Surgical Waste Detection Dataset

<br> Please cite our paper titled 'A Computer Vision-based System for Surgical Waste Detection' <br> Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130366 <br> The dataset is built based on real-time images from our surroundings including roads, beaches, water, maintenance holes and so on. Several images of the dataset are synthetic. Moreover, most of them are natural. Some images are taken using the Samsung Galaxy A51 smartphone camera and the rest of the images are taken from internet mining. Images are chosen from close range and distance range to make the dataset a distance variant. The angle variation left, right, back and top angle images are taken. The dataset comprises diverse gesture conditions such as curling and kneeling. At the time of image collection, this study tries to take different types of colored masks and gloves. The color variation of the mask is white, sky blue, pink, black and others. Different types of masks are included surgical, N95, Cone-style, KN95 and so on. Surgical gloves also have blue, white, black and pink colors. Transparent gloves are included with more eagerness to make the system as robust and reliable underwater as well as an object floating on the water condition. According to the above criteria, 1153 images are collected from different internet sources and smartphones camera.请引用我们题为《基于计算机视觉（Computer Vision）的手术废弃物检测系统》的论文。数字对象标识符（DOI）：10.14569/IJACSA.2022.0130366。本数据集基于周边环境的实时采集图像构建，涵盖道路、海滩、水域、检修井等多种场景。数据集包含部分合成图像，且绝大多数为自然图像。部分图像通过三星Galaxy A51智能手机摄像头拍摄，其余图像通过互联网爬取获取。为实现距离多样性，图像选取覆盖近距与远距范围；同时采集了左、右、后、顶等多视角的图像。数据集包含多种姿态场景，如蜷缩、跪姿等。在图像采集阶段，本研究采用了不同类型的彩色口罩与手套：口罩颜色涵盖白色、天蓝色、粉色、黑色等，类型包括医用外科口罩、N95口罩、杯型口罩、KN95口罩等；医用手套则有蓝色、白色、黑色、粉色等配色，同时额外收录透明手套，以提升系统在水下及水上漂浮物体场景下的鲁棒性与可靠性。按照上述标准，本研究从不同互联网资源及智能手机摄像头中共采集得到1153张图像。