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ding-dong-bot.py
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ding-dong-bot.py
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from collections import deque
import paddlehub as hub
import os
import asyncio
import re
import paddle
import PIL.Image as Image
import cv2
# import paddlex as pdx
import asyncio
import json
from garbage import predict
os.system("SET CUDA_VISIBLE_DEVICES=0")
model = hub.Module(name='plato-mini', version='1.0.0')
model._interactive_mode = True # 开启交互模式
model.max_turn = 20 # 对话轮次配置
model.context = deque(maxlen=model.max_turn) # 对话上下文的存储队列
from wechaty_puppet import FileBox, ScanStatus,MessageType # type: ignore
from wechaty import Wechaty, Contact
from wechaty.user import Message
from typing import Optional, Union
from wechaty.user import Message, Room
os.environ['WECHATY_PUPPET_SERVICE_ENDPOINT'] = 'ip'
os.environ['WECHATY_PUPPET_SERVICE_TOKEN'] = 'your token'
from wechaty import (
Contact,
FileBox,
Message,
Wechaty,
ScanStatus,
)
robot_state = 0
def mural_transform(image_old_path,img_name):
model = hub.Module(name='msgnet')
model = hub.Module(directory='D:\\project\\python\\dia_bot\\Mural_Gan\\msgnet')
result = model.predict(origin=[image_old_path], style='D:\\project\\python\\dia_bot\\Mural_Gan\\style_image\\style_2.jpg', visualization=True, save_path ='D:\\project\\python\\dia_bot\\Mural_Gan\\style_tranfer')
new_path = 'D:\\project\\python\\dia_bot\\Mural_Gan\\style_tranfer\\' + img_name
cv2.imwrite(new_path, result[0])
return new_path
async def on_message(msg: Message):
"""
Message Handler for the Bot
"""
talker = msg.talker()
# await msg.text()
if msg.text() == 'ding':
await msg.say('dong')
if msg.text() == 'hi' or msg.text() =='你好':
global robot_state
robot_state = 1000
await talker.say("Hello, My name is thomas! Now I will introduce myself to you!")
await talker.say("I'm your Personal Living Assistant")
await talker.say("You konw? Murals can be seen not only in the Mogao Grottoes, and if you say me '壁画' or 'Mural', you also can enjoy murals's beauty.")
await talker.say('Otherwise, I will be your Private Medical assistance! You can send me a message according to the format, for example "医疗:你的问题" or "Medicine:Your question" and I will try my best to answer your question about medicine!')
await talker.say('Besides, I can help you sort garbage and you can say me "垃圾分类" or "Garbage Classification". ')
await talker.say('Moreover,if you feel bored, say me "聊天" or "chat" and I will be your Siri.')
await talker.say("I have rich functions and it's up you to dig...")
await msg.say('Now begin your exploration!')
robot_state = 0
if msg.text() == 'Mural' or msg.text() == "壁画":
robot_state = 2
await talker.say('I will take you to Mogao Caves and please take me one picture!')
if msg.text() == '聊会天吧' or msg.text() == 'chat':
robot_state = 3
# model = hub.Module(name='plato-mini', version='1.0.0')
# model._interactive_mode = True
# model.max_turn = 100
# model.context = deque(maxlen=model.max_turn)
await talker.say("Let's begin! And if you want to end the chat, you can say me '再见' or 'Bye'.")
if robot_state == 3 and isinstance(msg.text(), str) and len(msg.text()) > 0 \
and msg._payload.type == MessageType.MESSAGE_TYPE_TEXT:
# and msg.text().startswith('[Chat]'): # Use a special token '[Test]' to select messages to respond.
if msg.text() == '再见' or msg.text() == 'Bye':
robot_state = 0
bot_response = model.predict(data=msg.text())[0]
await msg.say(bot_response) # Return the text generated by PaddleHub chatbot
if msg.text() == "垃圾分类" or msg.text() == 'Garbage Classification':
robot_state = 4
await talker.say("Please send the garbage's picture to me!")
if robot_state == 2 and msg.type() == Message.Type.MESSAGE_TYPE_IMAGE:
await talker.say('Image received! Please wait a minute!')
# 将Message转换为FileBox
file_box_1 = await msg.to_file_box()
# 获取图片名
img_name = file_box_1.name
# 图片保存的路径
img_path = 'D:\\project\\python\\dia_bot\\Mural_Gan\\test_image\\' + img_name
# 将图片保存为本地文件
await file_box_1.to_file(file_path=img_path)
# 调用图片风格转换的函数
img_new_path = mural_transform(img_path,img_name)
# 从新的路径获取图片
file_box_2 = FileBox.from_file(img_new_path)
robot_state = 0
await msg.say(file_box_2)
if "医疗" in msg.text() or "Medicine" in msg.text():
module = hub.Module(name="Medicine-dialogue")
if ':' in msg.text() and msg.text().split(':')[0] == '医疗' :
print(msg.text().split(':')[1])
question = msg.text().split(':')[1]
robot_state = 3
if ":" in msg.text() and msg.text().split(':')[0] == 'Medicine':
print(msg.text().split(':')[1])
robot_state =3
question = msg.text().split(':')[1]
print(question)
await talker.say('Question received! Please wait a minute!')
test_texts = []
test_texts.append(question)
# generate包含3个参数,texts为输入文本列表,use_gpu指定是否使用gpu,beam_width指定beam search宽度。
results = module.generate(texts=test_texts, use_gpu=False, beam_width=1)
robot_state = 0
for result in results:
print(result)
await msg.say(result[0])
if robot_state == 4 and msg.type() == Message.Type.MESSAGE_TYPE_IMAGE:
await talker.say('Image received! Please wait a moment!')
# 将Message转换为FileBox
file_box_2 = await msg.to_file_box()
# 获取图片名
img_name = file_box_2.name
# 图片保存的路径
img_path = 'D:\\project\\python\\dia_bot\\garbage\\picture\\' + img_name
await file_box_2.to_file(file_path=img_path)
result = predict.main(img_path)
f_obj=open('D:\\project\\python\\dia_bot\\garbage\\garbage_classification.json','r',encoding='utf8')
# print(res[i])
category_id = result[0][0]
score = result[1][0]
score="%.2f%%"%(score*100)
content=json.load(f_obj)[str(category_id)]
content = "This garbage is %s and it's score is %s."%(content,str(score))
robot_state = 0
await talker.say(content)
print(content)
# number=result[0]['category']
# score=result[0]['score']
# score="%.2f%%"%(score*100)
# content=json.load(f_obj)[number]
# content = "This garbage is %s and it's score is %s."%(content,str(score))
# robot_state = 0
# await talker.say(content)
# elif isinstance(msg.text(), str) and len(msg.text()) > 0 \
# and msg._payload.type == MessageType.MESSAGE_TYPE_TEXT : # Use a special token '[Test]' to select messages to respond.
# bot_response = model.predict(data=msg.text())[0]
# await msg.say(bot_response) # Return the text generated by PaddleHub chatbot
async def on_scan(
qrcode: str,
status: ScanStatus,
_data,
):
"""
Scan Handler for the Bot
"""
print('Status: ' + str(status))
print('View QR Code Online: https://wechaty.js.org/qrcode/' + qrcode)
async def on_login(user: Contact):
"""
Login Handler for the Bot
"""
print(user)
# TODO: To be written
async def main():
"""
Async Main Entry
"""
#
# Make sure we have set WECHATY_PUPPET_SERVICE_TOKEN in the environment variables.
# Learn more about services (and TOKEN) from https://wechaty.js.org/docs/puppet-services/
#
if 'WECHATY_PUPPET_SERVICE_TOKEN' not in os.environ:
print('''
Error: WECHATY_PUPPET_SERVICE_TOKEN is not found in the environment variables
You need a TOKEN to run the Python Wechaty. Please goto our README for details
https://github.com/wechaty/python-wechaty-getting-started/#wechaty_puppet_service_token
''')
bot = Wechaty()
bot.on('scan', on_scan)
bot.on('login', on_login)
bot.on('message', on_message)
await bot.start()
print('[Python Wechaty] Ding Dong Bot started.')
asyncio.run(main())