Tagged images with LEGO bricks - Windows and Doors

The set contains images of LEGO bricks (from Windows and Doors category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface. The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks. The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. Sample images are presented below.

本数据集包含乐高门窗类（Windows and Doors）积木的图像。所有图像均专为训练用于乐高积木识别与标注的神经网络而制备。每张图像仅包含单块乐高积木。拍摄时，将积木放置于白色无反光表面上，由手持相机在其上方从不同角度进行拍摄。图像源自使用华为P20 Pro相机拍摄的原始照片，分辨率为2160×3840，文件格式为JPEG。积木采用两台朝向正下方的1600流明、4000K色温LED灯具进行照明。快门速度与ISO感光度分别设置为1/100秒与50，以匹配灯具的频闪频率。每张图像文件均已通过LegoSorter应用（https://github.com/legosorter）检测并裁剪至仅保留目标边界框（bounding box）。该边界框由经训练的YOLO神经网络生成，该网络仅用于检测乐高积木，无法区分具体型号。积木颜色为随机选取。数据集按照乐高官方零件编号进行组织，每块积木的图像均存储于以该零件编号命名的文件夹中。示例图像如下所示。