Abstract: A lane line recognition method, a lane line recognition device and a non-volatile storage medium. The method includes obtaining a first image which is a road image; dividing the first image from a middle of the first image to determine a first sub-image at a left part of the first image and a second sub-image at a right part of the first image; and performing respectively a recognition operation on the first sub-image and the second sub-image to determine a first lane line in the first sub-image and a second lane line in the second sub-image.

Abstract: The present disclosure relates to a method and an apparatus for recognizing an organism action, a server and a storage medium. The method includes: obtaining body feature information of an organism corresponding to time-successive multiple frames of images; creating a feature information sequence, wherein the feature information sequence includes body feature information respectively corresponding to multiple frames of images which are arranged according to a time sequence of the multiple frames of images; and inputting the feature information sequence into a trained recurrent neural network model, and determining an action of the organism corresponding to the feature information sequence according to an output of the recurrent neural network model.

Abstract: A lane line recognition method, a lane line recognition device and a non-volatile storage medium. The method includes obtaining a first image which is a road image; dividing the first image from a middle of the first image to determine a first sub-image at a left part of the first image and a second sub-image at a right part of the first image; and performing respectively a recognition operation on the first sub-image and the second sub-image to determine a first lane line in the first sub-image and a second lane line in the second sub-image.

Abstract: The present disclosure relates to a method and an apparatus for recognizing an organism action, a server and a storage medium. The method includes: obtaining body feature information of an organism corresponding to time-successive multiple frames of images; creating a feature information sequence, wherein the feature information sequence includes body feature information respectively corresponding to multiple frames of images which are arranged according to a time sequence of the multiple frames of images; and inputting the feature information sequence into a trained recurrent neural network model, and determining an action of the organism corresponding to the feature information sequence according to an output of the recurrent neural network model.

Abstract: The present disclosure provides a method and apparatus for early warning of vehicle offset. The method includes: acquiring collected road image to be detected; obtaining a corresponding grayscale image by performing grayscale processing on the road image to be detected; determining a target lane line within the grayscale image; and determining whether to issue an early warning of vehicle offset according to the target lane line and an early warning trigger condition.

Abstract: The present disclosure provides a method and apparatus for early warning of vehicle offset. The method includes: acquiring collected road image to be detected; obtaining a corresponding grayscale image by performing grayscale processing on the road image to be detected; determining a target lane line within the grayscale image; and determining whether to issue an early warning of vehicle offset according to the target lane line and an early warning trigger condition.