Livestock temperature detection method, device and equipment and storage medium

Abstract

The invention discloses a livestock temperature detection method, which comprises the steps of obtaining an infrared photographing instruction, and collecting an infrared image of livestock by utilizing an infrared photographing device; processing the infrared image by using a super-resolution model to obtain a super-resolution image; detecting target livestock in the super-resolution image, and detecting coordinates of temperature detection key points of the target livestock; and detecting the temperature of the temperature detection key point, and giving an alarm when the temperature is higher than a preset threshold. According to the method, all-weather automatic fence patrolling can be achieved on the premise that precision is guaranteed, important guarantee is provided for livestock body temperature monitoring, the calculated amount can be reduced, hardware pressure can be reduced, cost can be saved, and livestock disease spreading can be prevented. The invention further discloses a livestock temperature detection device and equipment and a storage medium.

Description

technical field [0001] The invention belongs to the technical field of animal husbandry, and in particular relates to a livestock temperature detection method, device, equipment and storage medium. Background technique [0002] The livestock breeding industry is a labor-intensive industry. In the existing technology, when it is necessary to detect the temperature of livestock, one is the manual method, which is time-consuming and laborious, and depends on the personal quality of the operator, and is affected by various factors. It is also not easy to find all livestock with abnormal temperature. Another method is to rely on automatic technology to detect the temperature of livestock. It uses two target detection methods. One is to obtain the target outline through traditional opencv edge detection, but This method is difficult to adapt to the needs of target detection in complex scenes. The other method is deep learning, but it is mainly aimed at photos of pedestrians and ve...

AI Technical Summary

Problems solved by technology

[0002] The livestock breeding industry is a labor-intensive industry. In the existing technology, when it is necessary to detect the temperature of livestock, one method is manual, which is time-consuming and labor-intensive, and depends on the personal quality of the operator, and is affected by various factors. It is not easy to find all livestock with abnormal temperature. There is another method that relies on automatic technology to detect the temperature of livestock. It uses two target detection methods. One is to obtain the target outline through traditional opencv edge detection, but This method is difficult to adapt to the needs of target detection in complex scenes. The other method is deep learning, but it is mainly aimed at photos of pedestrians and vehicles, and its accuracy is low. It is not suitable for application in the field of livestock temperature detection.

Images