TL;DR
By the end of this tutorial, we would have built a "Live Proctoring System" using Dyte APIs that allows the admin to monitor whether the candidate has changed during the session. 👀🧑💻
Introduction
To stop students from cheating during tests, we often assign a proctor to observe them. But we can't have someone in-person watching each student for online tests. This is where live automatic proctoring helps.
With a webcam and microphone, this method monitors students while they take online tests. It uses computer tools to spot any cheating. 👀
In the previous blog, we built a live proctoring system to detect whether there are multiple people in the candidate's frame.
In this tutorial, we will build a live proctoring system using Dyte APIs that will allow an admin to monitor if the candidate who was supposed to be in the video is still the same candidate during the whole duration in real-time. ✨
High-Level Design of the application
We aim to notify the proctor if the candidate changes during the session. 🔍
The proctor would get the candidate's details and a photograph from their webcam as proof in his meeting sidebar. 📸✨
- In this project, we will use React with Dyte UI kit and Dyte React Web Core packages for the frontend.
- For the backend, we will use FastApi (Python 3).
- We will also use database as a service by ElephantSQL (PostgreSQL).
- Lastly, we will use Imgur for storing screenshots. And the image metadata will then be saved to the same database.
Folder Structure
After completing the tutorial, the folder structure will look like this. 👇
dyte-proctoring/
├── frontend
│ ├── README.md
│ ├── package.json
│ ├── public
│ ├── src
│ │ ├── App.css
│ │ ├── App.jsx
│ │ ├── Heading.jsx
│ │ ├── ImageInput.jsx
│ │ ├── Meet.jsx
│ │ ├── Proctor.jsx
│ │ ├── index.css
│ │ ├── index.jsx
│ │ ├── logo.svg
│ │ ├── react-app-env.d.ts
│ │ ├── reportWebVitals.ts
│ │ ├── setupTests.ts
│ │ ├── stage.jsx
│ │ └── utils.js
│ ├── tsconfig.json
├── venv
├── app.py
├── imgur.py
└── requirements.txt
Step 0: Configurations and Setup
🧑💻 Before building our live proctoring system, we must set up a Dyte account.
We can create a free account by clicking the "Start Building" button on Dyte.io and signing up using Google or GitHub 🎉.
Once signed up, we can access our Dyte API keys from the "API Keys" tab in the left sidebar. We will keep these keys secure as we will use them later.🔑🤫
For our live proctoring system, we will use React for the frontend and FastAPI for building the Backend and APIs.
We will begin by creating a new directory for our project, called dyte-proctoring and navigating into it using the following commands:
mkdir dyte-proctoring
cd dyte-proctoring
Please note:
We will also require accounts on the following platforms:
- Imgur: Create an account on Imgur and create an API key. Here is a step-by-step guide
- ElephantSQL: Here is a step-by-step guide to creating a db on ElephantSQL.
Now back to the tutorial.
Step 1: Setting up the frontend
Let's start setting up our frontend project using React and Dyte! ✨
We will create a boilerplate React app using create-react-app. We can do this with the following command:
yarn create react-app frontend
This will initialize a new React app in the frontend directory. 📁
Then, we will go ahead and install the dyte react-web-core, dyte react-ui-kit and react-router packages in this project using the following command 👇
yarn add @dytesdk/react-web-core @dytesdk/react-ui-kit react-router react-router-dom
Step 2: Setting up the backend
Let's get started with setting up our FastAPI backend now. 🙌
We will go back to the root directory of our project and initiate our project here itself for the ease of hosting:
cd ..
First of all, we will go ahead and create our requirements.txt file in the root directory itself with the following content 👇
requirements.txt
cmake
fastapi
uvicorn
face_recognition
numpy
python-multipart
psycopg2-binary
httpx
python-dotenv
pydantic
requests
After this, we will go ahead and create our virtual environment with venv and install the dependencies.
python -m venv venv
source venv/bin/activate # for linux/mac
venv\Scripts\activate.bat # for windows
pip install -r requirements.txt
We will also create an environment variable file .env, for storing our credentials.
.env
DYTE_ORG_ID=<ID>
DYTE_API_KEY=<KEY>
IMGUR_CLIENT_ID=<ID>
DB_USER=<ID>
DB_PASSWORD=<PASSWORD>
DB_HOST=<HOST>
Step 3: Setting up image upload with Imgur
Let's create a new file named imgur.py and add the following code. This will help us upload our screenshots to Imgur. 🌅
Here we are connecting the Imgur API using the CLIENT_ID that we can get from our Imgur API Dashboard and using it to upload the suspicious candidate's image and get back the link to it. 🔗👇
imgur.py
import base64
from fastapi import FastAPI, UploadFile, HTTPException
from httpx import AsyncClient
from dotenv import load_dotenv
load_dotenv()
app = FastAPI()
IMGUR_CLIENT_ID = os.getenv("IMGUR_CLIENT_ID")
async def upload_image(img_data):
headers = {
"Authorization": f"Client-ID {IMGUR_CLIENT_ID}"
}
data = {
"image": img_data
}
async with AsyncClient() as client:
response = await client.post("https://api.imgur.com/3/image", headers=headers, data=data)
if response.status_code != 200:
raise HTTPException(status_code=500, detail="Could not upload image.")
print(response.json())
return response.json()["data"]["link"]
Step 4: Setting up our backend application
Now, we will create a new file named app.py and add our 🐘 ElephantSQL PostgreSQL database connection and code for our APIs, including face detection logic.
In this file, we would need to create the following routes:
GET / - Root route
POST /is_admin/ - Check if the user is an admin
POST /suspicious_list/ - This route retrieves a list of participants who are detected as suspicious
POST /same_faces/ - Detect if the face in the screenshot is the same as the face in the reference image of the candidate.
POST /upload_photo/ - Upload a reference photo of the candidate
POST /meetings - Create a new meeting
POST /meetings/{meetingId}/participants - This route is responsible for adding a participant to a specific meeting identified by meetingId
So let's get started 👇
app.py
import base64
import io
import logging
import random
import requests
import uvicorn
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from imgur import upload_image
import face_recognition
import psycopg2
import os
import base64
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from dotenv import load_dotenv
from httpx import AsyncClient
import uuid
load_dotenv()
DYTE_API_KEY = os.getenv("DYTE_API_KEY")
DYTE_ORG_ID = os.getenv("DYTE_ORG_ID")
API_HASH = base64.b64encode(f"{DYTE_ORG_ID}:{DYTE_API_KEY}".encode('utf-8')).decode('utf-8')
DYTE_API = AsyncClient(base_url='https://api.cluster.dyte.in/v2', headers={'Authorization': f"Basic {API_HASH}"})
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
fh = logging.FileHandler("app.log")
fh.setLevel(logging.DEBUG)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
fh.setFormatter(formatter)
logger.addHandler(fh)
class ParticipantScreen(BaseModel):
base64_img: str
participant_id: str
meeting_id: str
ref_image_url: str
participant_name: str
class ProctorPayload(BaseModel):
meeting_id: str
admin_id: str
class AdminProp(BaseModel):
meeting_id: str
admin_id: str
class Meeting(BaseModel):
title: str
class Participant(BaseModel):
name: str
preset_name: str
meeting_id: str
origins = [
# allow all
"*",
]
app = FastAPI()
# enable cors
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"], # allow all
allow_headers=["*"], # allow all
)
def connect_to_db():
conn = psycopg2.connect(
dbname=os.getenv('DB_USER'),
user=os.getenv('DB_USER'),
password=os.getenv('DB_PASSWORD'),
host=os.getenv('DB_HOST'),
port=5432
)
return conn
@app.get("/")
async def root():
return {"message": "Hello World"}
@app.post("/is_admin/")
async def is_admin(admin: AdminProp):
conn = connect_to_db()
cur = conn.cursor()
cur.execute("SELECT count(1) FROM meeting_host_info WHERE meeting_id = %s AND admin_id = %s", (admin.meeting_id, admin.admin_id,))
count = cur.fetchone()[0]
if(count > 0):
return { "admin": True }
else:
return { "admin": False }
@app.post("/suspicious_list/")
async def suspicious_list(meeting: ProctorPayload):
conn = connect_to_db()
cur = conn.cursor()
cur.execute("SELECT count(1) FROM meeting_host_info WHERE meeting_id = %s AND admin_id = %s", (meeting.meeting_id, meeting.admin_id,))
count = cur.fetchone()[0]
if(count > 0):
cur.execute("SELECT * FROM meeting_proc_details WHERE meeting_id = %s ORDER BY ts DESC", (meeting.meeting_id,))
rows = cur.fetchall()
conn.commit()
cur.close()
conn.close()
return rows
else:
conn.commit()
cur.close()
conn.close()
raise HTTPException(status_code=401, detail="Participant dose not has admin role")
@app.post("/same_faces/")
async def same_faces(participant: ParticipantScreen):
conn = connect_to_db()
cur = conn.cursor()
cur.execute("CREATE TABLE IF NOT EXISTS meeting_proc_details (ts TIMESTAMP, meeting_id VARCHAR(255), participant_id VARCHAR(255), img_url VARCHAR(255), verdict VARCHAR(255))")
img_url = participant.ref_image_url
response = requests.get(img_url)
ref_img_data = io.BytesIO(response.content)
img_data = participant.base64_img.split(",")[1]
img_data_dc = base64.b64decode(participant.base64_img.split(",")[1])
file_obj = io.BytesIO(img_data_dc)
unknown_image = face_recognition.load_image_file(file_obj)
known_image = face_recognition.load_image_file(ref_img_data)
biden_encoding = face_recognition.face_encodings(known_image)[0]
unknown_encoding = face_recognition.face_encodings(unknown_image)[0]
results = face_recognition.compare_faces([biden_encoding], unknown_encoding)
is_same_face = True
for res in results:
is_same_face = is_same_face and res
if not is_same_face:
logger.info(
f"Detected different faces for participant {participant.participant_id}"
)
verdict = f"Participant Name: {participant.participant_name} <> Anomaly: Different Faces Detected <> Participant ID: {participant.participant_id}"
cur.execute("SELECT count(1) FROM meeting_proc_details WHERE meeting_id=%s AND participant_id=%s AND ts >= (current_timestamp - INTERVAL '10 minutes')", (participant.meeting_id, participant.participant_id))
count = cur.fetchone()[0]
if count == 0:
upload_resp = await upload_image(img_data)
cur.execute("INSERT INTO meeting_proc_details (ts, meeting_id, participant_id, img_url, verdict) VALUES (current_timestamp, %s, %s, %s, %s)",
(participant.meeting_id, participant.participant_id, upload_resp, verdict)
)
conn.commit()
cur.close()
conn.close()
if count == 0:
return { "id": participant.participant_id, "different_faces_detected": True, "url": upload_resp }
return { "id": participant.participant_id, "different_faces_detected": True, "url": "not uploaded" }
return {"id": participant.participant_id, "different_faces_detected": False}
@app.post("/upload_photo/")
async def upload_photo(participant: ParticipantScreen):
img_data = participant.base64_img.split(",")[1]
conn = connect_to_db()
cur = conn.cursor()
cur.execute("CREATE TABLE IF NOT EXISTS meeting_proc_details (ts TIMESTAMP, meeting_id VARCHAR(255), participant_id VARCHAR(255), img_url VARCHAR(255), verdict VARCHAR(255))")
verdict = f"REF_IMAGE"
upload_resp = await upload_image(img_data)
cur.execute("INSERT INTO meeting_proc_details (ts, meeting_id, participant_id, img_url, verdict) VALUES (current_timestamp, %s, %s, %s, %s)",
(participant.meeting_id, participant.participant_id, upload_resp, verdict)
)
conn.commit()
cur.close()
conn.close()
return {"id": participant.participant_id, "img_url": upload_resp, "reference_image_uploaded": True}
@app.post("/meetings")
async def create_meeting(meeting: Meeting):
response = await DYTE_API.post('/meetings', json=meeting.dict())
if response.status_code >= 300:
raise HTTPException(status_code=response.status_code, detail=response.text)
admin_id = ''.join(random.choices('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789', k=32))
resp_json = response.json()
resp_json['admin_id'] = admin_id
meeting_id = resp_json['data']['id']
conn = connect_to_db()
cur = conn.cursor()
cur.execute("INSERT INTO meeting_host_info (ts, meeting_id, admin_id) VALUES (CURRENT_TIMESTAMP, %s, %s)", (meeting_id, admin_id))
conn.commit()
cur.close()
conn.close()
return resp_json
@app.post("/meetings/{meetingId}/participants")
async def add_participant(meetingId: str, participant: Participant):
client_specific_id = f"react-samples::{participant.name.replace(' ', '-')}-{str(uuid.uuid4())[0:7]}"
payload = participant.dict()
payload.update({"client_specific_id": client_specific_id})
del payload['meeting_id']
resp = await DYTE_API.post(f'/meetings/{meetingId}/participants', json=payload)
if resp.status_code > 200:
raise HTTPException(status_code=resp.status_code, detail=resp.text)
return resp.text
if __name__ == "__main__":
uvicorn.run("app:app", host="localhost", port=8000, log_level="debug", reload=True)
This code defines a ⚡️ FastAPI application with an endpoint /detect_faces, which takes in a base64 encoded image and returns a boolean value indicating if the face matches the reference image of the candidate.
It uses the face recognition library to detect faces in the image received.
The code also makes use of the Dyte API for meeting-related operations. 📹
We can start the backend server simply by using the following command 🧑💻:
python app.py
This Python server helps us create and join meetings, detect different faces, and get the list of suspicious candidates. 🕵️
Here, when we hit the /same_faces endpoint with an image file encoded as a base64 string, the different_faces_detected key of the response would be set to True if the face of the candidate from the reference image doesn't match the face in the screenshot, else it will be set to False.
We can call this from our frontend with the participant's webcam feed.
With this sorted, let's return to our React application and create our UI. ✨
Step 5: Setting up the Meeting UI
First, let us add our CSS file, create a new file, frontend/src/App.css and paste the following code.
.App {
text-align: center;
}
.App-logo {
height: 40vmin;
pointer-events: none;
}
@media (prefers-reduced-motion: no-preference) {
.App-logo {
animation: App-logo-spin infinite 20s linear;
}
}
.App-header {
background-color: #282c34;
min-height: 100vh;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
font-size: calc(10px + 2vmin);
color: white;
}
.App-link {
color: #61dafb;
}
.heading-proctor {
font-size: x-large;
font-weight: bolder;
color: #fff;
}
@keyframes App-logo-spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
.file-input label {
margin-top: 20px;
display: block;
position: relative;
width: 200px;
height: 50px;
border-radius: 10px;
background-color: #2160fd;
display: flex;
align-items: center;
justify-content: center;
flex-direction: row;
color: #fff;
font-weight: bold;
cursor: pointer;
transition: transform 0.2s ease-out;
}
.file {
opacity: 0;
width: 0.1px;
height: 0.1px;
position: absolute;
}
Next, we will add the initial Dyte Meeting component to our app. We can do this by replacing the contents of frontend/src/App.jsx with the following code:
import { useEffect, useState } from "react";
import Home from "./Home";
import { BrowserRouter, Routes, Route, Link } from "react-router-dom";
import "./App.css";
import Stage from "./Stage";
const SERVER_URL = process.env.SERVER_URL || "http://localhost:8000";
function App() {
const [meetingId, setMeetingId] = useState();
const createMeeting = async () => {
const res = await fetch(`${SERVER_URL}/meetings`, {
method: "POST",
body: JSON.stringify({ title: "Joint Entrance Examination" }),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
window.localStorage.setItem("adminId", resJson.admin_id);
setMeetingId(resJson.data.id);
};
useEffect(() => {
window.localStorage.removeItem("refImgUrl");
const id = window.location.pathname.split("/")[2];
if (!!!id) {
createMeeting();
}
}, []);
return (
<BrowserRouter>
<Routes>
<Route path="/" element={<Home meetingId={meetingId} />}></Route>
<Route path="/meeting/:meetingId" element={<Stage />}></Route>
</Routes>
</BrowserRouter>
);
}
export default App;
This component will create a Dyte meeting link and an adminId for the admin. We will store the adminId secretly in localstorage. The adminId will be used later for accessing any sensitive data.
Home component
The home component renders the / route. Create a file as frontend/src/Home.jsx.
import { Link } from "react-router-dom";
function Home({ meetingId }) {
return (
<div
style={{
height: "100vh",
width: "100vw",
fontSize: "x-large",
display: "flex",
justifyContent: "center",
alignItems: "center",
}}
>
{meetingId && !window.location.pathname.split("/")[2] && (
<Link to={`/meeting/${meetingId}`}>Create and Join Meeting</Link>
)}
</div>
);
}
export default Home;
Heading component
Now we will create a file as frontend/src/Heading.jsx.
const Heading = ({ text }) => {
return (
<div
className="heading-proctor"
style={{
padding: "10px",
textAlign: "center",
backgroundColor: "#000",
borderBottom: "solid 0.5px gray",
}}
>
{text}
</div>
);
};
export default Heading;
Let us now build the component to upload a reference image of the candidate.
Create a file frontend/src/ImageInput.jsx
import { useState } from "react";
function ImageUploader({ setImgUploadedStatus }) {
const [selectedFile, setSelectedFile] = useState(null);
const [uploading, setUploading] = useState(false);
const [uploadError, setUploadError] = useState(null);
const [uploadSuccess, setUploadSuccess] = useState(false);
const handleFileChange = (event) => {
setSelectedFile(event.target.files[0]);
setUploadSuccess(false);
setUploadError(null);
};
const handleSubmit = async (event) => {
event.preventDefault();
setUploading(true);
setUploadError(null);
try {
const formData = new FormData();
formData.append("image", selectedFile);
const response = await fetch("https://api.imgur.com/3/image", {
method: "POST",
headers: {
Authorization: "Client-ID 48f0caef7256b40",
},
body: formData,
});
if (!response.ok) {
throw new Error("Failed to upload image");
}
const data = await response.json();
window.localStorage.setItem("refImgUrl", data.data.link);
setUploadSuccess(data.data.link);
setImgUploadedStatus(true);
} catch (error) {
setUploadError(error.message);
} finally {
setUploading(false);
}
};
return (
<div
style={{
display: "flex",
justifyContent: "center",
flexDirection: "column",
alignItems: "center",
fontSize: "x-large",
}}
>
<div>Hey Candidate 👋</div>
<div style={{ marginBottom: "30px" }}>
Please upload a image of yours to proceed
</div>
<input
type="file"
id="file"
style={{ border: "0.5px white solid" }}
onChange={handleFileChange}
/>
<form
onSubmit={handleSubmit}
style={{
display: "flex",
flexDirection: "column",
alignItems: "center",
marginTop: "1rem",
}}
>
<button
type="submit"
disabled={!selectedFile || uploading || uploadSuccess}
style={{
marginTop: "10px",
padding: "0.5rem 1rem",
backgroundColor: "#3460f3",
color: "#fff",
border: "none",
borderRadius: "0.25rem",
cursor: "pointer",
}}
>
{uploading ? "Uploading..." : "Upload"}
</button>
</form>
{uploadError && (
<div style={{ marginTop: "10px", color: "red" }}>{uploadError}</div>
)}
</div>
);
}
export default ImageUploader;
It will look like this 👇
Let's create a staging area for participants joining the meeting. Admin bypasses the staging area, but the candidate will be asked to upload a reference image of himself on this page.
For this, we will create another file, frontend/src/Stage.jsx
import { useState, useEffect } from "react";
import ImageUploader from "./ImageInput";
import Meet from "./Meet";
const SERVER_URL = process.env.REACT_APP_SERVER_URL || "http://localhost:8000";
const Stage = () => {
const [isAdminBool, setAdminBool] = useState(null);
const [isRefImgUploaded, setImgUploadedStatus] = useState(null);
const meetingId = window.location.pathname.split("/")[2];
const isAdmin = async (id) => {
const res = await fetch(`${SERVER_URL}/is_admin`, {
method: "POST",
body: JSON.stringify({
admin_id: window.localStorage.getItem("adminId") || "",
meeting_id: meetingId || "",
}),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
setAdminBool(resJson.admin);
};
useEffect(() => {
isAdmin();
}, []);
return (
<div
style={{
height: "100vh",
width: "100vw",
display: "flex",
justifyContent: "center",
alignItems: "center",
color: "white",
}}
>
{isAdminBool == null ? (
<>Loading...</>
) : (
<>
{isAdminBool || (isAdminBool === false && isRefImgUploaded) ? (
<Meet isAdminBool={isAdminBool} />
) : (
<ImageUploader setImgUploadedStatus={setImgUploadedStatus} />
)}
</>
)}
</div>
);
};
export default Stage;
Now, let's delve into the Meet component that renders on route /meeting/:meetingId.
When the admin clicks on the link provided on the / route, he gets redirected to the meeting page, where we add the user to the meeting as a participant with group_call_host preset. 🤙
Since this user created the meeting and was redirected to the meet page, we will assign him the admin role. Now the link from the address bar can be shared with the candidates.
When a candidate opens the shared link, they become a regular user. And for every regular user, the component emits screenshots of the users' videos to our directed to our Python server. 🐍
/* eslint-disable */
import { useState, useEffect, useRef } from "react";
import { DyteMeeting, provideDyteDesignSystem } from "@dytesdk/react-ui-kit";
import { useDyteClient } from "@dytesdk/react-web-core";
import Proctor from "./Proctor";
import Heading from "./Heading";
import { SendImageToBackendMiddleware, joinMeeting } from "./utils";
// Constants
const SERVER_URL = process.env.SERVER_URL || "http://localhost:8000";
let LAST_BACKEND_PING_TIME = 0;
const DETECT_FACES_ENDPOINT = `${SERVER_URL}/same_faces`;
const TIME_BETWEEN_BACKEND_PINGS = 10000;
const Meet = () => {
const meetingEl = useRef();
const [meeting, initMeeting] = useDyteClient();
const [userToken, setUserToken] = useState();
const [isAdminBool, setAdminBool] = useState(null);
const meetingId = window.location.pathname.split("/")[2];
function SendImageToBackendMiddleware() {
return async (canvas, ctx) => {
const currentTime = Date.now();
if (currentTime - LAST_BACKEND_PING_TIME > TIME_BETWEEN_BACKEND_PINGS) {
LAST_BACKEND_PING_TIME = currentTime;
const imgBase64String = canvas.toDataURL("image/png");
const response = await fetch(DETECT_FACES_ENDPOINT, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({
base64_img: imgBase64String,
participant_id: meeting?.self.id,
participant_name: meeting?.self.name,
ref_image_url: window.localStorage.getItem("refImgUrl"),
meeting_id: meetingId,
}),
});
}
};
}
const isAdmin = async (id) => {
const res = await fetch(`${SERVER_URL}/is_admin`, {
method: "POST",
body: JSON.stringify({
admin_id: window.localStorage.getItem("adminId") || "",
meeting_id: meetingId || "",
}),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
setAdminBool(resJson.admin);
};
const joinMeetingId = async () => {
if (meetingId) {
const authToken = await joinMeeting(meetingId);
await initMeeting({
authToken,
});
setUserToken(authToken);
}
};
useEffect(() => {
if (meetingId && !userToken) joinMeetingId();
isAdmin();
}, []);
useEffect(() => {
if (userToken) {
provideDyteDesignSystem(meetingEl.current, {
theme: "dark",
});
}
}, [userToken]);
useEffect(() => {
if (isAdminBool === false && meeting?.self) {
meeting.self.addVideoMiddleware(SendImageToBackendMiddleware);
}
}, [meeting?.self]);
return (
<div style={{ height: "96vh", width: "100vw", display: "flex" }}>
{userToken && (
<>
{isAdminBool && (
<div
style={{
width: "40vw",
height: "100vh",
overflowY: "scroll",
backgroundColor: "black",
borderRight: "solid 0.5px gray",
}}
>
<Heading text={"Proctoring Information"} />
<Proctor meeting={meeting} />
</div>
)}
{isAdminBool ? (
<div style={{ width: "60vw", height: "96vh" }}>
<Heading text={"Proctoring Admin Interface"} />
<DyteMeeting mode="fill" meeting={meeting} ref={meetingEl} />
</div>
) : (
<div style={{ width: "100vw", height: "96vh" }}>
<Heading text={"Proctoring Candidate Interface"} />
<DyteMeeting mode="fill" meeting={meeting} ref={meetingEl} />
</div>
)}
</>
)}
</div>
);
};
export default Meet;
Let's briefly go through some of the functions:
isAdmintalks to the Python server to identify whether the current client is the admin.joinMeetingadds the current client to the meeting.SendImageToBackendMiddlewaresends screenshots of candidates' videos to the Python server.
Proctor component
The proctor component gets activated only for admins. The proctor component, with the help of adminId fetches the list of suspicious candidates and renders it in a chat-like format. Create a file frontend/src/Proctor.jsx
import { useEffect, useState } from "react";
import { getCandidateStatus } from "./utils";
const Proctor = () => {
const [candidateStatuses, updateCandidateStatusState] = useState([]);
const [error, setError] = useState("");
const updateCandidateStatus = async () => {
try {
const res = await getCandidateStatus();
updateCandidateStatusState(res);
} catch (e) {
setError("User don't have admin privileges.");
}
};
useEffect(() => {
updateCandidateStatus();
}, []);
useEffect(() => {
if (candidateStatuses?.map) {
const id = setInterval(() => {
updateCandidateStatus();
}, 30000);
return () => {
clearInterval(id);
};
}
}, [candidateStatuses]);
return (
<>
<div style={{ padding: "0px 20px" }}>
{candidateStatuses?.map && candidateStatuses ? (
candidateStatuses.map((status) => (
<div
style={{
display: "flex",
justifyContent: "start",
margin: "50px 20px",
}}
>
<div style={{ marginRight: "20px" }}>
<img
src="https://images.yourstory.com/cs/images/companies/Dyte-1608553297314.jpg"
style={{
borderRadius: "50px",
height: "60px",
border: "1px double lightblue",
}}
/>
</div>
<div
style={{
textAlign: "center",
padding: "20px",
backgroundColor: "#2160fd",
fontSize: "large",
fontWeight: "400",
borderRadius: "10px 10px 10px 10px",
width: "80%",
}}
>
<div
style={{
color: "white",
padding: "20px 0px",
textAlign: "left",
}}
>
{status[4].split("<>").map((text) => (
<div>{text}</div>
))}
<div>Timestamp: {new Date(status[0]).toLocaleString()}</div>
</div>
<img
style={{ borderRadius: "10px", width: "100%" }}
src={status[3]}
/>
</div>
</div>
))
) : (
<div style={{ color: "white" }}>
Wait or check if you have admin privileges to access the proctoring
dashboard.
</div>
)}
</div>
</>
);
};
export default Proctor;
Utility functions
Now we will add utility functions.
Create a file frontend/src/utils.js.
const joinMeeting = async (id) => {
const res = await fetch(`http://localhost:8000/meetings/${id}/participants`, {
method: "POST",
body: JSON.stringify({
name: "new user",
preset_name: "group_call_host",
meeting_id: meetingId,
}),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
console.log(resJson.detail);
const data = JSON.parse(resJson.detail);
return data.data.token;
};
const getCandidateStatus = async () => {
const response = await fetch("http://localhost:8000/suspicious_list", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({
meeting_id: window.location.pathname.split("/")[2],
admin_id: window.localStorage.getItem("adminId") || "undefined",
}),
});
const res = await response.json();
if (res.details) return undefined;
console.log(res);
return res;
};
export { joinMeeting, getCandidateStatus };
To start the React app on the local server, we can run the following command:
yarn start
Now, upon visiting http://localhost:3000/, we should be able to see the Dyte meeting in our browser.
Step 6: Adding the face detection logic to the frontend
Since now we have a nice backend server to detect faces and a great UI 🎉, we can add the face detection logic to our frontend. For this, we will first add some constants to our previously edited frontend/src/App.jsx file:
We will be using the above constants in the SendImageToBackendMiddleware function, which we will add to our App component just after the useDyteClient hook. 🪝
The SendImageToBackendMiddleware is a Dyte Video Middleware. Middlewares are add-ons that we can use to easily add effects and filters to your audio and video streams.
Here, we use the middleware functionality to get the canvas object of the participant's webcam feed, convert it to a base64 encoded image, and send it to our backend server.
That was all the code we needed to add basic proctoring functionality to our Dyte meeting. 👍
The app sends a screenshot of the participant's webcam feed to the backend server every 30 seconds. If the backend detects the face isn't similar to the reference image, it sends a warning notification to the proctor. ⚠️
The backend also logs the participant's ID and the time of the detection in the terminal. This can be used to keep track of the participants who may have cheated during the meeting for later review.
Step 7: Trying out our live proctoring system
Ta-da! 🎩✨ It's time to put our live proctoring system to the test and see it in action!
- First, let's look at the candidate's view after uploading the reference image. The candidate can see that the proctor is in the meeting but cannot see the Proctoring Panel. 🧑💻
- Now, let's swap the candidates.
- In the proctor's view, we can see the details (proctoring information) along with proof when the candidate got swapped in the candidate's webcam view. 🙌
🧑💻 You can try out the live proctoring system here. And here's the link to the repository for you to take a look at the whole codebase.
Conclusion
Celebrate! 🎉✨ We've built a powerful live proctoring system with Dyte, ensuring integrity and fairness in online exams and interviews. But that's not all! We can now create our own customized online classroom or meeting platform.
We can now use this live proctoring system to proctor our online exams and interviews. ✍️
The possibilities are endless with Dyte, go ahead and try bringing your ideas to life by visiting dyte.io! 🚀
