Obstacle identification method and device, electronic equipment and storage medium

Abstract

The invention discloses an obstacle recognition method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: obtaining an obstacle picture; inputting the obstacle picture into a pre-trained meta-learning model, and outputting a corresponding classification identifier; when the classification identifier is empty, obtaining a task corresponding to the obstacle picture based on the obstacle picture, and training a pre-trained meta-learning model by using the task to obtain an intermediate meta-learning model so as to identify an intermediate classification identifier corresponding to the obstacle picture; determining an identifier of the training task, determining a loss function value corresponding to the intermediate meta-learning model according to the intermediate classification identifier and the identifier of the training task when the intermediate classification identifier is inconsistent with the identifier of the training task, and adjusting model parameters of the intermediate meta-learning model according to the loss function value to obtain a target meta-learning model, to identify the target obstacle picture. Therefore, the vehicle end target element learning model can accurately identify more types of obstacles.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to an obstacle identification method and device, electronic equipment and storage media. Background technique [0002] The deep learning model is an important tool for realizing environmental perception in autonomous driving scenarios. Generally, collecting a large amount of training data is a prerequisite for using a deep learning model. Since there are many types of obstacles in the autonomous driving scene, and some types of obstacles are difficult to collect a large amount of data due to their low frequency of occurrence, resulting in the scarcity of training data for this type of obstacles, so that the training data obtained from the training can be applied to automatic The model on the driving side is not accurate enough to recognize obstacles. [0003] During the process of implementing this application, the inventors found that at least the following problems e...

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Problems solved by technology

[0005] In view of this, the embodiments of the present application provide an obstacle recognition method and device, electronic equipment, and storage media, which can solve the existing problem that due to the limited computing power of the automatic driving vehicle, it is usually impossible to use models with too large quantities, and due to The training data for certain types of obstacles is scarce, making the trained model applied to the self-driving car end to identify obstacles inaccurately.

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