fun.py

#!/usr/bin/python3
import speech_recognition as sr
import numpy as np
import os, time, datetime, cv2, pyttsx3, urllib, urllib.parse, pafy, webbrowser
from bs4 import BeautifulSoup
from textblob import TextBlob
from nltk.corpus import wordnet
from textblob.classifiers import NaiveBayesClassifier

with open('document.json', 'r') as fp:
    cl = NaiveBayesClassifier(fp, format="json")

engine = pyttsx3.init()


def tts(voice_input_data):
    engine = pyttsx3.init()
    # voices = engine.getProperty('voices')
    # engine.setProperty('voice', voices[1].id)
    engine.say(voice_input_data)
    engine.runAndWait()


def camera():
    date = datetime.datetime.now().strftime("%m_%d_%Y_%H_%M_%S")
    img_counter = 0
    cam = cv2.VideoCapture(0)
    print("hit 'space' to click a pic\n hit 'Esc' to quit")

    while True:

        ret, frame = cam.read()
        cv2.imshow("test", frame)
        if not ret:
            break
        k = cv2.waitKey(1)

        if k % 256 == 27:
            # ESC pressed
            print("Escape hit, closing...")
            break
        elif k % 256 == 32:
            # SPACE pressed
            img_name = ("/home/manish/Desktop/" + date +
                        "opencv_frame_{}.png".format(img_counter))

            cv2.imwrite(img_name, frame)
            print("{} written!".format(img_name))
            img_counter += 1
    cam.release()
    cv2.destroyAllWindows()


class WordDef(sr.Recognizer):
    def listen(self, source, timeout=None):
        print("starting listening")
        result = super(self.__class__, self).listen(source, timeout)
        print("done listening")
        return result


class VideoPlay(sr.Recognizer):
    def listen(self, source, timeout=None):
        print("starting listening")
        result = super(self.__class__, self).listen(source, timeout)
        print("done listening")
        return result


def Video_Search():
    #engine.say("what video you want to search")
    #engine.runAndWait()
    tts("what video you want to play")
    sr.Recognizer = VideoPlay
    sa = sr.Recognizer()
    with sr.Microphone(chunk_size=512) as source:
        audio = sa.listen(source)
    srch_query = sa.recognize_google(audio)

    query = urllib.parse.quote(srch_query)
    url = "https://www.youtube.com/results?search_query=" + query
    response = urllib.request.urlopen(url)

    html = response.read()

    soup = BeautifulSoup(html)
    zx = 0
    for vid in soup.findAll(attrs={'class': 'yt-uix-tile-link'}):

        x = ('https://youtube.com/' + vid['href'])
        print(zx)

        if x != None and zx == 1:
            recv_url = x
            break

        zx += 1

    video = pafy.new(recv_url)
    best = video.getbest()
    playurl = best.url
    webbrowser.open(playurl)


class Search(sr.Recognizer):
    def listen(self, source, timeout=None):

        print("starting listening")
        result = super(self.__class__, self).listen(source, timeout)
        print("done listening")
        return result


def Search_Anything():
    #engine.say("what do you want to search")
    #engine.runAndWait()
    tts("what do you want to search")
    sr.Recognizer = Search
    sa = sr.Recognizer()
    with sr.Microphone(chunk_size=512) as source:
        audio = sa.listen(source)
    user_input = sa.recognize_google(audio)
    result = webbrowser.open("https://www.google.com/search?q=" + user_input)


class SentAnalyzer(sr.Recognizer):
    def listen(self, source, timeout=None):
        print("starting listening")
        result = super(self.__class__, self).listen(source, timeout)
        print("done listening")
        return result


def sentiment_Analyzer():
    #engine.say("Speak a sentence")
    #engine.runAndWait()
    tts("Speak a sentence")
    sr.Recognizer = SentAnalyzer
    sa = sr.Recognizer()
    with sr.Microphone(chunk_size=512) as source:
        audio = sa.listen(source)
    user_input = sa.recognize_google(audio)

    analysis = TextBlob(user_input)
    print(analysis.sentiment)
    if analysis.sentiment.polarity == 0:
        engine.say("your sentiment is nutral")
        engine.runAndWait()
    elif analysis.sentiment.polarity > 0:
        engine.say("your sentiment is positive")
        engine.runAndWait()

    elif analysis.sentiment.polarity < 0:
        engine.say("your sentiment is negative")
        engine.runAndWait()


def word_def_ex():
    #engine.say("speak a word")
    #engine.runAndWait()
    tts("speak a word")
    sr.Recognizer = WordDef
    w = sr.Recognizer()
    with sr.Microphone(chunk_size=512) as source:
        audio = w.listen(source)
    user_input1 = w.recognize_google(audio)
    result = wordnet.synsets(user_input1)
    re = (result[0].definition())
    tts(re)
    print(re)
    print(result[0].examples())


def bot_help():
    print(
        "__camera()__   ---\n say 'take picture' for open camera\n press 'space' for clicking picture\n press 'Esc' for quit...\n"
    )

    print("\n__sentiment_Analysis()__ ---\n say 'analysis' for sentiment analysis\n")

    print("\n__word_def_ex()__ ---\n say 'definition' for asking word's definition\n")

    print("\n__Video_Search()__ ---\n say 'video' for search for a video\n")

    print("\n__Search_Anything()__ ---\n say 'search' for search anything\n")