• Akshat chopra

Machine learning has been gaining momentum over last decades: self-driving cars, efficient web search, speech and image recognition. The successful results gradually propagate into our daily live. Machine learning is a class of artificial intelligence methods, which allows the computer to operate in a self- learning mode, without being explicitly programmed. It is a very interesting and complex topic, which could drive the future of technology. Face detection is an important step in face recognition and emotion recognition, which is one of the more representative and classic application in computer vision. Face is one of the physiological bio-metrics based on stable features. Face detection by computer systems has become a major field of interest. Face detection algorithms are used in wide range of applications, such as security control, video retrieving, biometric signal processing, human computer interface, emotion detection, face recognition and image database management. Face detection is a challenging mission because faces in the images are all uncontrolled. E.g. illumination condition, vary pose, different facial expressions

Our project has four directories in the root folder: Dataset/: Contains our face images organized into subfolders by name. Images/: Contains three test images that we’ll use to verify the operation of our model. Face-detection-model/: Contains a pre- trained Caffe deep learning model provided by OpenCV to detect faces. This model detects and localizes face in an image. Output/: Contains my output pickle files. If you’re working with your own dataset, you can store your output files here as well. The output files include: embedding.Pickle :A Serialized facial embeddings file. Embeddings have been computed for every face in the dataset and are stored in this file. le. pickle: Our label encoder. Contains the name labels for the people that our model can recognize. Recognizer. Pickle: Our Linear Support Vector Machine (SVM) model. This is a machine learning model rather than a deep learning model and it is responsible for actually recognizing faces.

"Facemask detection by open cv ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.d132-d136, July-2023, Available :http://www.jetir.org/papers/JETIR2307317.pdf

"Facemask detection by open cv ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppd132-d136, July-2023, Available at : http://www.jetir.org/papers/JETIR2307317.pdf