Pig B ultrasonic image fat content detection method based on deep regression network

The invention provides a pig B-mode ultrasound image fat content detection method based on a deep regression network, which comprises the following steps: S1, collecting a plurality of pig B-mode ultrasound images, and then zooming the width and height of the images to a uniform value to obtain a sample; s2, image enhancement: carrying out image enhancement based on contrast-limited adaptive histogram equalization; s3, increasing samples: expanding a data set by translating, rotating, mirroring, sharpening, and changing one or any combination of pixel values and brightness; s4, inputting the sample into the network model for training to obtain a trained network model; and S5, inputting the to-be-detected pig B ultrasonic image into the network for training to obtain a fat content result. The detection process can be simplified, the labor cost is reduced, the detection time is saved, the detection cost is reduced, the detection precision is improved, and the breeding effect is improved. The method is of great