The invention relates to the technical field of neural networks, and provides a CNN model compression method and device based on a DS structure, and a storage medium, wherein the method comprises thesteps: S110, enabling DW convolution and SE Module to form DS convolution blocks through common convolution and batch standardization BN operation, wherein the DS convolution blocks comprise a convolution Conv-1, a batch standardization BN, an activation function, a DW convolution, a batch standardization BN, an activation function, an SE Module, a convolution Conv-2 and a batch standardization BN; S120, stacking the DS convolution blocks in order to form a neural network structure; and S130, adding an input layer, a pooling layer, a full connection layer and a classification layer to the neural network structure to form a neural network model. According to the method, the DS convolution block structure is applied to the neural network, and the number of parameters of the neural network isgreatly reduced while the picture feature extraction capability is ensured.