Training method of crowd counting network

The invention provides a training method of a crowd counting network, and the method provided by the invention effectively extracts multi-scale information through a plurality of groups of pyramid convolution kernels with different voidage rates, and solves the problem that the sizes of heads are not uniform. By adding batch normalization to each layer of output, the problem of difficulty in training caused by increase of the depth of the network is solved, meanwhile, the depth of the network is further improved through a residual structure under the condition that the parameter quantity is not increased, and high robustness is achieved. 本发明提供了一种人群计数网络的训练方法，本发明提供的方法通过多组空洞率不同的金字塔卷积核有效地提取了多尺度信息，解决了人头大小不统一的问题。通过在每一层输出都加上批量归一化，解决了网络深度增加造成难以训练的问题，同时通过残差结构在不增加参数量的情况下进一步提高了网络的深度，具有较高的鲁棒性。