类似:caffe*** Aborted at 1457897730 (unix time) try "date -d @1457897730" if you are using GNU date ***
1)考虑***_train.prototxt文件配置问题
net: "RDbyDL/Models/segnet_train.prototxt" test_iter: 1 test_interval: 100 base_lr: 0.001 lr_policy: "step" #error1:此处设置为step,后面没有设置stepsize; #error2:此处设置为step,实际使用的是fixed; gamma: 1.0 stepsize: 1000 # display: 5 momentum: 0.9 max_iter: 10000 weight_decay: 0.0005 snapshot: 100 snapshot_prefix: "RDbyDL/Models/Training/" solver_mode: CPU
2)考虑***_train.prototxt文件配置问题
name: "RDbyDL" layer { name: "data" type: "DenseImageData" top: "data" top: "label" dense_image_data_param { source: "RDbyDL/RDTD/train.txt" batch_size: 1 shuffle: false } } . . . layer { name: "upsample5" type: "Upsample" bottom: "pool5" top: "pool5_D" bottom: "pool5_mask" upsample_param { scale: 2 upsample_w: 30 #error1: upsample时,有可能宽/高度不能被scale整除,所以需要设置。一方面,可以保证最到 # 后得的结果与原图大小一致;另一方面,只有与对应pooling得到的mask(pool5_mask) # 大小一致,才可能实现对应的upsample。 upsample_h: 23 } } . . . layer { bottom: "conv1_2_D" top: "conv1_2_D" name: "relu1_2_D" type: "ReLU" } layer { bottom: "conv1_2_D" top: "conv1_1_D" name: "conv1_1_D" type: "Convolution" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0 } convolution_param { weight_filler { type: "msra" } bias_filler { type: "constant" } num_output: 12 #error2: 样本中的label类别要与此对应。 pad: 1 kernel_size: 3 } } layer { name: "loss" type: "SoftmaxWithLoss" bottom: "conv1_1_D" bottom: "label" top: "loss" softmax_param {engine: CAFFE} loss_param: { ignore_label: 12 #error3:不用于训练的label,可以在这设置忽略(比如unlabeled对应的标签) } } . . .