Face Detection And Recognition Using Opencv Python

The breakthrough in face detection happened with Viola & Jones. By integrating OpenCV with MATLAB, you can: Use and explore current research algorithms, whether they are implemented in MATLAB or OpenCV; Use OpenCV algorithms with the convenience of the data access, image acquisition, and visualization capabilities in MATLAB. os - This module will be used to maneuver with image and directory names. FaceNet: A Unified Embedding for Face Recognition and Clustering. This article intends to show the reader how to use EmguCV 3. You may already know that OpenCV ships out-of-the-box with pre-trained. First of all we need to make a clear distinction between face detection and face recognition. In Haar features, all human faces share some common properties. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts … - Selection from Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python [Book]. The focus of this paper is to implement face recognition with OpenCV using Python as the main language, and Haar cascade as the classifier. Originally developed by Intel, it was later supported by Willow Garage then Itseez. This is a module which gets shipped along with standard release of OpenCV. Please enter a comment. It is a machine 27. Recently i tested a ROS stack for face_recognition. OpenCV is an open-source toolkit for advanced computer vision. The 3 Phases. OpenCV has several built-in pretrained classifiers for face, eyes, and smile detection, among others. Here we will deal with detection. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. In this OpenCV with Python tutorial, we're going to discuss object detection with Haar Cascades. Moreover, this library could be used with other Python libraries to perform realtime face recognition. What is EmguCV?. However, it is acceptable to use facial recognition for monitoring. Download it once and read it on your Kindle device, PC, phones or tablets. We will use the Haar feature-based cascade classifiers for facial detection. This is a simple example of how to detect face in Python. Using a model for predicting facial landmarks. Face recognition of living people. Please enter a comment. Covers advanced machine learning and deep learning methods for image processing and classification Explains concepts using real-time use cases such as facial recognition, object detection, self-driving cars, and pattern recognition Includes applications of machine learning and neural networks on. Delphi Face Recognition March_01_2019 Donate _$54_ for FULL source code of the project. Session 30: Face Recognition using Machine Learning-----. We used 200 images kindly provided by Rosario Rascuna , collected from Instagram and annotated by us. The Library provides more than 2500 algorithms that include machine learning tools for classification and clustering, image processing and vision algorithm, basic algorithms and drawing. This article intends to show the reader how to use EmguCV 3. As a matter of fact we can do that on a streaming data continuously. Haar-cascade Detection in OpenCV. OpenCV, the most popular library for computer vision, provides bindings for Python. Line detection and timestamps, video, Python. By integrating OpenCV with MATLAB, you can: Use and explore current research algorithms, whether they are implemented in MATLAB or OpenCV; Use OpenCV algorithms with the convenience of the data access, image acquisition, and visualization capabilities in MATLAB. (or pip2 for Python 2): pip3 install face_recognition. 7 Next, we're going to touch on using OpenCV with the Raspberry Pi's camera, giving our robot the gift of sight. x in a way different from the example I…. Although recently made famous by the iPhone X’s Face ID, face recognition is not a new thing. Create an optical character recognition (OCR) model using deep learning and convolutional neural networks. We consider here Python's OpenCv for accomplishing this task. The painting loop occasionally might be too slow, so we’ll save the image to the class and call the update method at the end of the slot. This tutorial is a follow-up to Face Recognition in Python, so make sure you've gone through that first post. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms. 28 Jul 2018 Arun Ponnusamy. In Face Detection only the Face of a person is detected the software will have no Idea who that Person is. This tutorial will introduce you to the concept of object detection in Python using the OpenCV library and how you can utilize it to perform tasks like Facial detection. Coding Face Recognition with OpenCV. Automatic Memes in Python with Face Detection. I recommend you to save that Pdf and read it when you have a chance if you plan to stay in this face detection/recognition plus machine learning rock star! In this paper, they have introduced the concept of Cascade of Classifiers. Their demo that showed faces being detected in real time on a webcam feed was the most stunning demonstration of computer vision and its potential at the time. In this discussion we will learn about Face Recognition using. There are tons of interesting problems to solve! One. To create a complete project on Face Recognition, we must work on 3 very distinct phases: Face Detection and Data Gathering ; Train the Recognizer ; Face Recognition. Face Recognition is a well researched problem and is widely used in both industry and in academia. Example of Python with Opencv and camera face detection - python_opencv_camera_haar. perspectiveTransform() with Python. ) Fingerprint identification, how is it done?. EigenFaces Face Recognizer Recognizer - cv2. FRT toolbox; Deep face recognition with face specific data augmentation Authors: Iacopo Masi, Anh Tuan Tran, Tal Hassner, Jatuporn Toy Leksut, Gerard Medioni. Python OpenCV library will use to teach multiple face recognition software development. To create a complete project on Face Recognition, we must work on 3 very distinct phases: Face Detection and Data Gathering; Train the Recognizer; Face Recognition. In addition, OpenCV offers support to many programming languages such C++, Java, and of course, Python. As input video we will use a Google Hangouts video. Before we start, it is important to understand that Face Detection and Face Recognition are two different things. Face recognition library will give you access to use the face detection model. 2 Today's outline The OpenCV Library Brief introduction Getting started Creating a face detector How it's done OpenCV implementation Using a. This method is more reliable than the conventional route. First of all you have to install the prerequisite software as described in this post. NOTE: I MADE THIS PROJECT FOR SENSOR CONTEST AND I USED CAMERA AS A SENSOR TO TRACK AND RECOGNITION FACES. Learning OpenCV is a good asset to the developer to improve aspects of coding and also helps in building a software development. In this tutorial you will learn how to apply face detection with Python. "Facenet: A unified embedding for face recognition and clustering. The Face Recognition module is not native to the official source yet so the additional libraries are built using a new method I came up with as documented here. Today we'll write an automatic meme generator, using any static image with faces as our input. All that we need is just select the boxes with a strong confidence. Face detection is performed by using classifiers. Robust Real-Time Face Detection. This algorithm helps to detect face using convolutional neural network. Lane detection and object detection with OpenCV & TensorFlow. In this post, we will get a 30,000 feet view of how face recognition works. For the face detection, the cascaded detector of Viola & Jones is employed [Viola2004] via the python interface of OpenCV [OpenCV] implementation. It uses Arduino as the controller and need to communicate with a computer that runs the face detection program to track the target. dstack function? Getting single frames from video with python. To install OpenCV with terminal use. It can detect more haar files now. openCV is a cross platform open source library written in C++,developed by Intel. The data will be in real time to detect what objects are where. OpenCV is an open source C++ library for image processing and computer vision, originally developed by Intel and now supported by Willow Garage. OpenCV, the most popular library for computer vision, provides bindings for Python. 0 for making our face recognition app. It also explains how to create a face recognition. For this program, we will need a webcam-enabled system with Python 3. Face Detection, Face Recognition. I need a freelance developer who can develop facial recognition with liveness detection with OpenCV in C#. space is an OCR engine that offers free…. Before we start, it is important to understand that Face Detection and Face Recognition are two different things. Study from MIT notes and get Interview questions. For this tutorial, I am using Windows 10 machine with installed python 3. To create a complete project on Face Recognition, we must work on 3 very distinct phases: Face Detection and Data Gathering; Train the Recognizer; Face Recognition. Use Python and OpenCV to draw shapes on images and videos. 4 now comes with the very new FaceRecognizer class for face recognition, so you can start experimenting with face recognition right away. In face recognition, a computer can easily detect who is a person in front of the camera. So, it's perfect for real-time face recognition using a camera. Face Recognition is a computer vision technique which enables a computer to predict the identity of a person from an image. py  and it will start detecting faces from the webcam. I’ll focus on face detection using OpenCV, and in the next, I’ll dive into face recognition. What You Will LearnDiscover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects. OpenCV has been a vital part in the development of software for a long time. Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. In this tutorial we're going to look at how to use OpenCV, a real time computer vision library, with Processing, Arduino, a webcam and a pan/tilt bracket to create a video that will keep a persons face in the middle of the frame as they walk around the room. You may already know that OpenCV ships out-of-the-box with pre-trained. Line detection and timestamps, video, Python. In addition to performing Hand Gesture Recognition, there are many more things that you can do with the OpenCV such as Object Detection, Face Recognition, Template Matching, SLAM Detection, create your own self-driving car, making Augmented Reality Applications and much more!. It has numerous pre-written functions for image processing tasks. Recently, I wanted to perform Face Recognition using OpenCV in Python but sadly, I could not find any good resource for the same. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Introduction. To confirm that your OpenCV is installed, when you activate Python‘s interactive environment try to import it using: import cv2 If do not get an error, then you can proceed. The Library provides more than 2500 algorithms that include machine learning tools for classification and clustering, image processing and vision algorithm, basic algorithms and drawing functions, GUI and I/O functions for images and videos. We used 200 images kindly provided by Rosario Rascuna , collected from Instagram and annotated by us. If you want to train your own classifier for any object like car, planes etc. py" and insert following code:. OpenCV is an open source C++ library for image processing and computer vision, originally developed by Intel and now supported by Willow Garage. First we have to create a dataset for the faces which needs to get identified. face detection model to use: either. Practical Machine Learning and Image Processing For Facial Recognition, Object Detection, and Pattern Recognition Using Python. Face Detection. x versions of the library. Slide2 Content. “Facenet: A unified embedding for face recognition and clustering. Same feature you can also find in Google Photoes where you can categories you image using face. Let's improve on the emotion recognition from a previous article about FisherFace Classifiers. py example help. Torch allows the network to be executed on a CPU or with CUDA on GPU. [1] Despite the fact that other methods of identification can be more accurate, face recognition has always remained a major focus of. OpenCV uses machine learning algorithms to search for faces within a picture. The Face Recognition process in this tutorial is divided into three steps. When OpenCV is correctly configured by means of the procedure described above, it reads and processes all frames from the video stream. openCV is used for Face Recognising System, motion sensor, mobile robotics etc. OpenCV comes with a trainer as well as a detector. A video of the final product illustrates the concept a little better than I can explain it. It can be used for: object detection, motion detection, augmented reality, facial recognition or gesture recognition. OpenCV, the most popular library for computer vision, provides bindings for Python. Object Detection using Haar feature-based cascade classifiers is an effective object detection method. Covers advanced machine learning and deep learning methods for image processing and classification Explains concepts using real-time use cases such as facial recognition, object detection, self-driving cars, and pattern recognition Includes applications of machine learning and neural networks on. A technique used by OpenCV 4 for face detection is based on the so-called Haar Cascades. Lane detection and steering module with OpenCV & Arduino. you can use OpenCV to create one. 3 and PyCharm IDE. Before we start, it is important to understand that Face Detection and Face Recognition are two different things. The most popular and probably the simplest way to detect faces using Python is by using the OpenCV package. Prepare training data: In this step we will read training images for each person/subject along with their labels, detect faces from each image and assign each detected face an integer label of the person it belongs to. py, and create test data to detect and recognize my faces. So, it’s perfect for real-time face recognition using a camera. createEigenFaceRecognizer(). Introduction to Scikit Learn | Edureka. Face Recognition Python is the latest trend in Machine Learning techniques. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. Face recognition on the other hand is the process of distinguishing faces to identify a particular person. This library can be used in python , java , perl , ruby , C# etc. sudo apt-get install python-opencv. As an example, a criminal in China was caught because a Face Recognition system in a mall detected his face and raised an alarm. We need to extend our Face Detection as well. Moreover, this library could be used with other Python libraries to perform realtime face recognition. Computer vision deep learning Keras. A video of the final product illustrates the concept a little better than I can explain it. Please try again. Here is a demo to get you excited and set the stage for what will follow:. We need to extend our Face Detection as well. This tutorial is a follow-up to Face Recognition in Python, so make sure you've gone through that first post. Now, how do I do the comparison thing? What I understand is this: In general Machine learning approach, I need to gather lots of data about that particular person and finalize it using a CNN. At the end, face detection algorithm will use the trained datasets to identify faces. This library is supported in most of the operating system i. Face detection in android media apps Adding more value to applications Hackathon, Mobile Day Endava 24. The most famous and commonly used API for face recognisation and other image processing and computer vision stuff are done in OpenCV library You can easily download. "Face detection is a computer technology that determines the locations and sizes of human faces in arbitrary (digital) images. Feb 24, 2015 • Bikramjot Singh Hanzra Posted under python sklearn opencv digit recognition. By the end of this post, you will have a working face detector using OpenCV that can communicate with Azure’s Cognitive Services. Schroff, Florian, Dmitry Kalenichenko, and James Philbin. Face recognition with OpenCV: Haar Cascade Viola and Michael Jones in their paper "Rapid Object Detection using a Boosted Cascade of Simple Features" in 2001. So, after a few hours of work, I wrote my own face recognition program using OpenCV and Python. In this post we will see how to use the Haar Classifier implemented in OpenCV in order to detect faces and eyes in a single image. I’ll focus on face detection using OpenCV, and in the next, I’ll dive into face recognition. There are 3 steps involved in implementing the face detection/recognition. Unfortunately the current binary version of OpenCV available to install in the Raspbian operating system through apt-get (version 2. In this article by Joseph Howse, Quan Hua, Steven Puttemans, and Utkarsh Sinha, the authors of OpenCV Blueprints, we delve into the aspect of fingerprint detection using OpenCV. This article demonstrates real-time training, detection and recognition of a human face with OpenCV using the Eigenface algorithm. The Face Recognition module is not native to the official source yet so the additional libraries are built using a new method I came up with as documented here. Create Face Detection Software; Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python; Use Python and Deep Learning to build image classifiers; Use Python and OpenCV to draw shapes on images. Trainig the model. Originally developed by Intel, it was later supported by Willow Garage then Itseez. Many, many thanks to Davis King () for creating dlib and for providing the trained facial feature detection and face encoding models used in this library. Watch Now This tutorial has a related video course created by the Real Python team. Face detection can be regarded as a more general case of face localization. Slide1 Face feature detection using Java and OpenCV. Automatic Memes in Python with Face Detection. FRT toolbox; Deep face recognition with face specific data augmentation Authors: Iacopo Masi, Anh Tuan Tran, Tal Hassner, Jatuporn Toy Leksut, Gerard Medioni. We are using OpenCV 3. you can use OpenCV to create one. Python Tutorial for Computer Vision and Face Detection with OpenCV: Learn Vision Includes all OpenCV Image Processing Features with Simple Examples. To do this I decided on the "Hello World" of Deep Learning: Image Recognition. We'll do face and eye detection to start. This article demonstrates real-time training, detection and recognition of a human face with OpenCV using the Eigenface algorithm. Following its success with object recognition, CNNs have been widely used for face recognition. However, it is acceptable to use facial recognition for monitoring. In this OpenCV with Python tutorial, we're going to discuss object detection with Haar Cascades. The face-boxer. In this tutorial series, we are going to learn how can we write and implement our own program in python for face recognition using OpenCV. MATLAB provides integration with OpenCV through the OpenCV C++ API. Face recognition is a combination of two major operations: face detection followed by Face classification. Skills: Face Recognition, Python. The face recognition system is also being increasingly used in the mobiles for device security. conda install -c conda-forge opencv Program. Opencv Replace Color Python. Suppose you are searching for an object which has multiple occurances, cv2. In this article, I will show you how to build a capable face detection algorithm using open source tools. OpenCV is an open source software library that allows developers to access routines in API (Application Programming Interface) used for computer vision applications. py script is designed to be run from the command-line. To create a complete project on Face Recognition, we must work on 3 very distinct phases: Face Detection and Data Gathering ; Train the Recognizer ; Face Recognition. opencv face recognition /detection system using java in netbeans with source code. *Note: Put everything in a folder both the Python files, HaarCasCade XML file and face_data. In the case of video, the detected faces may need to be tracked using a face tracking component. Using a cascade of “weak-classifiers”, using simple Haar features, can – after excessive training – yield impressive results. The contents of this zip are: opencv_face_detector. Previously I’d used openCV to build a face tracking robot head in Python and we figured a review of what’s easily available might be fun: Balthazar ran the face detection process with face. Detecting facial landmarks with face_recognition The landmarks_detection_fr. A basic implementation is included in OpenCV. Tony Car land detection with OpenCV and Python view source. Unfortunately the current binary version of OpenCV available to install in the Raspbian operating system through apt-get (version 2. Download Open CV Package 3. Detection is carried out through training. Haar-cascade Detection in OpenCV. This document is the guide I've wished for, when I was working myself into face recognition. Face Detection, Face Recognition A guide to Face Detection in Python. INTRODUCTION. Typically, the accuracy of face recognition is highly dependent on the quality and variety of the sample images. In part 1 I will be doing simple face detection and moving onto the more complicated aspects in further. We are using OpenCV 3. MATLAB provides integration with OpenCV through the OpenCV C++ API. 推荐:Face detection using HTML5, javascript, webrtc, websockets, Jetty and OpenCV. ) Fingerprint identification, how is it done?. Now, we will use the following Haar Cascade Classifier for our face detection code. EigenFaces Face Recognizer Recognizer - cv2. Windows,Linux,Mac,openBSD. Python For Vision and Detection : OpenCv Python, Learn Vision Includes all OpenCV Image Processing Features with Simple Examples. There are tons of Google Hangouts videos around the web and in these videos the face is usually large enough for the software to detect the faces. Example of Python with Opencv and camera face detection - python_opencv_camera. OpenCV is an open source software library that allows developers to access routines in API (Application Programming Interface) used for computer vision applications. php(143) : runtime-created function(1) : eval()'d code(156) : runtime-created. Given a new image of a face, we need to report the person’s name. 4 now comes with the very new FaceRecognizer class for face recognition, so you can start experimenting with face recognition right away. So, it’s perfect for real-time face recognition using a camera. It uses OpenCV for many processing steps. openCV is used for Face Recognising System, motion sensor, mobile robotics etc. 7, but am having a hard time making the jump to emotion recognition. Source image: So, we begin to import our modules and the source image: import cv2 import numpy as np #import image image = cv2. It's quite easy to do, and we can sample the frames, because we probably don't want read every single frame of the video. openCV is used for Face Recognising System, motion sensor, mobile robotics etc. To start with, we would have to first install opencv on our machines, which can only be done if you have Python installed. So, it’s perfect for real-time face recognition using a camera. The objective of this post is to demonstrate how to detect and count faces in an image, using OpenCV and Python. Face detection. Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations. 6 or higher. Delphi Face Recognition March_01_2019 Donate _$54_ for FULL source code of the project. We'll do mouth detection to start. Previously, we've worked on facial expression recognition of a custom image. FaceRecognizer is much easier to use & understand than this old code. Recently i tested a ROS stack for face_recognition. As mentioned, one of the features of our robot is that it will do face recognition. I wrote a small Python program for face detection using OpenCV and Face detection API. Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs Udemy Course Free Download Go from beginner to Expert in using Deep Learning for Computer. It detects facial features and ignores anything else, such as buildings, trees and bodies. Key Features. Deep Learning Face Detection, Face Recognition & OCR OPENCV COMPLETE DUMMIES GUIDE TO COMPUTER VISION WITH PYTHON UDEMY COURSE FREE DOWNLOAD. Watch it together with the written tutorial to deepen your understanding: Traditional Face Detection With Python Computer vision is an exciting and growing field. Unfortunately the current binary version of OpenCV available to install in the Raspbian operating system through apt-get (version 2. Face recognition with OpenCV, Python, and deep learning Inside this tutorial, you will learn how to perform facial recognition using OpenCV, Python, and deep learning. face_locations(image). The pipeline for the concerned project is as follows: Face detection: Look at an image and find all the possible faces in it. Opencv Replace Color Python. A basic implementation is included in OpenCV. To carry out facial recognition, we would be writing three scripts. We will use the Haar feature-based cascade classifiers for facial detection. EigenFaces Face Recognizer Recognizer - cv2. Windows,Linux,Mac,openBSD. Example of Python with Opencv and camera face detection - python_opencv_camera. You can add more xml according to your requirement. Face detection can be performed using the classical feature-based cascade classifier using the OpenCV library. Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python. For developers learning and applying the OpenCV computer vision framework. Show us something cool! Tags:. These regularities may be matched using Haar features, as shown in Fig. This project depends on the OpenCV computer vision library to perform the face detection and recognition. cv2 bindings incompatible with numpy. The links below are helpful for understanding the Python bindings for OpenCV with regard to facial detection and image masks. Use features like bookmarks, note taking and highlighting while reading Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python. By integrating OpenCV with MATLAB, you can: Use and explore current research algorithms, whether they are implemented in MATLAB or OpenCV; Use OpenCV algorithms with the convenience of the data access, image acquisition, and visualization capabilities in MATLAB. In Face Detection only the Face of a person is detected the software will have no Idea who that Person is. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. optimization of Viola Jones Face Detection Framework using OpenCV on Devkit8500, which is a low power, open source single-board computer produced by Texas. Set Environmental. Coding Face Recognition with OpenCV. The face recognition system is also being increasingly used in the mobiles for device security. 0 installed on it. Hello everyone, this is going to be an in-depth tutorial on face recognition using OpenCV. I'd like to use it also for the cheap one you can use raspberry pi board and web camera with openCV in python code. Face recognition software can be developed more widely. ) 2D descriptors and detectors in 3D constellation using Kinect depth Bag of words to propose objects 3D to 3D fit to confirm recognition and Yield object pose in 6 degrees of freedom. We almost have all the elements to set up our “real”-face recognition algorithm. OpenCV + Face Detection. I would like to use OpenCV to implement a face recognition (not detection) program in python. Moreover, this library could be used with other Python libraries to perform realtime face recognition. Lane detection and object detection with OpenCV & TensorFlow. import numpy as np import cv2 as cv. face detection model to use: either. sudo apt-get install python-opencv. 4 now comes with the very new FaceRecognizer class for face recognition, so you can start experimenting with face recognition right away. OCR (Optical character recognition) is the process by which the computer recognizes the text from an image. All that we need is just select the boxes with a strong confidence. face recognition opencv python free download. Face detection in android media apps Adding more value to applications Hackathon, Mobile Day Endava 24. Automatic Memes in Python with Face Detection. Face Detection with OpenCV-Python. Donate and message or mail at [email protected] We can use openCV for facial detection. For the extremely popular tasks, these already exist. We'll start with a brief discussion of how deep learning-based facial recognition works, including the concept of "deep metric learning". In Face Detection only the Face of a person is detected the software will have no Idea who that Person is. Face detector is based on SSD framework (Single Shot MultiBox Detector), using a reduced ResNet-10 model. Python correctMatches. 10), and the two facial-detection articles for OpenCV are both good, and can be used to help understand the code in this. Lately, I’ve been looking for ways to detect faces in photos with PHP. Face and Eye Detection Group Person Example In this Python tutorial, we will write a Python program for face and eye detection using OpenCV. OpenCV comes with a library specially built for face recognition cv::FaceRecognizer. YOLO object detection using Opencv with Python; Simple shape detection - Opencv with Python 3; YOLO V3 - Install and run Yolo on Nvidia Jetson Nano (with GPU) Find and Draw Contours - OpenCV 3. Face detection is a process, which is to analysis the input image and to determine the number, location, size, position and the orientation of face. Face-Recognition Using OpenCV: A step-by-step guide to build a facial recognition system. The 3 Phases. hello i am using openCV c++ on vs2012 i am trying to do ASL to voice recognition please guide me how can i process , i am trying to understand every line of your code and do as you mentioned to enhace contour detection or background subtraction , but i really dont know how , please any help or ideas ? Thanks alot. Face Recognition Using OpenCv Face Recognition Using OpenCv project is a desktop application which is developed in C#. Python OpenCV library will use to teach multiple face recognition software development. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Previously I’d used openCV to build a face tracking robot head in Python and we figured a review of what’s easily available might be fun: Balthazar ran the face detection process with face. Senthilkumar, Institute of Road and Transport Technology. Using some relatively simple code in Python/ OpenCV we walk through a face-detection script that can be applied to your photo collection.