analyticsindiamagazine

analyticsindiamagazine

# -*- coding: utf-8 -*-

""" This is the expected File Format for Feature_pipeline.py script """

## import required libraries
import time
import pandas as pd
import os

analyticsindiamagazine

analyticsindiamagazine

analyticsindiamagazine

analyticsindiamagazine

analyticsindiamagazine

#Importing the speech recognition module
import speech_recognition as sr
#A random default value for prediction -- not among the classes we are predicting
prediction = 10

#Initializing the speech recognizer
r = sr.Recognizer()

#Declaring the listener source
with sr.Microphone() as source:

analyticsindiamagazine

analyticsindiamagazine

def predict():
    
    try:
    	#all the input labels . We had only trained the model using these selected features.
        labels = ['Brand', 'Location', 'Year', 'Kilometers_Driven', 'Fuel_Type','Transmission', 'Owner_Type', 'Mileage']
        
        #Collecting values from the html form and converting into respective types as expected by the model
        Brand =  request.form["Brand"]
        Location =  request.form["Location"]
        Year = int(request.form["Year"])

analyticsindiamagazine

#Importing necessary packages
import numpy as np
from flask import Flask, request, render_template
import pickle
from fastai.tabular import *
import os