = cv2.VideoCapture(0)
#connecting to the robot
IP = "192.168.0.238"
#speech module
tts = ALProxy("ALTextToSpeech", IP, 9559)
cameraid=0
camProxy = ALProxy("ALVideoDevice", IP, 9559)
resolution = vision_definitions.kVGA
colorSpace = vision_definitions.kBGRColorSpace
videoClient = camProxy.subscribe("python_client", resolution, colorSpace, 5)
camProxy.setParam(vision_definitions.kCameraSelectID, cameraid)
#9137743885
