Flood routing process flooding range measurement method based on deep learning

The invention discloses a flood routing process flooding range measurement method based on deep learning. The method comprises the steps that firstly, a camera is arranged to be used for collecting video data of a whole test river channel; calibrating the camera through a camera checkerboard calibration method to correct the perspective distortion effect; extracting image data at different time points from the video data; constructing a flood test flooding range sample library; carrying out primary labeling on the sample through a Label labeling tool; and finally, adopting an MASK R-CNN imageinstance segmentation algorithm to realize automatic segmentation and recognition of a flooding range, and obtaining the submerging range change of the whole test riverway by splicing the recognitionpictures. The method has the advantages of being low in economic cost, high in intelligent degree, high in efficiency, high in precision, high in applicability and the like, and therefore the method can be used for extracting