We'll show you how to setup a video streaming web server with face recognition and detection in less than 5 minutes with Arduino IDE. There's a library for the Arduino IDE and it works with ESP devices. You can follow this tutorial, #Setup Communication path for arduino (In place of 'COM5' put the port to which your arduino is connected), #importing the Haarcascade for face detection, face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml'). This project will teach you how to use the easyVR for Voice recognition: Note: Voice recognition is different from speech recognition, voice recognition recognizes only a single person's voice, while speech recognition can recognize everybody's voice. The servo's connected to the Arduino provides a pan/tilt mechanism where the camera is connected to one of the servo. Choose which one seems easiest to you: * Face Detection and Tracking With Arduino and OpenCV * Facial recognition: OpenCV on the camera board - Raspberry Pi OpenCV provides a training method or pre-trained models called as Cascade Classifier. Python does the image processing, Arduino controls the servos. https://stackoverflow.com/questions/23708898/pip-i Once OpenCV is installed we are good to go To check if its properly installed open your Python interpreter and import the library. These coordinates are sent to the arduino for moving the angle of the camera. So first we need Python 2.7 up and running. I have attached the horizontal moving servo on the shaft of the vertical moving servo in which the camera is mounted. This project requires pyserial and opencv libraries which I have downloaded using pip. I am on Python 2.x and OpenCV 2.x - mainly because this is how the OpenCV-Python Tutorials are setup/based on. I hope that you have learned something new. Upon downloading, the xml file can be loaded using cv2.CascadeClassifier('haarcascade_frontalface_default.xml'). Detecting face mask and body temperature helps in . Store that data in electrical or digital format on a server. Bring the power of face unlock to your shelf, door or wardrobe with Bolt IoT. I have used a readily available kit for the Pan-Tilt. Subscribe to my youtube channel for more stuff related to python and Arduino. Consistently individuals bring about an enormous loss of property a life because of fire and blasts. Right-click on "My Computer" (or "This PC" on Windows 8.1) -> left-click Properties -> left-click "Advanced" tab -> left-click "Environment Variables" button.Add a new User Variable to point to the OpenCV (either x86 for 32-bit system or x64 for 64-bit system.) It took me days to have got it working. After spending hours figuring it out, I began looking for similar projects online until I found this project(, ). OpenCV already contains many pre-trained classifiers for face, eyes, smile etc. Install the ESP32 add-on In this example, we use the Arduino IDE to program the ESP32-Cam board. Nice post and thank you for your help!Though I'm getting an error in when I run the code in step 4. Blynk is a cloud platform and mobile phone app that allows you to receive messages from IoT devices and microcontrollers and also control these devices. Now we can move to the coding part. 9 facial recognition Projects - Arduino Project Hub Sign In Add project 9 facial recognition projects Spectrino: TinyML Arduino & IoT Based Touch-Free. Let's create face and eye detector with OpenCV.First we need to load the required XML classifiers. When a picture is taken for verification, any distortion caused by the angle the cam From these coordinates, the center coordinates of the image can be calculated using x+width/2 and y+height/2. The folder where the "AccessTo_webcam.py" file is stored. This project used as arduino interface to control the motors, and the Creator Ci20 as image processor with a script in python. Just attach two servos to arduino. Open Arduino -> Sketch -> Include Library -> Add .ZIP Library -> Navigate to downloaded zip file -> add Arduino Source Code/program The source code/program ESP32 CAM Face Recognition can be found in Library Example. We first used the standard OpenCV example . You might be thinking what is OpenCV, isn't it? I am looking to code an arduino with a camera that recognizes when it sees any human face. Share this if you liked it. 2 years ago, Help me i follow your program and program face trainer always eror like this please help me: Traceback (most recent call last): File "C:\Users\USER\OneDrive\Documents\python\opencv\face recognition\face_trainer.py", line 11, in recognise = cv2.face.LBPHFaceRecognizer_create()AttributeError: module 'cv2.cv2' has no attribute 'face', Answer It is capable of performing all the facial recognition stages on its own such as face detection, features extraction, face recognition using OpenCV libraries. In my case, I've extracted the package (essentially a folder) straight to my F drive. Download Citation | On Nov 25, 2021, Nawin Najat Mohammed and others published Line-Following Service Robot Using Arduino with Face Recognition for Offices | Find, read and cite all the research . Data collection is rather the easiest step in this project. 2 years ago, Thank you very much for your work!!! Python does the image processing, Arduino controls the servos. The Arduino would store a couple of faces and if it recognizes a face, it displays a box around the face on the LCD. The facial recognition is a very useful tool incorporated in many modern devices to detect human faces for tracking, biometric and to recognize human activities. Make sure you check the Current Working Directory (CWD)!!! Aurduino Project. We need to test whether we can now do these in Anaconda (via Spyder IDE): To confrim that Anaconda is now able to import the OpenCV-Python package (namely, cv2). I am a bit of a beginner to arduino so please try to explain things as simple as possible please. Thanks. Go through the video which I have linked above to find how Serial Communication works and to establish one.You will find all the required files in the video description. Those XML files are stored in opencv/data/haarcascades/ folder. Now, the system can perform face recognition and detection. Make code to train the recognizer 8. Refer the code below, paste it in Arduino IDE and save it as 'servo.ino' in the same folder as face.py and haarcascade. The camera catches the facial picture and compares it with the image which is stored in the database. Face Detection Tracking And Recognition Using Opencv Python And Arduino 4 High Security Surveillance Camera using OpenCV, Python & Arduino most recent commit 2 years ago +str(sampleN)+ ".jpg", gray[y:y+h, x:x+w]), Step 7: Make Code to Train the Recognizer, from PIL import Image # For face recognition we will the the LBPH Face Recognizer. Anaconda is essentially a nicely packaged Python IDE that is shipped with tons of useful packages, such as NumPy, Pandas, IPython Notebook, etc. It seems to be recommended everywhere in the scientific community. The servo should move as you move the object. Introduction. First open CMD and type the following codes:- >pip install serial >pip install opencv-python >pip install numpy these commands will install the necessary modules. It made me aware of the Serial function Serial.parseInt() which takes integer inputs from an incoming serial of bytes(check here). OpenCV already contains many pre-trained classifiers for face, eyes, smile etc. Hope you like it. Check out, site to download the complete OpenCV package. It's just started but I will post stuff related to python, Arduino and electronics. Creating Local Server From Public Address Professional Gaming Can Build Career CSS Properties You Should Know The Psychology Price How Design for Printing Key Expect Future. There you go. Project tutorial by Team Enzi 6,235 views 4 comments SimAr stands for Semi-Intelligent Multifunctional Robot SimAr is a humanoid robot which is designed to unleash the secrets Of the robotic. Test to confirm 5. If this is Adesh singh.. September 19, 2021. Pick a version you like (2.x or 3.x). video file in a directory. The 1st step for facial recognition was to have access to a camera or a computer vision. So go to Files -> Examples -> esp32cam -> WifiCam. In a previous tutorial, I shared how you can communicate between Arduino and Python using 'pyserial' module and control a LED. Track your face using OpenCV's facial recognition. In this tutorial, you will learn how to make Face Recognition based Door Lock Control system using ESP32 Camera Module and a 12V electronic lock. as shown in the above image. Install Anaconda 2. Once downloaded add this zip library to Arduino Libray Folder. All the necessary information is provided in it. similar steps will be followed for person Y. Step 4: Arduino Code : After the python script is ready we need arduino sketch to control the servo. Simillerly download "face_recogniser1.py" that will establish the serial communication between Arduino and the python program. Make code for face detection 6. Question ESP32-CAM Video Streaming, Face Recognition Using Arduino IDE: This article is a short introduction to the ESP32-CAM motherboard. Very interesting, Yahia. Arduino Uno is a microcontroller board based on the ATmega328P . This may sound difficult but trust me it isn't, All you need is basic knowledge of Arduino and Python. Connect the positive from the DC power source to the common of the . In brief, we will go through all the folders and images which are present in the "image_data" folder and create a dictionary that will contain the label ID and the corresponding name. Upon downloading, the xml file can be loaded using. With the help of deep neural network based Convolution Neural Network algorithm, face mask has been recognized and for body temperature, LM35 temperature sensor is used and this system undergoes data pre-processing, training, detecting face mask and temperature. The OpenCV returns the cartesian coordinates of the image upon detection along with the height and width. Then each time when face recognition triggers it again maps the special features of your face. for example: In the "image_data" folder I have created two more folders named "HRK" and "Yahiya". Make code to train the recognizer 8. If you see an error in CMD, Do not panic you probably need to set environment variable. The function used for face detection is cv2.CascadeClassifier.detectMultiScale() with the 'scale factor' value as 1.1(default) and 'minNeighbour' value as 6. So, you need to have Arduino IDE installed as well as the ESP32 add-on. This paper details the design and development of IOT based security surveillance system in buildings with Wi-Fi network connectivity. Here we will deal with detection. In this project, I have used the OpenCV's Harr cascade classifiers for detecting human faces and pan/tilt servo mechanism to track the user's face using Arduino UNO. Our goal is to copy and paste the cv2.pyd file to this directory (so that we can use the import cv2 in our Python codes.). The Anaconda Site-packages directory (e.g. Now we will use that data for face recognition. Commercial image recognition systems use custom high speed processors, GB of memory and databases containing millions of images that have been manually classified by people. After finding nothing online, I am wondering if this is possible at all? And finally, we will create a ".yml" file. Those XML files are stored in opencv/data/haarcascades/ folder. It seems to be recommended everywhere in the scientific community. You can either create your own dataset or start with one of the available face databases, http://face-rec.org/databases/ gives you an up-to-date overview. (F:\opencv). Inside the "image_data" folder create some additional folders with the person's name, where we will store the data. To test first make sure that servos are properly connected to arduino and sketch is uploaded. I was looking for something like that about AI. Through the UART / I2C port, HuskyLens can connect yout Arduino board like to help you make very creative projects . out = cv2.VideoWriter("output_video.avi", fourcc, 20.0, (640, 360)). pip install face_recognition. At Coolest Projects 2018, we showcased the Wia platform with a facial recognition Ferris wheel! Step 1: Install Anaconda Also make sure that the XML file for face detection is saved in the same directory which contains the python script. Download the "face_trainer.py" file and place it in the main project folder. ARDUINO PYTHON arduino T. . Then load our input image (or video) in grayscale mode OR we can use camera( for Real time face detection). in function 'cv::face::LBPH::train' "Any idea why this error is happening? 1 year ago Let's create face and eye detector with OpenCV.First we need to load the required XML classifiers. So create a new folder, name it anything you want. You can also add more images but see to it that data collected for all the persons contains the same number of images. Check out Anaconda to get it installed. Answer (1 of 3): Can I use an Arduino Uno for Facial reconition or would it be easier to use a Raspberry Pi 3? Firstly, go to the official OpenCV site to download the complete OpenCV package. OpenCV uses Harr cascade of classifiers where each frame of the video is passed through stages of classifiers and if the frame passes through all the classifiers, the face is present else the frame is discarded from the classifier i.e the face is not detected. I want a C program for face recognition. If the subject face is a recognized face stored in a database and the password input by the subject both matches simultaneously, then only the door of this system is unlocked which is . Note that the camera does not support using both interfaces at the same time. For the Authorized person, the onboard white LED is turned ON and also the electronic lock is opened. When it sees you, it won't stop following! Author . Arduino Voice recognition! Record quantitative data (PM 1.0, 2.5 and 10.0). All the explanation is provided in it. HuskyLens is an easy-to-use AI machine vision sensor. (Image credit: Tom's Hardware) 6. We'll guide you through how to create a web server using facial recognition and detection in under 5 minutes using Arduino IDE. After everything is done last thing to do is test if it works. For communication, I used "Serial Communication". Facial-recognition-based-automatic-door-lock-unlock-system Introduction This project aims at automating the locking and unlocking of the main door of the house. then proceed with face_recognition, this too installs with pip. Follow the next steps to get up and running! Increasing the 'minNeighbour' can improve facial detection but sacrifices in execution speeds which would lead to a delayed response from the servo. Project tutorial by Dhruv Sheth 18,452 views 12 comments 56 respects Smart Door with Face Unlock Project tutorial by Divins Mathew 46,981 views 8 comments 45 respects DasCognitiveServices ). Arduino IDE is basically C code, which is much more efficient and has smaller memory footprint. The coordinates describe the top-left pixel values(x and y) along with the height and width. The one I used is pretty cheap, and very easy to assemble. When using the Face Recognition function, always use CIF resolution. My current python and OpenCV version is 3.8 and 4.4.0, so make sure you have a similar or a higher version. Using Arduino Project Guidance. OpenCV (Open Source Computer Vision Library: http://opencv.willowgarage.com/wiki/) is an open-source library that includes several hundreds of real-time computer vision algorithms. Make code to create data set 7. Set Environmental Variables 4. For which we need some data. Python Project. Thus, the value 6 seemed optimal. Follow the below steps to build a video streaming web server with the ESP32-Cam that you can access on your local network. Thank you for your time. Arduino Face Detection. 5. The Arduino UNO is the best board to get started with electronics and coding. In a previous tutorial, I shared how you can communicate between Arduino and Python using 'pyserial' module and control a LED. We are doing face recognition, so youll need some face images! Learn Arduino the Easy Way Are you new to Arduino? I have installed opencv-contrib. I recommend collecting nearly about 20 images per person. Ghosty and Skully can follow your face and they know when you are smiling to laugh with you! Append %OPENCV_DIR%\bin to the User Variable PATH. Overview. Go through this post it may help you. September 19, 2021. Whenever you will go in front of the camera . may look like (Note: many thanks to Pete's and Warren's suggestions in the comment field - I have replaced my original test code with his - please test it yourself and let us know if this works better): This test is VERY IMPORTANT. False - fail to write out video. Right-Click within the dataset folder and select New Folder. We use an Arduino to build an autonomous "follow me" cooler that connects to a smartphone via Bluetooth and uses GPS to navigate. In the absence of it, I have noticed some sort of vibration in them without making them move. Python does the image processing, Arduino controls the servos. Facial recognition AKA face ID is one of the most important feature on mobile phones nowadays. The python script also requires some modification(in line 9)by entering the correct COM port of your arduino before execution. You'll need more than one sample to learn a model. with the 'scale factor' value as 1.1(default) and 'minNeighbour' value as 6. Bonus: charge your phone with free clean energy! Step 3: Python Script Before starting to write code first thing to do is make a new folder as all of the code needs to be stored in same folder. NOTE: I MADE THIS PROJECT FOR SENSOR CONTEST AND I USED CAMERA AS A SENSOR TO TRACK AND RECOGNITION FACES.So, Our GoalIn this session, 1. It will call out your name and also display your name on the computer screen, as shown in Fig. Assuming that you have data collected for person X and Y. we will label person X as 1 which will be his label ID and name will be X itself. Adding facial recognition to a microcontroller system. It will take a few seconds to connect to arduino and then you should be able to see a window streaming the web cam. I found this part challenging as I tried many ways to send the coordinates sequentially to the arduino but the response was slow. ?Thanks in advance for your answers. If it is outside the squared region when the face is moved, then the servo will align the camera to bring it inside the region. The python sends the center coordinates in a single string. For example, if the ith index in the list of faces represents the 5th individual in the database, then the corresponding ith location in the list of labels has value equal to 5. Face Recognition Based Attendance management system:- This Project Based on the Face Rec Adesh singh.. September 19, 2021. 2 years ago, Your welcome, Amedo1. You can either create your own dataset or start with one of the available face databases, gives you an up-to-date overview. When you flash and run this new Sketch you should see 'Face recognised' in the serial monitor when a matched face is found. Now you have trained your own model. Face recognition door lock system is capable of making decisions based on facial recognition technology. #ArduinoProject #FaceRecognition #DIYProject How To Make Face Recognition Door Lock (Ep 03) 34,830 views Aug 27, 2021 Hey Guys, In this video I'm making a Face Recognition Door Lock using. In CMD type >> python and hit enter, Python interface should display. To do this first download and Install. Install Anaconda 2. This project is awesome!A short question:What do I have to do if I just want to send a short message to the Arduino if there is no face detected?? Using the technique I'm going to show you it was measured to be 259.91Hz only 0.09Hz away from an Exact Middle C Frequency of 260Hz. Make code to recognize the faces &Result. and finally result will came in front off your eyesu can also download the zip file from below the link : So, in this tutorial we performed the task of face detection+recognition using OpenCV..if you like this tutorial.. plzzz subscribe me and vote for me..thanks friends. After spending hours figuring it out, I began looking for similar projects online until I found this project(here). . I hope that this will help you out. OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. The pre-trained models are located in the data folder in the OpenCV installation. After sketch is uploaded make sure to close the IDE so the port is free to connect to python. Download Open CV Package 3. step 3: Data collection Step 4: Training step 5: Face recognition step 6: Programming Arduino I will explain all the steps below. I have used 'haarcascade_frontalface_default.xml' which is a pre- trained model for detecting human faces and can be downloaded from Git-Hub(here). Share it with us! Download the python file "AccessTo_webcam.py" and run it. print cap.isOpened() # True = read video successfully. The OpenCV 2.x library is a C++ API. The Circuit is pretty simple. Tracking and facial recognition with Arduino !<br><br>A project based on the Arduino Micro board, which will result in a device capable of tracking and recognizing faces.<br> <br>Entry<br> <br>The development and advancement of high-resolution cameras in recent years has encouraged engineers and students to research and build applications based on "automated" computer vision algorithms, a . I want this to work remotely so it doesn't have to stay plugged into a computer. /* adjust the servo within the squared region, #out= cv2.VideoWriter('face detection4.avi',fourcc,20.0,(640,480)), #plot the squared region in the center of the screen, read= str(ArduinoSerial.readline(ArduinoSerial.inWaiting())), Test the Effectiveness of Your DIY Face Mask, Smart fire detection using opencv and python. COLOUR DETECTION USING OPENCV AND PYTHON. In this project, I have used the OpenCV's Harr cascade classifiers for detecting human faces and pan/tilt servo mechanism to track the user's face using Arduino UNO. I am currently on a 64-bit machine. Face Tracking and Smile Detecting Halloween Robots, IoT WiFi | Bluetooth Face Tracking + Recognition. Anaconda is essentially a nicely packaged Python IDE that is shipped with tons of useful packages, such as NumPy, Pandas, IPython Notebook, etc. If you have gone through all the steps properly then you may have created your own trained data. create a folder named "image_data" in your main project folder. Basically i have an arduino with 2 servo motors and an HD webcam and i want to recognise this 2 parameters. if the data is matched then we say that the person is recognized it is just that simple Download "face_recognise.py" and run it. FFMPEG is ready to be used! Here is a video(gif) captured by the camera tracking my face. Face Recognition Door Lock Security System using Arduino and Python - GitHub - V-Uni/Face-Recognition-Security-System: Face Recognition Door Lock Security System using Arduino and Python When my face is recognized then the label ID provided is 2. We use the Easy VR and an Arduino. Arduino Face Tracking Mechanism for Biometric Verification (TfCD Prototype Project): When you want to implement a biometric facial recognition system for for example a biometric door lock, it may be necessary to use a linear face tracking mechanism. If you have not created one then do it. This uses the OpenCV open source computer vision library to do the face recognition and then sends position information to an Arduino over its serial port. I started by building a simple circuit on an Arduino, a small program that would repeatedly power a set of LEDs on and off; somehow it worked. Three interesting databases are (parts of the description are quoted from http://face-rec.org): HERE I m using my own dataset.with the help of code which is given below: Create the function to prepare the training set. on Step 4, i didnt understand step 4 that is training!! Yahiya Mulla 1.51K subscribers Subscribe 617 Share 26K views 2 years ago Facial recognition AKA face. The square in the center of the frame in white describes the region within which the center of the face i.e the green dot must be. See the image above that should be your output. (You can download the code I have provided the file below) : Once this is done, move on to write the code for Arduino After the python script is ready we need arduino sketch to control the servo. Face mask and body temperature detection is necessary for current pandemic period. Fire being one of the savage component. The Arduino controls the movement of the webcam with the help of two pan/tilt servos to follow the detected face. Image and object recognition on Esp32-cam can be implemented in 30 minutes, with minimal code configuration, thanks to the Eloquent Arduino ecosystem of libraries: once deployed, it takes 1 kb of RAM and runs at 60 FPS. and learn something new. If label ID is other than 2 then i will send '0' as the serial data, which will turn off my LED chaser Circuit. In-order to have a precise facial recognition, a plain background would be recommended as I faced some false detection due to the curtains in the background. Hello, I have an ESP32 camera module and use the sample project from ESP32 "CameraWebServer". Turn on Face Recognition from the left-side menu, and the ESP32 will begin detecting human faces. pip install opencv-python. With ESP32-CAM, we can try to develop a simple application that use your face as ID. Open the face recognition script (FaceRecoginitionv1.py) from the Raspberry Pi terminal and run it. #detect the face and make a rectangle around it. Download "haarcascade_frontalface_default" and place it in the main project folder. I have used the center coordinates of the face for reference and can be calculated using x+width/2 and y+height/2 and can be seen as a green dot. Raspberry Pi face recognition has become very popular recently. How it Works? I'm providing that file just download it and place it in your project folder. This returns the cartesian coordinates of the image along with the height and width. Spectrino - Arduino devices that can be implemented on a wide spectrum of touch-free tinyML based housing and society systems. I will explain all the steps below. The facial recognition is a very useful tool incorporated in many modern devices to detect human faces for tracking, biometric and to recognize human activities. I have provided all the necessary comments there. Test to confirm 5. Which will turn on my LED chaser circuit. However, when I enable face detection . To make face recognition work, we need to have a dataset of photos also composed of a single image per . Facial detection identifies and localizes human faces and ignores any background objects such as curtain, windows, trees, etc. Now our AI Robot is ready to work. OpenCV returns the face coordinates in terms of pixel values. When I enable face detection it recognizes my face (recognizes five points). BUT, we still need to do a little bit more work to get FFMPEG (video codec) to work (to enable us to do things like processing videos.). If OpenCV detects a face it will track it and calculate its center's X,Y coordinates. Now open 'face.py' with Python IDLE and press 'F5' to run the code. Once the folders are created then start collecting images of that specific person. ; English . Well done. To do this first download and Install python 2.7.14. After booting the Raspberry Pi, open the face recognition script that we have made and run that script. these commands will install the necessary modules. 7 face recognition Projects - Arduino Project Hub 7 face recognition projects Smart Door with Face Unlock Project tutorial by Divins Mathew 47,398 views 8 comments 45 respects DasCognitiveServices by Marius Dima 19,310 views 8 comments 76 respects Alexa Controlled Face Recognizing Arduino Door. In this tutorial, I will be showing you how to track faces using Arduino and Python and make the camera follow the face. Step 1: Connect Your Arduino to any USB Port of your PC Step 2: Click on "Check" to find your Arduino COM Port Step 3: Finally click on "Start" button to start reading serially. For ex: "X100Y200", the value 100 after X represents center x-coordinate and 200 represents center-y coordinate. Installing 'pyserial', 'OpenCV" and "numpy" in Python: To install these modules we will use use pip install, First open CMD and type the following codes:-. Detect human face details with the help of an Arduino. SamIAm93 March 5, 2017, 2:05pm #3. for which You need to add the path of your pip installation to your PATH system variable. My approach towards sending the serial data is similar to the one used in that project. The Arduino board serves as the two-way authenticator. A Python Shell should pop up. Summary of links to WebRTC-related articles Under construction WebRTC Server-Side Technical Checks twilio Real-time video infrastructure and SDKs Firefo. I found this part challenging as I tried many ways to send the coordinates sequentially to the arduino but the response was slow. If you want you can make one yourself using wood/Plastic or even 3D print one. By default, the video resolution is set to 640*480. Hello everyone, I was wondering if there were any codes or programs out there that used Arduino with a camera to identify human faces and face expressions. It uses an image capturing technique in the system. Download the "ard_chaser.ino" file. This is a simple example of running face detection and recognition with OpenCV from a camera. 1. Since India is under lockdown the cheapest solution which I found was to use my computers webcam to which I had access with a python program using openCV module. Opening a Door The Sketch above combined with a relay or Mosfet module can be used to switch an electrical device on or off. If you'd like to process video files, you'd need to ensure that Anaconda / Spyder IDE can use the FFMPEG (video codec). Then power the Arduino Mini connected with the OLED display via 5V pin of Raspberry Pi. if the accuracy is not good then try updating the data. Now open notepad and write the script given below, Save it as 'face.py' in the same folder as haarcascade. cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),5), print("Center of Rectangle is :", center), servoVer.attach(5); //Attach Vertical Servo to Pin 5, servoHor.attach(6); //Attach Horizontal Servo to Pin 6, The one I used is pretty cheap, and very easy to assemble. Thus, the value 6 seemed optimal. To do so follow the following steps: Open Arduino -> Sketch -> Include Library -> Add .ZIP Library -> Navigate to downloaded zip file -> add Source Code/Program for ESP32 CAM Module Here is a source code for Face Recognition Based Attendance System using ESP32 CAM & OpenCV. 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