Covid Face-Mask Monitoring Dataset

During the present time, COVID-19 situation is the topmost priority in our life. We are introducing a new dataset named Covid Face-Mask Monitoring Dataset which is based on Bangladesh perspective. We have a main concern to detect people who are using masks or not in the street. Furthermore, few people are not wearing masks properly which is harmful for other people and we have the intention to detect them also. Our proposed dataset contains 6,550 images and those images collected from the walking street, bus stop, street tea stall, foot-over bridge and so on. Among the full dataset, we selected 5,750 images for training purposes and 800 images for validation purposes. Our selected dimension is 1080 × 720 pixels for entire dataset. The percentage of validation data from the full dataset is almost 12.20%. We used a personal cell phone camera, DSLR for collecting frames and adding them into our final dataset. We have also planned to collect images from the mentioned place using an action camera or CCTV surveillance camera. But, from Bangladesh perspective it is not easy to collect clear and relevant data for research. To extend, CCTV surveillance cameras are mostly used in the university, shopping complex, hospital, school, college where using a mask is mandatory. But our goal of research is different. In addition, we want to mention that in our proposed dataset there are three classes which are 1. Mask, 2. No_mask, 3. Mask_not_in_position.

在当前时期，COVID-19疫情已成为我们生活中的首要关切。本团队推出了一项名为‘COVID-19面部口罩监测数据集’的新数据集，该数据集基于孟加拉国的视角。我们的主要目标是检测在街头上是否有人佩戴口罩。此外，我们注意到部分人群未能正确佩戴口罩，这对他人构成了危害，因此我们也致力于检测此类情况。本数据集共包含6,550张图片，这些图片采集自街头、公交车站、街头茶摊、人行天桥等地。在全部数据集中，我们选取了5,750张图片用于训练，800张图片用于验证。所选图像分辨率为1080 × 720像素，整个数据集均采用此分辨率。从完整数据集中，验证数据的比例约为12.20%。在数据采集过程中，我们使用了个人手机摄像头和单反相机来捕捉画面并添加至最终数据集。同时，我们计划使用动作相机或闭路电视监控摄像头从上述地点采集图像。然而，从孟加拉国的视角来看，要收集清晰且与研究相关的数据并非易事。进一步而言，闭路电视监控摄像头在大学、购物中心、医院、学校、学院等强制要求佩戴口罩的场所中普遍使用。但我们的研究目标与众不同。此外，我们还需指出，在我们提出的数据集中，共分为三类：1. 佩戴口罩，2. 未佩戴口罩，3. 佩戴口罩但位置不当。