Face Mask Detection Using Keras and Flask

The COVID-19 pandemic has quickly disrupted global trade and travel, affecting our day to day lives. It has been standard practice to use a face mask for protection. Many public service providers will require proper face mask wear soon for customers to use their services. Facemask Detection is now an essential responsibility to assist the worldwide civilization. This paper outlines a condensed method for achieving this goal can certain fundamental machine learning tools, including TensorFlow, Keras, OpenCV, and Scikit-Learn. The suggested method correctly extracts the face from the image before determining whether it has a mask on it. It can detect a face and a mask in motion as a surveillance task performance. On two separate datasets, be found to outperform any prior method or strategy utilized to determine sentence polarity. Thus, the approaches achieve accuracy of up to 95.77% and 94.58% respectively. We investigate enhanced values. The goal of this project is to make easier for the authorities to maintain the laws and regulation. This technique will identify the percentage mask that is being worn on a person’s face. In this manner, it may be determined whether it has been worn effectively to stop infections. If the mask is not worn the user will be highlighted and, after identification, we can issue a warning if is being used in public areas.