Abstract: A vision acquisition system equipped in an intelligent terminal of a smart logistics vehicle is disclosed. The vision acquisition system includes an image information acquisition unit, an angle information acquisition unit, a vehicle information acquisition unit, an image information analysis unit and a calculation unit. The image information acquisition unit includes a ground image acquisition module and a feature point identification module; the ground image acquisition module acquires a ground image in front of a vehicle through a camera; and the feature point identification module is used for identifying contour information of the image and mark a near point and a far point of the image. In implementation of the present invention, a road surface in front of the driving vehicle can be acquired.

Abstract: The present disclosure provides a dog nose print recognition method and system. The dog nose print recognition method includes: collecting a nose image of a dog, acquiring the nose image, and processing the nose image to obtain a plurality of regional images to be recognized; performing key point detection on the plurality of regional images to be recognized to obtain key points corresponding to the regional images to be recognized, and using the key points to perform alignment processing of the regional images to be recognized to obtain aligned regional images to be recognized; and performing dog nose print feature vector extraction and recognition on the aligned regional images to be recognized, and determining a dog identity recognition result through the dog nose print feature vector extraction and recognition. The system includes modules corresponding to the steps of the method.

Abstract: The present application relates to a pet safety management method and system, computer equipment and a storage medium. The method includes: acquiring a first video comprising a target pet and a target object, the target object being an active object except the target pet; analyzing the first video to determine a first state of the target pet and a second state of the target object; acquiring a surrounding environment video of the target pet if the target pet is determined to be in an initial dangerous state according to the first state and the second state; and analyzing the surrounding environment, determining that the target pet is in a dangerous state if the surrounding environment is an interference-free environment, and controlling an warning device carried by the target pet to send a warning message to timely prevent a pet from being stolen.