Rebar counting detection using object detection based on deep learning

A high-precision DJI Phantom 4 Pro drone was commissioned at five unique construction sites in South Korea during peak productivity hours. Construction supervisors manually controlled the drone, thus ensuring the capture of clearly visible images of the rebars. The drone's path was methodically guided in a vertical trajectory above each column, positioning it directly above the rebars at an estimated altitude of 1 to 2 meters. At each position, still images were captured with the columns nearly centred in each frame. To underscore the pragmatic viability of the proposed method, rebar images were sourced under authentic operational conditions, thus encapsulating the complexities and challenges that typify bustling construction sites. This dataset contained a diverse array of variations in factors such as illumination, scale, and perspective. Moreover, other construction equipment such as scaffolding, timber and moulding were also observed in the images. In total, 728 images of rebars with a resolution of 1,500 × 900 pixels were captured.