def on_event(self, event, data):
if event == "chat" and self.fb_id:
msg = data["message"]["text"]
if msg == "train":
chatbot.send_fb_message(self.fb_id, "start training")
self.X, self.y = collect_img_hue(self.operating_instructions, self.user,
start=self.start, end=self.end)
self.learner.data_update(self.X, self.y)
self.learner.train()
chatbot.send_fb_message(self.fb_id, "finish training")
joblib.dump(self.learner.classifier, 'huelv2.pkl')
if msg == "control true":
self.control = True
if msg == "control false":
self.control = False
if event == "timer":
if self.learner.classifier is not None and self.control:
d = get_current_images(self.user, self.cam_ids)
all_state = self.operating_instructions[self.learner.predict(d)]
hue_data = json.dumps([
{"id": "1", "state": all_state},
{"id": "2", "state": all_state},
{"id": "3", "state": all_state}
])
self.output = [{"platform": "hue", "data": hue_data}]
def on_event(self, event, data):
if event == "chat" and self.fb_id:
msg = data["message"]["text"]
if msg == "train":
chatbot.send_fb_message(self.fb_id, "start training")
self.X_cols, self.labels = HueDBReader.read_db(
self.start, self.end)
self.learner.data_update(self.X, self.y)
self.learner.train()
chatbot.send_fb_message(self.fb_id, "finish training")
joblib.dump(self.learner.classifier, 'huelv2.pkl')
if msg == "control true":
self.control = True
if msg == "control false":
self.control = False
def on_event(self, event, data):
if event == "image":
if self.classifier is not None:
self.counter += 1
feats, summs = self.get_current_images()
if feats is None:
return
#datasets.data2vec([], [], data, False, False, False, False, False, True)
try:
pred = self.classifier.predict([feats])[0]
probs = self.classifier.predict_proba([feats])[0]
self.history.append(probs)
if len(self.history) < self.last_avg*2:
return
if len(self.history) > 20:
history = self.history[-20:]
if self.classes[pred] == "watch":
state = "watch"
self.last_state = state
probs[pred] = 1.0
else:
# moving average
avg_dist = np.mean(self.history[-self.last_avg:], axis=0)
state = self.classes[np.argmax(avg_dist)]#self.classes[pred]
pred = np.argmax(avg_dist)
probs = avg_dist
self.last_state = state
if self.stream:
chatbot.send_fb_message(self.fb_id, state + " " + str(int(probs[pred] * 100.0)) + "%")
#chatbot.send_fb_message(self.fb_id, str([int(p*100.0) for p in avg_dist]))
#if self.counter % 20 == 0:
# show_image_chat(summs[0], self.fb_id, send_img=True, message=state + " " + str(probs[pred]))
#chatbot.send_fb_message(self.fb_id, "===END===")
if probs[pred] < self.prob_threshold:
return
except Exception as e:
logger.error(str(e))
return
self.output = []
if state == "bed":
all_state = {"on": False}
#chatbot.send_fb_message(self.fb_id, "turning off lights")
else:
all_state = {"on": True}
if state == "study":
all_state.update({"bri":254,"hue":33016,"sat":53})
#chatbot.send_fb_message(self.fb_id, "brightening lights")
else:
all_state.update({"bri":254,"hue":14957,"sat":141})
if state == "study":
if not self.music_on:
chatbot.send_fb_message(self.fb_id, "playing music")
self.output.append({"platform": "play_youtube", "data": ""})
self.music_on = True
else:
if self.music_on:
chatbot.send_fb_message(self.fb_id, "stopping music")
self.output.append({"platform": "stop_youtube", "data":""})
self.music_on = False
hue_data = json.dumps([
{"id": "1", "state": all_state},
{"id": "2", "state": all_state},
{"id": "3", "state": all_state}
])
self.output.append({"platform": "hue", "data": hue_data})
if state == "watch":
if not self.tv_on:
self.output.append({"platform": "irkit", "data": ["TV"]})
self.tv_on = True
chatbot.send_fb_message(self.fb_id, "toggling TV (to on)")
else:
if self.tv_on:
self.output.append({"platform": "irkit", "data": ["TV"]})
self.tv_on = False
chatbot.send_fb_message(self.fb_id, "toggling TV (to off)")
probs = self.classifier.predict_proba([feats])
#logger.debug(self.classes)
#logger.debug(probs)
##logger.debug("current: {}, pred: {}".format(self.last_pred, pred))
#logger.debug(state)
##logger.debug("time since last change: " + str(time.time() - self.last_change))
min_state_time = 60
if self.train:
self.train = False
self.learn_and_load(force_update=True)
chatbot.send_fb_message(self.fb_id, "retrained")
elif event == "chat" and self.fb_id:
msg = data["message"]["text"]
if msg == "train":
#self.learn_and_load()
self.train = True
elif msg == "stream":
self.stream = not self.stream
elif msg == "state":
chatbot.send_fb_message(self.fb_id, self.last_state)
chatbot.send_fb_message(self.fb_id, str(len(self.last_images)))
for img in self.last_images:
show_image_chat_raw(img, self.fb_id)
elif msg.startswith("avg"):
prev = self.last_avg
self.last_avg = int(msg.strip().split()[-1])
chatbot.send_fb_message(self.fb_id, "changed averaging from %s to %s" % (prev, self.last_avg))
elif msg.startswith("threshold"):
prev = self.prob_threshold
self.prob_threshold = float(msg.strip().split()[-1])
chatbot.send_fb_message(self.fb_id, "changed threshold from %s to %s" % (prev, self.prob_threshold))
def on_event(self, event, data):
if event == "timer":
if self.classifier is not None:
feats, summs = self.get_current_images()
#datasets.data2vec([], [], data, False, False, False, False, False, True)
try:
pred = self.classifier.predict([feats])[0]
probs = self.classifier.predict_proba([feats])[0]
state = self.classes[pred]
except Exception as e:
logger.error(str(e))
return
if self.stream:
chatbot.send_fb_message(self.fb_id, state + " " + str(probs[pred]))
show_image_chat(summs[0], self.fb_id, send_img=True, message=state + " " + str(probs[pred]))
#chatbot.send_fb_message(self.fb_id, "===END===")
self.output = []
if state == "bed":
all_state = {"on": False}
else:
all_state = {"on": True}
if state == "study":
all_state.update({"bri":254,"hue":33016,"sat":53})
else:
all_state.update({"bri":254,"hue":14957,"sat":141})
if state == "study":
if not self.music_on:
chatbot.send_fb_message(self.fb_id, "playing music")
self.output.append({"platform": "play_youtube", "data": ""})
self.music_on = True
else:
if self.music_on:
chatbot.send_fb_message(self.fb_id, "stopping music")
self.output.append({"platform": "stop_youtube", "data":""})
self.music_on = False
hue_data = json.dumps([
{"id": "1", "state": all_state},
{"id": "2", "state": all_state},
{"id": "3", "state": all_state}
])
self.output.append({"platform": "hue", "data": hue_data})
if state == "watch":
if not self.tv_on:
self.output.append({"platform": "irkit", "data": ["TV"]})
self.tv_on = True
chatbot.send_fb_message(self.fb_id, "toggling TV (to on)")
else:
if self.tv_on:
self.output.append({"platform": "irkit", "data": ["TV"]})
self.tv_on = False
chatbot.send_fb_message(self.fb_id, "toggling TV (to off)")
probs = self.classifier.predict_proba([feats])
logger.debug(self.classes)
logger.debug(probs)
#logger.debug("current: {}, pred: {}".format(self.last_pred, pred))
logger.debug(state)
#logger.debug("time since last change: " + str(time.time() - self.last_change))
min_state_time = 60
if self.train:
self.train = False
self.learn_and_load(force_update=True)
chatbot.send_fb_message(self.fb_id, "retrained")
elif event == "chat" and self.fb_id:
msg = data["message"]["text"]
if msg == "train":
#self.learn_and_load()
self.train = True
elif msg == "stream":
self.stream = not self.stream
def on_event(self, event, data):
if event == "image":
if not self.wait and time.time() - self.ask_time > self.duration:
d = get_current_images(self.user, self.cam_ids)
index, confidence = self.learner.predict('TV', [d])
index = int(index[0])
predicted_on = self.classes[index]
if self.tv_on and (not predicted_on):
self.wait = True
self.ask_time = time.time()
self.re.append({
"platform": "irkit",
"data": ['TV', 'off'],
"confirmation": "テレビをけしますか?"
})
elif (not self.tv_on) and predicted_on:
self.wait = True
self.ask_time = time.time()
self.re.append({
"platform": "irkit",
"data": ['TV', 'on'],
"confirmation": "テレビをつけますか?"
})
if time.time() - self.ask_time > self.duration:
self.wait = False
if event == 'confirmation':
if data['platform'] == 'irkit':
self.wait = False
if 'answer' in data:
if data['confirmation'] == 'テレビをつけますか?' and data['answer']:
self.tv_on = True
if data['confirmation'] == 'テレビをけしますか?' and data['answer']:
self.tv_on = False
if event == "chat":
msg = data["message"]["text"].split()
if msg[0] == "irkit":
if msg[1] == "TV":
if msg[2] == "on":
if self.tv_on:
chatbot.send_fb_message(self.fb_id, "TVは既についています")
else:
self.re.append({
"platform": "irkit",
"data": msg[1:],
"confirmation": "テレビをつけますか?"
})
elif msg[2] == "off":
if self.tv_on:
self.re.append({
"platform": "irkit",
"data": msg[1:],
"confirmation": "テレビをけしますか?"
})
else:
chatbot.send_fb_message(self.fb_id, "TVはすでにきえています")
elif msg[1] == "AirConditioning":
pass
if event == "speech" and data["type"] == "speech":
msg = data["text"]
if "テレビ" in msg and "つけて" in msg:
if self.tv_on:
self.re.append({"platform": "tts", "data": "TVはすでについています"})
else:
self.re.append({"platform": "tts", "data": "TVをつけます"})
self.re.append({"platform": "irkit", "data": ['TV', 'on']})
self.tv_on = True
if "テレビ" in msg and "消して" in msg:
if self.tv_on:
self.re.append({"platform": "tts", "data": "TVを消します"})
self.re.append({
"platform": "irkit",
"data": ['TV', 'off']
})
self.tv_on = False
else:
self.re.append({"platform": "tts", "data": "TVは既に消えています"})