IoTKITs

This dataset contains annotated images of educational embedded boards, including popular models such as Arduino Uno, Arduino Nano, Arduino Mega, Raspberry Pi (various versions), ESP32, and similar microcontroller-based platforms. The images were collected from various sources such as Google Image Search, Kaggle datasets, Roboflow Universe, and original photographs captured by the authors. Each image is annotated using the Smart Polygon feature in Roboflow, which provides high-precision segmentation by labeling object boundaries with polygons instead of conventional bounding boxes. This allows for more accurate object detection, especially for boards with irregular shapes and connectors. The dataset is intended for use in object detection tasks, particularly in computer vision applications related to embedded systems, STEM education, and automated electronics recognition.本数据集包含教育用嵌入式开发板的标注图像，涵盖多款主流型号，例如Arduino Uno、Arduino Nano、Arduino Mega、树莓派（Raspberry Pi，多版本）、ESP32以及其他基于微控制器的同类平台。该数据集的图像来源多样，包括谷歌图片搜索（Google Image Search）、Kaggle数据集、Roboflow Universe，以及作者自行拍摄的原始照片。每张图像均通过Roboflow的智能多边形（Smart Polygon）功能进行标注：相较于传统的边界框标注方式，该功能通过多边形勾勒目标物体的轮廓，实现高精度的图像分割，此举可实现更精准的目标检测，尤其适配形状不规则、带有各类接口的开发板。本数据集旨在用于目标检测任务，尤其适用于嵌入式系统、STEM教育以及电子元器件自动识别相关的计算机视觉应用场景。