The application discloses a
machine vision target positioning method and
system based on boundary frame self-adaptive adjustment, relates to the technical field of target detection and positioning, and comprises the following steps: acquiring real-time images and depth images of a current monitoring environment; inputting the real-time images into a light-weight target detection model based on an improved YOLO, identifying targets in the images and extracting target boundary frames; aligning the real-time images and the depth images, determining the depth value of each pixel point according to the coordinates of each pixel point in the target boundary frame region; based on the depth value of each pixel point in the target boundary frame region, using an adaptive width and
distance measurement algorithm to distinguish target regions and background regions in the target boundary frame region, extracting the overall depth value of the target regions, determining the target distance and the target position, re-identifying the boundaries around the targets in the target boundary frame region, determining the target width and height, and thus completing target positioning. The application can realize more accurate and reliable acquisition of target positioning information.