{"id":79463,"date":"2020-07-20T14:27:39","date_gmt":"2020-07-20T08:57:39","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=79463"},"modified":"2025-07-29T19:25:36","modified_gmt":"2025-07-29T13:55:36","slug":"face-mask-detection-with-python","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/","title":{"rendered":"Real-Time Face Mask Detector with Python, OpenCV, Keras"},"content":{"rendered":"

During pandemic COVID-19, WHO has made wearing masks compulsory to protect against this deadly virus. In this tutorial we will develop a machine learning project – Real-time Face Mask Detector with Python.<\/p>\n

\"face<\/a><\/p>\n

Real-Time Face Mask Detector with Python<\/h3>\n

We will build a real-time system to detect whether the person on the webcam is wearing a mask or not. We will train the face mask detector model using Keras and OpenCV.<\/p>\n

Download the Dataset<\/h3>\n

The dataset we are working on consists of 1376 images with 690 images containing images of people wearing masks and 686 images with people without masks.<\/p>\n

Download the dataset: Face Mask Dataset<\/strong><\/a><\/p>\n

Download the Project Code<\/h3>\n

Before proceeding ahead, please download the project source code: Face Mask Detector Project<\/strong><\/a><\/p>\n

Install Jupyter Notebook<\/h3>\n

In this machine learning project for beginners, we will use Jupyter Notebook for the development. Let’s see steps for the installation and configuration of Jupyter Notebook.<\/p>\n

Using pip python package manager you can install Jupyter notebook:<\/p>\n

pip3 install notebook\r\n<\/pre>\n
And that\u2019s it, you have installed jupyter notebook<\/p>\n
After installing Jupyter notebook you can run the notebook server. To run the notebook, open terminal and type:<\/p>\n
jupyter notebook\r\n<\/pre>\n
It will start the notebook server at http:\/\/localhost:8888<\/p>\n
\"jupyter<\/a><\/p>\n
To create a new project click on the \u201cnew\u201d tab on the right panel, it will generate a new .ipynb file.<\/p>\n
Create a new file and write the code which you have downloaded<\/p>\n
Let’s dive into the code for face mask detector project:<\/h3>\n
We are going to build this project in two parts. In the first part, we will write a python script using Keras to train face mask detector model. In the second part, we test the results in a real-time webcam using OpenCV.<\/p>\n
Make a python file train.py to write the code for training the neural network on our dataset. Follow the steps:<\/p>\n
1. Imports:<\/p>\n
Import all the libraries and modules required.<\/p>\n
from keras.optimizers import RMSprop\r\nfrom keras.preprocessing.image import ImageDataGenerator\r\nimport cv2\r\nfrom keras.models import Sequential\r\nfrom keras.layers import Conv2D, Input, ZeroPadding2D, BatchNormalization, Activation, MaxPooling2D, Flatten, Dense,Dropout\r\nfrom keras.models import Model, load_model\r\nfrom keras.callbacks import TensorBoard, ModelCheckpoint\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.metrics import f1_score\r\nfrom sklearn.utils import shuffle\r\nimport imutils\r\nimport numpy as np\r\n<\/pre>\n
2.\u00a0Build the neural network:<\/p>\n
This convolution network consists of two pairs of Conv and MaxPool layers to extract features from the dataset. Which is then followed by a Flatten and Dropout layer to convert the data in 1D and ensure overfitting.<\/p>\n
And then two Dense layers for classification.<\/p>\n
model = Sequential([\r\n    Conv2D(100, (3,3), activation='relu', input_shape=(150, 150, 3)),\r\n    MaxPooling2D(2,2),\r\n    \r\n    Conv2D(100, (3,3), activation='relu'),\r\n    MaxPooling2D(2,2),\r\n    \r\n    Flatten(),\r\n    Dropout(0.5),\r\n    Dense(50, activation='relu'),\r\n    Dense(2, activation='softmax')\r\n])\r\nmodel.compile(optimizer='adam', loss='binary_crossentropy', metrics=['acc'])\r\n<\/pre>\n
3. Image Data Generation\/Augmentation:<\/p>\n
TRAINING_DIR = \".\/train\"\r\ntrain_datagen = ImageDataGenerator(rescale=1.0\/255,\r\n                                   rotation_range=40,\r\n                                   width_shift_range=0.2,\r\n                                   height_shift_range=0.2,\r\n                                   shear_range=0.2,\r\n                                   zoom_range=0.2,\r\n                                   horizontal_flip=True,\r\n                                   fill_mode='nearest')\r\n\r\ntrain_generator = train_datagen.flow_from_directory(TRAINING_DIR, \r\n                                                    batch_size=10, \r\n                                                    target_size=(150, 150))\r\nVALIDATION_DIR = \".\/test\"\r\nvalidation_datagen = ImageDataGenerator(rescale=1.0\/255)\r\n\r\nvalidation_generator = validation_datagen.flow_from_directory(VALIDATION_DIR, \r\n                                                         batch_size=10, \r\n                                                         target_size=(150, 150))\r\n<\/pre>\n
4. Initialize a callback checkpoint to keep saving best model after each epoch while training:<\/p>\n
checkpoint = ModelCheckpoint('model2-{epoch:03d}.model',monitor='val_loss',verbose=0,save_best_only=True,mode='auto')\r\n<\/pre>\n
5. Train the model:<\/p>\n
history = model.fit_generator(train_generator,\r\n                              epochs=10,\r\n                              validation_data=validation_generator,\r\n                              callbacks=[checkpoint])\r\n<\/pre>\n
\"project<\/a><\/p>\n
 <\/p>\n
Now we will test the results of face mask detector model using OpenCV.<\/p>\n
Make a python file \u201ctest.py\u201d and paste the below script.<\/p>\n
import cv2\r\nimport numpy as np\r\nfrom keras.models import load_model\r\nmodel=load_model(\".\/model-010.h5\")\r\n\r\nresults={0:'without mask',1:'mask'}\r\nGR_dict={0:(0,0,255),1:(0,255,0)}\r\n\r\nrect_size = 4\r\ncap = cv2.VideoCapture(0) \r\n\r\n\r\nhaarcascade = cv2.CascadeClassifier('\/home\/user_name\/.local\/lib\/python3.6\/site-packages\/cv2\/data\/haarcascade_frontalface_default.xml')\r\n\r\nwhile True:\r\n    (rval, im) = cap.read()\r\n    im=cv2.flip(im,1,1) \r\n\r\n    \r\n    rerect_size = cv2.resize(im, (im.shape[1] \/\/ rect_size, im.shape[0] \/\/ rect_size))\r\n    faces = haarcascade.detectMultiScale(rerect_size)\r\n    for f in faces:\r\n        (x, y, w, h) = [v * rect_size for v in f] \r\n        \r\n        face_img = im[y:y+h, x:x+w]\r\n        rerect_sized=cv2.resize(face_img,(150,150))\r\n        normalized=rerect_sized\/255.0\r\n        reshaped=np.reshape(normalized,(1,150,150,3))\r\n        reshaped = np.vstack([reshaped])\r\n        result=model.predict(reshaped)\r\n\r\n        \r\n        label=np.argmax(result,axis=1)[0]\r\n      \r\n        cv2.rectangle(im,(x,y),(x+w,y+h),GR_dict[label],2)\r\n        cv2.rectangle(im,(x,y-40),(x+w,y),GR_dict[label],-1)\r\n        cv2.putText(im, results[label], (x, y-10),cv2.FONT_HERSHEY_SIMPLEX,0.8,(255,255,255),2)\r\n\r\n    cv2.imshow('LIVE',   im)\r\n    key = cv2.waitKey(10)\r\n    \r\n    if key == 27: \r\n        break\r\n\r\ncap.release()\r\n\r\ncv2.destroyAllWindows()\r\n<\/pre>\n
Run the project and observe the model performance.<\/p>\n
python3 test.py\r\n<\/pre>\n
\"face<\/a><\/p>\n
Summary<\/h3>\n
After the COVID-19 pandemic, wearing a face mask became important. This project uses machine learning to detect if a person is wearing a mask or not in real-time. Using OpenCV, Keras, and a webcam, we can alert people if they are without a mask. This project is great for public safety systems.<\/p>\n
In this project, we have developed a deep learning model for face mask detection using Python, Keras, and OpenCV. We developed the face mask detector model for detecting whether person is wearing a mask or not. We have trained the model using Keras with network architecture. Training the model is the first part of this project and testing using webcam using OpenCV is the second part.<\/p>\n
This is a nice project for beginners to implement their learnings and gain expertise.<\/p>\n","protected":false},"excerpt":{"rendered":"
During pandemic COVID-19, WHO has made wearing masks compulsory to protect against this deadly virus. In this tutorial we will develop a machine learning project – Real-time Face Mask Detector with Python. Real-Time Face...<\/p>\n","protected":false},"author":10,"featured_media":79503,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[22694,21686,22693,22695,21082],"class_list":["post-79463","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning","tag-covid-19-face-mask-detection","tag-deep-learning-project","tag-face-mask-detector","tag-machine-learning-project-for-beginners","tag-python-project"],"yoast_head":"\nReal-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair<\/title>\n<meta name=\"description\" content=\"Real-time Face Mask Detector with Python -\u00a0develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Real-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Real-time Face Mask Detector with Python -\u00a0develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2020-07-20T08:57:39+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-07-29T13:55:36+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2020\/07\/python-project-real-time-face-mask-detection.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Real-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair","description":"Real-time Face Mask Detector with Python -\u00a0develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/","og_locale":"en_US","og_type":"article","og_title":"Real-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair","og_description":"Real-time Face Mask Detector with Python -\u00a0develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.","og_url":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2020-07-20T08:57:39+00:00","article_modified_time":"2025-07-29T13:55:36+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2020\/07\/python-project-real-time-face-mask-detection.jpg","type":"image\/jpeg"}],"author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/a90b082e16aa38d207212d22b0581f33"},"headline":"Real-Time Face Mask Detector with Python, OpenCV, Keras","datePublished":"2020-07-20T08:57:39+00:00","dateModified":"2025-07-29T13:55:36+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/"},"wordCount":553,"commentCount":100,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"image":{"@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#primaryimage"},"thumbnailUrl":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2020\/07\/python-project-real-time-face-mask-detection.jpg","keywords":["covid-19 face mask detection","deep learning project","face mask detector","machine learning project for beginners","Python project"],"articleSection":["Machine Learning Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/","url":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/","name":"Real-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/#website"},"primaryImageOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#primaryimage"},"image":{"@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#primaryimage"},"thumbnailUrl":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2020\/07\/python-project-real-time-face-mask-detection.jpg","datePublished":"2020-07-20T08:57:39+00:00","dateModified":"2025-07-29T13:55:36+00:00","description":"Real-time Face Mask Detector with Python -\u00a0develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.","breadcrumb":{"@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#primaryimage","url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2020\/07\/python-project-real-time-face-mask-detection.jpg","contentUrl":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2020\/07\/python-project-real-time-face-mask-detection.jpg","width":1200,"height":628,"caption":"python project real time face mask detection"},{"@type":"BreadcrumbList","@id":"https:\/\/data-flair.training\/blogs\/face-mask-detection-with-python\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Blog Home","item":"https:\/\/data-flair.training\/blogs\/"},{"@type":"ListItem","position":2,"name":"Machine Learning Tutorials","item":"https:\/\/data-flair.training\/blogs\/category\/machine-learning\/"},{"@type":"ListItem","position":3,"name":"Real-Time Face Mask Detector with Python, OpenCV, Keras"}]},{"@type":"WebSite","@id":"https:\/\/data-flair.training\/blogs\/#website","url":"https:\/\/data-flair.training\/blogs\/","name":"DataFlair","description":"Learn Today. Lead Tomorrow.","publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/data-flair.training\/blogs\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/data-flair.training\/blogs\/#organization","name":"DataFlair","url":"https:\/\/data-flair.training\/blogs\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/logo\/image\/","url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/07\/Data-Flair.png","contentUrl":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/07\/Data-Flair.png","width":106,"height":48,"caption":"DataFlair"},"image":{"@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/DataFlairWS\/","https:\/\/x.com\/DataFlairWS","https:\/\/www.linkedin.com\/company\/dataflair-web-services-pvt-ltd\/","https:\/\/www.youtube.com\/user\/DataFlairWS"]},{"@type":"Person","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/a90b082e16aa38d207212d22b0581f33","name":"DataFlair Team","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/dd6de0d647a0185cd6faf264e4ba860b0d85d08d7070766f9cd41bea5bb0b227?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/dd6de0d647a0185cd6faf264e4ba860b0d85d08d7070766f9cd41bea5bb0b227?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/dd6de0d647a0185cd6faf264e4ba860b0d85d08d7070766f9cd41bea5bb0b227?s=96&d=mm&r=g","caption":"DataFlair Team"},"description":"The DataFlair Team is passionate about delivering top-notch tutorials and resources on programming, Java, Python, C++, DSA, AI, ML, data Science, Android, Flutter, MERN, Web Development, and technology. With expertise in the tech industry, we simplify complex topics to help learners excel. Stay updated with our latest insights.","url":"https:\/\/data-flair.training\/blogs\/author\/dfadteam1\/"}]}},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/79463","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/comments?post=79463"}],"version-history":[{"count":11,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/79463\/revisions"}],"predecessor-version":[{"id":146345,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/79463\/revisions\/146345"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/media\/79503"}],"wp:attachment":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/media?parent=79463"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/categories?post=79463"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/tags?post=79463"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}