From 8d818364750e677d7412b55eab38a04df9bfb5e1 Mon Sep 17 00:00:00 2001
From: Priyanshu Sharma <132160817+iPriyanshu19@users.noreply.github.com>
Date: Thu, 25 Jan 2024 00:22:30 +0530
Subject: [PATCH 1/4] Main Modules

All the required modules for running the project
---
 README.md                           |     2 +-
 app.py                              |   108 +
 dataset.py                          |    52 +
 face_detect.py                      |    53 +
 haarcascade_frontalface_default.xml | 35712 ++++++++++++++++++++++++++
 main.py                             |    85 +
 models/models_downloadLink.txt      |     1 +
 object.py                           |    26 +
 requirements.txt                    |    17 +
 yolov8n.pt                          |   Bin 0 -> 6534387 bytes
 10 files changed, 36055 insertions(+), 1 deletion(-)
 create mode 100644 app.py
 create mode 100644 dataset.py
 create mode 100644 face_detect.py
 create mode 100644 haarcascade_frontalface_default.xml
 create mode 100644 main.py
 create mode 100644 models/models_downloadLink.txt
 create mode 100644 object.py
 create mode 100644 requirements.txt
 create mode 100644 yolov8n.pt

diff --git a/README.md b/README.md
index f87f933..39545b3 100644
--- a/README.md
+++ b/README.md
@@ -1 +1 @@
-# P19
+# ProjectSem3
diff --git a/app.py b/app.py
new file mode 100644
index 0000000..2c6f69b
--- /dev/null
+++ b/app.py
@@ -0,0 +1,108 @@
+import streamlit as st
+import smtplib
+from langchain.prompts import PromptTemplate
+from langchain_community.llms import CTransformers
+from email.mime.text import MIMEText
+from email.mime.multipart import MIMEMultipart
+
+
+def send_email(sender_email, receiver_email, subject, body):
+    # Set up SMTP server
+    smtp_server = smtplib.SMTP('smtp.gmail.com', 587)
+    smtp_server.starttls()
+    smtp_server.login(sender_email, "aacr gmev ylhg uplf")
+
+    # Create email message
+    msg = MIMEMultipart()
+    msg['From'] = sender_email
+    msg['To'] = receiver_email
+    msg['Subject'] = subject
+
+    msg.attach(MIMEText(body, 'plain'))
+
+    # Send the email
+    smtp_server.sendmail(sender_email, receiver_email, msg.as_string())
+    smtp_server.quit()
+
+
+
+
+# Function to get the response back
+def getLLMResponse(form_input, email_sender, email_recipient, email_style):
+    # llm = OpenAI(temperature=.9, model="text-davinci-003")
+
+    # Wrapper for Llama-2-7B-Chat, Running Llama 2 on CPU
+
+    # Quantization is reducing model precision by converting weights from 16-bit floats to 8-bit integers,
+    # enabling efficient deployment on resource-limited devices, reducing model size, and maintaining performance.
+
+    # C Transformers offers support for various open-source models,
+    # among them popular ones like Llama, GPT4All-J, MPT, and Falcon.
+
+    # C Transformers is the Python library that provides bindings for transformer models implemented in C/C++ using the GGML library
+
+    llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',
+                        # https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
+                        model_type='llama',
+                        config={'max_new_tokens': 256,
+                                'temperature': 0.01},
+                        access_token="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"
+                        )
+
+    # Template for building the PROMPT
+    template = """
+    Write a email with {style} style and includes topic :{email_topic}.\n\nSender: {sender}\nRecipient: {recipient}
+    \n\nEmail Text:
+
+    """
+
+    # Creating the final PROMPT
+    prompt = PromptTemplate(
+        input_variables=["style", "email_topic", "sender", "recipient"],
+        template=template, )
+
+    # Generating the response using LLM
+    response = llm(
+        prompt.format(email_topic=form_input, sender=email_sender, recipient=email_recipient, style=email_style))
+    print(response)
+
+    return response
+
+
+st.set_page_config(page_title="Generate Emails",
+                   page_icon='📧',
+                   layout='centered',
+                   initial_sidebar_state='collapsed')
+st.header("Generate Emails 📧")
+
+form_input = st.text_area('Enter the email topic', height=275)
+
+# Creating columns for the UI - To receive inputs from user
+col1, col2, col3 = st.columns([10, 10, 5])
+with col1:
+    email_sender = st.text_input('Sender Name')
+with col2:
+    email_recipient = st.text_input('Recipient Name')
+with col3:
+    email_style = st.selectbox('Writing Style',
+                               ('Formal', 'Appreciating', 'Not Satisfied', 'Neutral'),
+                               index=0)
+
+submit = st.button("Generate")
+send_button = st.button("Send Email")
+# When 'Generate' button is clicked, execute the below code
+
+while True:
+    if submit:
+        generate_response=getLLMResponse(form_input, email_sender, email_recipient, email_style)
+        st.write(generate_response)
+
+
+    if send_button:
+        sender_email = "mysteryverse9@gmail.com"
+        receiver_email = st.text_input("Please enter your email address: ")
+        subject = "Test email from Python"
+        body = generate_response
+        send_email(sender_email, receiver_email, subject, body)
+        st.success("Email Sent Successfully!")
+        break
\ No newline at end of file
diff --git a/dataset.py b/dataset.py
new file mode 100644
index 0000000..c652999
--- /dev/null
+++ b/dataset.py
@@ -0,0 +1,52 @@
+import cv2, os, time
+# change the paths below to the location where these files are on your machine
+haar_file = 'haarcascade_frontalface_default.xml'
+# All of the faces data (images) will be stored here
+datasets ="dataset"
+# change the name below when creating a new dataset for a new person
+name = 'priyanshu'
+
+path = os.path.join(datasets, name)
+# if sub_dataset folder doesn't already exist, make the folder with the name defined above
+if not os.path.isdir(path):
+    os.mkdir(path)
+
+# defining the size of images
+(width, height) = (640, 480)
+
+face_cascade = cv2.CascadeClassifier(haar_file)
+cap = cv2.VideoCapture(0)
+# returns true or false (if the camera is on or not)
+print("Webcam is open? ", cap.isOpened())
+# wait for the camera to turn on (just to be safe, in case the camera needs time to load up)
+time.sleep(2)
+#Takes pictures of detected face and saves them
+count = 1
+print("Taking pictures...")
+# this takes 300 pictures of your face. Change this number if you want.
+# Having too many images, however, might slow down the program
+while count < 300:
+    # im = camera stream
+    ret, frame = cap.read()
+    # if it recieves something from the webcam...
+    if ret == True:
+        img_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        # detect face using the haar cascade file
+        faces = face_cascade.detectMultiScale(img_gray, 1.3, 4)  #(source,scale,min_neighbours)
+        for (x,y,w,h) in faces:
+            # draws a rectangle around your face when taking pictures
+            # this is to create a ROI (region of interest) so it only takes pictures of your face
+            cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
+            # define 'face' as the inside of the rectangle we made above and make it grayscale
+            face = img_gray[y:y + h, x:x + w]
+            # resize the face images to the size of the 'face' variable above (i.e: area captured inside of the rectangle)
+            face_resize = cv2.resize(face, (width, height))
+            # save images with their corresponding number
+            cv2.imwrite('%s/%s.png' % (path,count), face_resize)
+        count += 1
+        cv2.imshow('Face Capturing', frame)
+        if cv2.waitKey(1) == ord("q"):
+            break
+print("Your face has been created.")
+cap.release()
+cv2.destroyAllWindows()
diff --git a/face_detect.py b/face_detect.py
new file mode 100644
index 0000000..12f733d
--- /dev/null
+++ b/face_detect.py
@@ -0,0 +1,53 @@
+import cv2
+import os
+import numpy as np
+
+haar_file = 'haarcascade_frontalface_default.xml'
+datasets ='dataset/'
+(images, labels, names, id) = ([], [], {}, 0)
+for (subdir, dirs, files) in os.walk(datasets):
+    for subdir in dirs:
+        names[id] =subdir
+        subjectpath = os.path.join(datasets, subdir)
+        for filename in os.listdir(subjectpath):
+            path = os.path.join(subjectpath, filename)
+            label = id
+            images.append(cv2.imread(path, 0))
+            labels.append(int(label))
+        id = id + 1
+
+(images, labels) = [np.array(lists) for lists in [images, labels]]
+# Load the face recognizer from the 'face' submodule
+model =  cv2.face.LBPHFaceRecognizer_create()
+
+# Rest of your code...
+
+model.train(images, labels)
+
+face_cascade = cv2.CascadeClassifier(haar_file)
+cap = cv2.VideoCapture(0)
+
+while True:
+    ret, frame = cap.read()
+    if ret == True:
+        img_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        faces = face_cascade.detectMultiScale(img_gray, 1.3, 4)
+        # detectMultiscale(source_image,scale,min_neighbours)
+        for (x, y, w, h) in faces:
+            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+            face = img_gray[y:y + h, x:x + h]
+            face_resize = cv2.resize(face, (640, 480))
+            prediction = model.predict(face_resize)
+            if prediction[1] < 25:
+                person_name=names[prediction[0]]
+                cv2.putText(frame, '%s' % (person_name), (x + 5, (y + 25 + h)),
+                            cv2.FONT_HERSHEY_PLAIN, 1.5, (20, 185, 20), 2)
+            else:
+                cv2.putText(frame, "Unknown", (x + 5, (y + 25 + h)), cv2.FONT_HERSHEY_PLAIN,
+                            1.5, (65, 65, 255), 2)
+
+        cv2.imshow("Face Recognition", frame)
+        if cv2.waitKey(1) == ord("q"):
+             break
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/haarcascade_frontalface_default.xml b/haarcascade_frontalface_default.xml
new file mode 100644
index 0000000..8dff079
--- /dev/null
+++ b/haarcascade_frontalface_default.xml
@@ -0,0 +1,35712 @@
+<?xml version="1.0"?>
+<!--
+    Stump-based 24x24 discrete(?) adaboost frontal face detector.
+    Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<haarcascade_frontalface_default type_id="opencv-haar-classifier">
+  <size>24 24</size>
+  <stages>
+    <_>
+      <!-- stage 0 -->
+      <trees>
+        <_>
+          <!-- tree 0 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>6 4 12 9 -1.</_>
+                <_>6 7 12 3 3.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.0315119996666908</threshold>
+            <left_val>2.0875380039215088</left_val>
+            <right_val>-2.2172100543975830</right_val></_></_>
+        <_>
+          <!-- tree 1 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>6 4 12 7 -1.</_>
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+              <tilted>0</tilted></feature>
+            <threshold>0.0123960003256798</threshold>
+            <left_val>-1.8633940219879150</left_val>
+            <right_val>1.3272049427032471</right_val></_></_>
+        <_>
+          <!-- tree 2 -->
+          <_>
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+              <tilted>0</tilted></feature>
+            <threshold>0.0219279993325472</threshold>
+            <left_val>-1.5105249881744385</left_val>
+            <right_val>1.0625729560852051</right_val></_></_>
+        <_>
+          <!-- tree 3 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
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+              <tilted>0</tilted></feature>
+            <threshold>5.7529998011887074e-003</threshold>
+            <left_val>-0.8746389746665955</left_val>
+            <right_val>1.1760339736938477</right_val></_></_>
+        <_>
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+            <threshold>0.0150140002369881</threshold>
+            <left_val>-0.7794569730758667</left_val>
+            <right_val>1.2608419656753540</right_val></_></_>
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+            <left_val>0.5575129985809326</left_val>
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+            <threshold>2.7340000960975885e-003</threshold>
+            <left_val>-1.6911929845809937</left_val>
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+            <threshold>-0.0188590008765459</threshold>
+            <left_val>-1.4769539833068848</left_val>
+            <right_val>0.4435009956359863</right_val></_></_>
+        <_>
+          <!-- tree 8 -->
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+            <!-- root node -->
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+              <tilted>0</tilted></feature>
+            <threshold>5.9739998541772366e-003</threshold>
+            <left_val>-0.8590919971466065</left_val>
+            <right_val>0.8525559902191162</right_val></_></_></trees>
+      <stage_threshold>-5.0425500869750977</stage_threshold>
+      <parent>-1</parent>
+      <next>-1</next></_>
+    <_>
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+            <feature>
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+            <threshold>-0.0211100000888109</threshold>
+            <left_val>1.2435649633407593</left_val>
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+            <left_val>-1.6204780340194702</left_val>
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+            <right_val>0.2719680070877075</right_val></_></_>
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+          <!-- tree 175 -->
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+          <!-- tree 176 -->
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+            <!-- root node -->
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+            <right_val>0.5888490080833435</right_val></_></_>
+        <_>
+          <!-- tree 177 -->
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+            <!-- root node -->
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+            <right_val>-0.0359119996428490</right_val></_></_>
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+          <!-- tree 178 -->
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+        <_>
+          <!-- tree 182 -->
+          <_>
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+        <_>
+          <!-- tree 183 -->
+          <_>
+            <!-- root node -->
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+            <threshold>0.1070580035448074</threshold>
+            <left_val>0.1897229999303818</left_val>
+            <right_val>-0.5123620033264160</right_val></_></_>
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+          <!-- tree 184 -->
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+            <!-- root node -->
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+            <threshold>-0.0405250005424023</threshold>
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+          <!-- tree 185 -->
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+          <!-- tree 187 -->
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+          <!-- tree 189 -->
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+          <!-- tree 192 -->
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+        <_>
+          <!-- tree 198 -->
+          <_>
+            <!-- root node -->
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+            <left_val>-0.1342169940471649</left_val>
+            <right_val>1.6807060241699219</right_val></_></_>
+        <_>
+          <!-- tree 199 -->
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+            <!-- root node -->
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+            <left_val>0.4860099852085114</left_val>
+            <right_val>3.6160000599920750e-003</right_val></_></_></trees>
+      <stage_threshold>-2.9928278923034668</stage_threshold>
+      <parent>23</parent>
+      <next>-1</next></_></stages></haarcascade_frontalface_default>
+</opencv_storage>
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..92618da
--- /dev/null
+++ b/main.py
@@ -0,0 +1,85 @@
+import speech_recognition as sr
+import pyttsx3
+import pywhatkit
+import datetime
+import pyjokes
+import wikipedia
+import os
+import streamlit
+import subprocess
+
+listener =  sr.Recognizer()
+engine = pyttsx3.init()
+voices = engine.getProperty('voices')
+engine.setProperty('voice',voices[0].id)
+
+
+def speak(text):
+    engine.say(text)
+    engine.runAndWait()
+
+
+def take_command():
+    try:
+        with sr.Microphone() as source:
+            print("Listening..")
+            voice  = listener.listen(source)
+            command = listener.recognize_google(voice)
+            command = command.lower()
+            
+            if 'professor' in command:
+                command = command.replace('professor','')
+                print(command)
+    
+    except Exception as e:
+        raise e
+    
+    return command
+
+def run_assistant():
+    command = take_command()
+    print(command)
+
+    if 'play' in command:
+        song = command.replace('play','')
+        speak('playing ' + song)
+        pywhatkit.playonyt(song)
+
+    elif 'time' in command:
+        time = datetime.datetime.now().strftime('%I:%M %p')
+        speak("current time is " + time)
+
+    elif 'name' in command:
+        speak("My name is Professor")
+
+    elif 'joke' in command:
+        speak(pyjokes.get_jokes())
+
+    elif 'wikipedia' in command:
+        speak("Searching wikipedia")
+        query = command.replace("wikipedia","")
+        results = wikipedia.summary(query,sentences=2)
+        speak("According to wikipedia...")
+        print(results)
+        speak(results)
+
+    elif 'generate email' in command:
+        os.system("app.py")
+        # from subprocess import call
+        # call(["streamlit run app.py", "-1"])
+        # command = 'streamlit run app.py'
+        # result = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+    
+    elif 'detect object' in command:
+        os.system("object.py")
+    
+    elif 'detect face' in command:
+        os.system("face_detect.py")
+
+    else:
+        print("Please say the command again")
+
+
+if __name__ == "__main__":
+    while True:
+        run_assistant()
diff --git a/models/models_downloadLink.txt b/models/models_downloadLink.txt
new file mode 100644
index 0000000..a99931f
--- /dev/null
+++ b/models/models_downloadLink.txt
@@ -0,0 +1 @@
+https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/resolve/main/llama-2-7b-chat.ggmlv3.q8_0.bin?download=true
\ No newline at end of file
diff --git a/object.py b/object.py
new file mode 100644
index 0000000..06ac41b
--- /dev/null
+++ b/object.py
@@ -0,0 +1,26 @@
+import os
+import numpy as np
+from ultralytics import YOLO
+import cv2
+# loding model
+model = YOLO('yolov8n.pt')
+# read frmaes
+cap = cv2.VideoCapture(0)
+ret = True
+while ret:
+    ret,frame = cap.read()
+    if ret==True:
+        # detecting objects from frame
+        # track object
+        result = model.track(frame, persist=True)
+
+        #plot results
+        frame_ = result[0].plot()
+
+        # visulaize
+        cv2.imshow('frame',frame_)
+        if cv2.waitKey(1)==ord('q'):
+            break
+
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..6d047a8
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,17 @@
+speechrecognition
+pyttsx3
+pyaudio
+pywhatkit
+wikipedia
+pyjokes
+setuptools
+sentence-transformers
+uvicorn
+ctransformers
+fastapi
+ipykernel
+langchain
+python-box
+ultralytics
+opencv-python
+opencv-contrib-python
\ No newline at end of file
diff --git a/yolov8n.pt b/yolov8n.pt
new file mode 100644
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From 1d4ede2f3a9b9fdf882feb194879142315da0433 Mon Sep 17 00:00:00 2001
From: Priyanshu Sharma <132160817+iPriyanshu19@users.noreply.github.com>
Date: Thu, 25 Jan 2024 00:29:25 +0530
Subject: [PATCH 2/4] Update README.md

---
 README.md | 47 ++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 46 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 39545b3..b87f4fa 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,46 @@
-# ProjectSem3
+# P19
+# Virtual Assistant README
+## Overview
+Welcome to the Virtual Assistant project! This Python-based virtual assistant leverages various libraries, including OpenCV, PyWhatKit, PyAudio, and more, to perform face detection, object detection, automated email generation, and playing music on YouTube. This README file provides essential information to get you started and use the virtual assistant effectively.
+
+## Features
+### Face Detection: The virtual assistant can detect faces in images and videos using the OpenCV library. This feature enhances the security and interaction capabilities of the assistant.
+
+### Object Detection: Utilizing OpenCV's object detection capabilities, the virtual assistant can identify and classify objects in images or video streams. This is useful for a variety of applications, including surveillance and analysis.
+
+### Automated Email Generation: The virtual assistant can compose and send emails automatically using the PyWhatKit library. This feature is handy for sending predefined messages or automated responses.
+
+### Playing Music on YouTube: With the help of PyWhatKit and other libraries, the virtual assistant can search for and play music on YouTube. Users can specify their preferences or choose from predefined playlists.
+
+## Prerequisites
+Before using the virtual assistant, ensure you have the following prerequisites installed:
+Python 3.x
+Required libraries (install using pip install -r requirements.txt):
+OpenCV
+PyWhatKit
+PyAudio
+Other necessary libraries
+
+## Usage
+### Face Detection:
+Activate face detection by specifying the appropriate command or trigger phrase.
+The virtual assistant will use the device's camera or process a specified image or video file.
+
+### Object Detection:
+Use the command or trigger phrase to initiate object detection.
+The assistant will analyze the input image or video stream and provide information about detected objects.
+
+###Automated Email Generation:
+Provide input or specify triggers to compose and send emails automatically.
+
+### Playing Music on YouTube:
+Request music playback by providing the song name, artist, or genre.
+The assistant will use PyWhatKit to search for the music on YouTube and play it.
+
+## Customization
+Feel free to customize the virtual assistant to suit your needs. You can modify the behavior, add new features, or integrate additional libraries as required.
+
+## Contributing
+Contributions are welcome! If you find bugs or want to add new features, please open an issue or submit a pull request.
+
+# Happy coding with your virtual assistant!

From b477ddae36032ebe4094ed687399c8eebda96d1c Mon Sep 17 00:00:00 2001
From: Priyanshu Sharma <132160817+iPriyanshu19@users.noreply.github.com>
Date: Thu, 25 Jan 2024 00:30:11 +0530
Subject: [PATCH 3/4] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index b87f4fa..f441697 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
 # P19
-# Virtual Assistant README
+# Virtual Assistant
 ## Overview
 Welcome to the Virtual Assistant project! This Python-based virtual assistant leverages various libraries, including OpenCV, PyWhatKit, PyAudio, and more, to perform face detection, object detection, automated email generation, and playing music on YouTube. This README file provides essential information to get you started and use the virtual assistant effectively.
 

From 52c71a9a59b056633c06a7df7c531411b8cb7146 Mon Sep 17 00:00:00 2001
From: Priyanshu Sharma <132160817+iPriyanshu19@users.noreply.github.com>
Date: Thu, 25 Jan 2024 00:30:40 +0530
Subject: [PATCH 4/4] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f441697..9b3a9e9 100644
--- a/README.md
+++ b/README.md
@@ -30,7 +30,7 @@ The virtual assistant will use the device's camera or process a specified image
 Use the command or trigger phrase to initiate object detection.
 The assistant will analyze the input image or video stream and provide information about detected objects.
 
-###Automated Email Generation:
+### Automated Email Generation:
 Provide input or specify triggers to compose and send emails automatically.
 
 ### Playing Music on YouTube: