#print height, " ", width
#sleep(5)
#gray = cv2.resize(image, dim, interpolation = cv2.INTER_AREA)
#height, width = gray.shape[:2]
# Our operations on the frame come here, doing some manipulation to reduce effects from surrounding objects,
#light&shadow play, etc
gray = cv2.medianBlur(gray, 5)
#gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.bilateralFilter(gray, 5, 25, 25)
#cv2.rectangle(gray, (width/2-150, height/2-150), (width/2+200, height/2+150), (255,0,0), 2)
cv2.imshow('frame',gray) #showing image
#gray = gray.copy()[height/2-150:height/2+150,width/2-150:width/2+200]
image = Image.fromarray(gray) #turning array into image
speech = ocr.ocr_image(image) #ocr-ing image by Tesseract
#print type(speech)
#speech = ocr.get_utf8_text()
if ocr.get_mean_confidence() >= 63 and len(speech.strip()) >1:
tts.say(str(speech))
print speech
sleep(1)
#robot speech
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
#cap.release()
camProxy.unsubscribe(videoClient)
cv2.destroyAllWindows()
cv2.imshow('frame',gray) #showing image
if cv2.waitKey(1) & 0xFF == ord('p'):
cv2.imwrite('pic{:>05}.jpg'.format(i), gray)
i += 1
#gray = gray.copy()[height/2-150:height/2+150,width/2-150:width/2+200]
image = Image.fromarray(gray) #turning array into image
#img = cv2.QueryFrame(image)
speech = ocr.ocr_image(image) #ocr-ing image by Tesseract
#print type(speech)
#speech = ocr.get_utf8_text()
wordList = re.sub("[^\w]", " ", str(speech)).split()
if ocr.get_mean_confidence() >= 63:
for word in wordList:
print word
# print dict.dictionary
if dict.find_word(word.strip()):
tts.say(word)
print " the word is " + word
# tts.say(str(speech))
# print speech
sleep(1)
#robot speech
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
