实时人脸检测使用Streamlit,TensorFlow, Keras和Open-CV

R. N. S. V. Yalamarthi, Shareef Shaik, Dalwinder Singh, Manik Rakhra
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引用次数: 1

摘要

这篇论文是基于保护我们的健康免受冠状病毒COVID-19的侵害。实时检测口罩有助于预防冠状病毒,在机器学习和数据科学算法(如Streamlit、MoblieNetV2、OpenCV等)的帮助下检测口罩,在这种理想的方法中被广泛使用。本文研究的是基于实时视频流的掩码检测方法,其检测准确率达到99.78%。该方法提出了建立精确的模型,并将模型与图形界面相结合,以提高用户的体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Face Mask Detection Using Streamlit,TensorFlow, Keras and Open-CV
This paper is based on the protection of our health from coronavirus officially known as COVID-19. Real-time detection of a face mask can help to prevent of the coronavirus, detecting the mask with the help of machine learning and data science algorithms such as Streamlit, MoblieNetV2, OpenCV, etc., are widely used in this ideal methodology. This paper is about the method that provides an accuracy of 99.78% in detecting the mask with live video stream. The method proposes building accurate model and integrating the model with a graphical interface which can improve the experience of the user.
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