Distance Measurement in Industrial Scenarios

3D reconstruction technology is one of the important technologies of computer vision. Compared with 2D data, 3D space contains more abundant information, including location information, local / global features and so on. It is of great significance to solve the problem of target distance measurement in a single image scene. It is difficult for neural network to predict hole size without image scale information. In this paper, we focus on the measurement of objects with little change in height in the image. We use the relationship between camera parameters and regional features and the internal relationship between regional features to solve the problems of three-dimensional parameter reconstruction and monocular image distance measurement and use the standard cross entropy loss to optimize the transformer model. This model has achieved good results on the sampled data set.