016_teachable-machine_chatbot.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"9OitNmq4FaJy"},"outputs":[],"source":["'''\n","\n","安裝套件\n","\n","'''\n","!pip install line-bot-sdk flask \n","!pip install pyngrok"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"t6qnOcS-FrsE"},"outputs":[],"source":["'''\n","解壓縮模型\n","'''\n","\n","from zipfile import ZipFile\n","\n","with ZipFile('converted_savedmodel.zip', 'r') as zipObj:\n","   # Extract all the contents of zip file in different directory\n","   zipObj.extractall('converted_savedmodel')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"z1KdkjGaFtYc"},"outputs":[],"source":["'''\n","載入類別列表\n","'''\n","class_dict = {}\n","with open('converted_savedmodel/labels.txt') as f:\n","    for line in f:\n","       (key, val) = line.split()\n","       class_dict[int(key)] = val"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Ce6T5eW2FvUz"},"outputs":[],"source":["from flask import Flask, request, abort\n","\n","from linebot import (\n","    LineBotApi, WebhookHandler\n",")\n","from linebot.exceptions import (\n","    InvalidSignatureError\n",")\n","from linebot.models import (\n","    MessageEvent, TextMessage, TextSendMessage,\n",")\n","\n","# 外部連結自動生成套件\n","# from flask_ngrok import run_with_ngrok\n","from pyngrok import ngrok\n","\n","# 設定Server啟用細節\n","app = Flask(__name__,static_url_path = \"/material\" , static_folder = \"./material/\")\n","\n","\n","line_bot_api = LineBotApi('CHANNEL_ACCESS_TOKEN')\n","handler = WebhookHandler('CHANNEL_SECRET')\n","\n","\n","@app.route(\"/\", methods=['POST'])\n","def callback():\n","    # get X-Line-Signature header value\n","    signature = request.headers['X-Line-Signature']\n","\n","    # get request body as text\n","    body = request.get_data(as_text=True)\n","    app.logger.info(\"Request body: \" + body)\n","\n","    # handle webhook body\n","    try:\n","        handler.handle(body, signature)\n","    except InvalidSignatureError:\n","        print(\"Invalid signature. Please check your channel access token/channel secret.\")\n","        abort(400)\n","\n","    return 'OK'"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"eNxeavGsF7Jy"},"outputs":[],"source":["'''\n","\n","關注事件，功能說明\n","\n","'''\n","\n","# 引用套件\n","from linebot.models import (\n","    FollowEvent,TextSendMessage\n",")\n","\n","# 關注事件處理\n","@handler.add(FollowEvent)\n","def process_follow_event(event):\n","    \n","    # 消息發送\n","    line_bot_api.reply_message(\n","        event.reply_token,\n","        TextSendMessage(\n","        \"\"\"這個教室裡面，我置入了兩個業配，當大家找到了業配，今天課程才算開始。請找到那個業配，拍下來並上傳。\"\"\"\n","        )\n","    )\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"5hAH0J8dGDy5"},"outputs":[],"source":["'''\n","\n","文字消息，功能說明\n","\n","'''\n","\n","# 引用套件\n","from linebot.models import (\n","    MessageEvent,TextMessage,TextSendMessage\n",")\n","\n","# 關注事件處理\n","@handler.add(MessageEvent,message=TextMessage)\n","def process_text_message_event(event):\n","    \n","    # 消息發送\n","    line_bot_api.reply_message(\n","        event.reply_token,\n","        TextSendMessage(\n","        \"\"\"這個教室裡面，我置入了兩個業配，當大家找到了業配，今天課程才算開始。請找到那個業配，拍下來並上傳。\"\"\"\n","        )\n","    )\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"1q5cZ5NaGHXM"},"outputs":[],"source":["'''\n","\n","圖片消息，解析圖片\n","\n","'''\n","\n","import tensorflow.keras\n","from PIL import Image, ImageOps\n","import numpy as np\n","\n","# 引用套件\n","from linebot.models import (\n","    MessageEvent,ImageMessage,TextSendMessage\n",")\n","\n","# Disable scientific notation for clarity\n","np.set_printoptions(suppress=True)\n","\n","# Load the model\n","model = tensorflow.keras.models.load_model('converted_savedmodel/model.savedmodel')\n","\n","import time\n","\n","@handler.add(MessageEvent, message=ImageMessage)\n","def handle_message(event):\n","\n","    print(time.asctime( time.localtime(time.time()) ))\n","\n","    message_content = line_bot_api.get_message_content(event.message.id)\n","    file_name = event.message.id+'.jpg'\n","    with open(file_name, 'wb') as fd:\n","        for chunk in message_content.iter_content():\n","            fd.write(chunk)\n","\n","    print(time.asctime( time.localtime(time.time()) ))\n","\n","    data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)\n","\n","    # Replace this with the path to your image\n","    image = Image.open(file_name)\n","\n","    #resize the image to a 224x224 with the same strategy as in TM2:\n","    #resizing the image to be at least 224x224 and then cropping from the center\n","    size = (224, 224)\n","    image = ImageOps.fit(image, size, Image.ANTIALIAS)\n","\n","    print(time.asctime( time.localtime(time.time()) ))\n","    \n","    #turn the image into a numpy array\n","    image_array = np.asarray(image)\n","\n","    # display the resized image\n","    image.show()\n","\n","    \n","    # Normalize the image\n","    normalized_image_array = (image_array.astype(np.float32) / 127.0 - 1 )\n","\n","    # Load the image into the array\n","    data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)\n","    data[0]= normalized_image_array[0:224,0:224,0:3]\n","\n","    # run the inference\n","    prediction = model.predict(data)\n","\n","    print(time.asctime( time.localtime(time.time()) ))\n","\n","    max_probability_item_index = np.argmax(prediction[0])\n","\n","    if prediction.max() > 0.6:\n","        line_bot_api.reply_message(\n","          event.reply_token,\n","          TextSendMessage(\n","          \"\"\"這個物件極有可能是 %s ，其相似機率為 %s \"\"\" %(class_dict.get(max_probability_item_index), prediction[0][max_probability_item_index])\n","          )\n","        )\n","    else :\n","      line_bot_api.reply_message(\n","        event.reply_token,\n","        TextSendMessage(\n","        \"\"\"再混啊！亂拍照！！\"\"\"\n","        )\n","      )"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"aix7yEkVGMqk"},"outputs":[],"source":["# 主程序運行\n","port = 5000\n","# Open a ngrok tunnel to the HTTP server\n","public_url = ngrok.connect(port).public_url\n","print(\" * ngrok tunnel \\\"{}\\\" -> \\\"http://127.0.0.1:{}\\\"\".format(public_url, port))\n","app.run()"]}],"metadata":{"colab":{"authorship_tag":"ABX9TyMi5WnSrVhB+57GY2fvq8Hp","collapsed_sections":[],"name":"016_teachable-machine_chatbot.ipynb","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"}},"nbformat":4,"nbformat_minor":0}