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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' |
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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 |
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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")]) |
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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', |
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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 |
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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: |
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''' | |
BoxLayout: | |
orientation:'vertical' | |
MDToolbar: | |
title: 'Programming' | |
md_bg_color: app.theme_cls.primary_color | |
specific_text_color: 1, 1, 1, 1 | |
MDBottomNavigation: | |
MDBottomNavigationItem: |
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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)} |
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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') |
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pyttsx3 | |
SpeechRecognition | |
PyMusic-Player |
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