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The most powerful weapon in the World

Kushal Bhavsar Spidy20

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The most powerful weapon in the World
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import streamlit as st
import PIL
import tensorflow as tf
import tensorflow_hub as hub
import numpy as np
import pandas as pd
from geopy.geocoders import Nominatim
model_url = 'https://tfhub.dev/google/on_device_vision/classifier/landmarks_classifier_asia_V1/1'
labels = 'landmarks_classifier_asia_V1_label_map.csv'
from geopy.geocoders import Nominatim
def Get_Addres(location):
geolocator = Nominatim(user_agent="Your_Name")
location = geolocator.geocode(location)
print(location.address)
print((location.latitude, location.longitude))
Get_Addres('India Gate')
# Output
import numpy as np
import pandas as pd
import PIL
import tensorflow as tf
import tensorflow_hub as hub
model_url = 'https://tfhub.dev/google/on_device_vision/classifier/landmarks_classifier_asia_V1/1'
labels = 'landmarks_classifier_asia_V1_label_map.csv'
img_shape = (321,321)
classifier = tf.keras.Sequential([hub.KerasLayer(model_url,input_shape=img_shape+(3,),output_key="predictions:logits")])
import streamlit as st
from PIL import Image
from keras.preprocessing.image import load_img,img_to_array
import numpy as np
from keras.models import load_model
import requests
from bs4 import BeautifulSoup
model = load_model('FV.h5')
labels = {0: 'apple', 1: 'banana', 2: 'beetroot', 3: 'bell pepper', 4: 'cabbage', 5: 'capsicum', 6: 'carrot', 7: 'cauliflower', 8: 'chilli pepper', 9: 'corn', 10: 'cucumber', 11: 'eggplant', 12: 'garlic', 13: 'ginger', 14: 'grapes', 15: 'jalepeno', 16: 'kiwi', 17: 'lemon', 18: 'lettuce',
from flask import Flask, request
import requests
from twilio.twiml.messaging_response import MessagingResponse
## Init Flask APp
app = Flask(__name__)
@app.route('/bot', methods=['POST'])
def bot():
## GEt user message
from kivymd.app import MDApp
from kivy.lang import Builder
class Test(MDApp):
def build(self):
self.title = 'Programming'
self.theme_cls.primary_palette = "Blue"
return Builder.load_string(
'''
BoxLayout:
'''
BoxLayout:
orientation:'vertical'
MDToolbar:
title: 'Programming'
md_bg_color: app.theme_cls.primary_color
specific_text_color: 1, 1, 1, 1
MDBottomNavigation:
MDBottomNavigationItem:
import streamlit as st
from PIL import Image
from fake_useragent import UserAgent
import requests
import pandas as pd
import base64
ua = UserAgent()
header = {'User-Agent': str(ua.chrome)}
import pyttsx3
import speech_recognition as sr
import datetime
import os
## Music Player Module developed by me
from PyMusic_Player import Music_Player_GUI
## Initializing voice of Assistant
engine = pyttsx3.init('sapi5')
voices = engine.getProperty('voices')
pyttsx3
SpeechRecognition
PyMusic-Player