def onMessage(self,
mid=None,
author_id=None,
message=None,
message_object=None,
thread_id=None,
thread_type=ThreadType.USER,
ts=None,
metadata=None,
msg=None):
# igrone your own message
if (author_id == self.uid):
return
self.markAsDelivered(thread_id, message_object.uid)
self.delay()
self.markAsRead(thread_id)
self.delay()
#handle
name = self.get_name_by_user_id(author_id)
text = message_object.text
log.info('{}: {}'.format(name, text))
text_to_speech.say(name + ' nói ' + text)
def assistant(command):
if "price of" in command:
regex = re.search("price of (.*)", command)
if regex:
item = regex.group(1)
get_marketvalue(item)
print("Done!")
if "quantity of" in command:
regex = re.search("quantity of (.*)", command)
if regex:
item = regex.group(1)
get_quantity(item)
print("Done!")
if "show me" in command:
regex = re.search("show me (.*)", command)
if regex:
item = regex.group(1)
webbrowser.open("https://goblineer.tk/item/" +
item.replace(" ", "+"))
print("Done!")
if "exit" == command:
tts.say("Goodbye!")
sys.exit()
if "dog" in command:
webbrowser.open(
get_data.load_json("https://dog.ceo/api/breeds/image/random")
["message"])
return
def get_quantity(item_to_search):
found = False
for data in mv_names:
if data["name"].upper() == item_to_search.upper():
quantity = data["quantity"]
tts.say("The quantity of " + data["name"] + " is " +
num2words(quantity))
found = True
break
if not found:
tts.say("Item not found.")
def get_marketvalue(item_to_search):
found = False
for data in mv_names:
if data["name"].upper() == item_to_search.upper():
marketvalue = float(data["marketvalue"])
marketvalue_gold = trunc(marketvalue)
marketvalue_silver = trunc(
round(marketvalue - marketvalue_gold, 2) * 100)
tts.say("The marketvalue of " + data["name"] + " is " +
num2words(marketvalue_gold) + " gold and " +
num2words(marketvalue_silver) + " silver")
found = True
break
if not found:
tts.say("Item not found.")
def run_without_mic():
while True:
item_to_search = input("Item to search: ")
found = False
if item_to_search == "exit":
sys.exit()
for data in mv_names:
if data["name"].upper() == item_to_search.upper():
marketvalue = float(data["marketvalue"])
marketvalue_gold = trunc(marketvalue)
marketvalue_silver = trunc(
round(marketvalue - marketvalue_gold, 2) * 100)
tts.say("The marketvalue of " + data["name"] + " is " +
num2words(marketvalue_gold) + " gold and " +
num2words(marketvalue_silver) + " silver")
found = True
break
if not found:
tts.say("Item not found.")
def on_symbol_clicked(self, symbol, event):
if event.button == LEFT_BUTTON:
text_to_speech.say(symbol.label)
elif event.button == RIGHT_BUTTON:
SymbolEditorDialog(self.parent, symbol)
def cmd_dispatcher(sentence):
if sentence in STOP_LISTENING_HOTWORDS:
return True
# setup
sentence = str.lower(sentence)
words = sentence.split(' ')
features_controller(sentence, words)
def init():
# starting with speech searches
# cmd_dispatcher("testing")
pass
def controller():
init()
while True:
if cmd_dispatcher(get_text_from_speech()):
break
if __name__ == '__main__':
say(f'Kiara is alive')
controller()
print("Number of words: " + str(len(boxes)))
if (nWordsPrev != len(boxes)):
nWordsPrev = len(boxes)
#text_to_speech.say(str(len(boxes)) + " words have been found")
#text_to_speech.say(str(len(boxes)) + " words have been found")
errorMargin = 0.35
if (len(boxes) >= readThreshold and batchIndex == len(batch)
and batchAvg(batch) / len(boxes) < 1 + errorMargin
and batchAvg(batch) / len(boxes) > 1 - errorMargin):
print("start reading")
print(crop)
cropImage = noBox[crop[0][1]:crop[1][1], crop[0][0]:crop[1][0]]
cv2.imwrite("currentFrame.png", cropImage)
text_to_speech.say("The text says: ")
convert_to_text.convert("currentFrame.png")
if (batchIndex == len(batch)):
print(batchAvg(batch))
batchIndex = 0
batch[0] = len(boxes)
else:
batch[batchIndex] = len(boxes)
batchIndex += 1
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
import sys
########################## Main ##########################
# first argument: phrase
# second argument: who responds
# Nao as default
import speech_to_text_app as stt
import text_to_speech as tts
import nlc
voice = sys.argv[1]
#TODO: if no phrase given, start detecting speech
phrase = sys.argv[2]
global HILTON_CLASSIFIER = "341781x90-nlc-7639"
# ask watson what type of phrase is this
topClass = nlc.find_class(HILTON_CLASSIFIER, phrase)
# Make the robot say the phrase
tts.set_voice(voice)
tts.say(phrase)
# say the veredict
veredict = 'The class is. ' + str(topClass['class_name']) + '. With confidence of. ' + str(topClass['confidence'])
tts.say(veredict)