Automatic driving direction prediction method based on lightweight neural network

The invention specifically discloses an automatic driving direction prediction method based on a lightweight neural network. The method comprises the following steps: step 1, a neural network model is trained; and step 2, the neural network model is tested; in the neural network model training process, the obtained images are preprocessed, and data are subjected to horizontal overturning, brightness adjustment, angle adjustment and data screening operation, so that a data set is enriched, training samples are increased, and the network model is better trained. And the EffNet network and the BP neural network propagation algorithm are combined to adjust the error between the predicted steering wheel rotation angle and the actual steering wheel rotation angle, so that the network budget demand is reduced, and the method has actual reference value and a great market prospect. 本发明具体公开了一种基于轻量级神经网络的自动驾驶方向预测方法，包括以下步骤：步骤1：训练神经网络模型；步骤2：测试神经网络模型；在训练神经网络模型过程，对获取的图像进行预处理，经过对数据进行水平翻转，亮度调整，角度调整以及数据筛除操作，丰富了数据集，增加了训练样本，使得训练网