图2. 所提出的CGAN的结构. 根据判别网络输出的0/1矩阵计算对抗损失，误差反向传播给生成网络和判别网络，使用人工标注图像和生成网络生成结果计算L1损失，反向传播给生成网络，根据梯度下降原理不断调整网络参数

Fig. 2. The architecture of the proposed CGAN. The countermeasure loss is calculated according to the 0/1 matrix of the output of the discriminator network. The error is propagated back to the generator network and the discriminator network, and the L1 loss is calculated by using the artificially labeled image and the generating result of the generator network, transmitting back to the generator network, and the network parameters are continuously adjusted according to the gradient descent principle