Closed Jai-wei closed 5 years ago
There is no output model after the training,The final result is as follows(train.py):
speed: 14.338s / iter iter: 3991 / 4000, total loss: 0.024490
rpn_loss_cls: 0.001267 rpn_loss_box: 0.000509 loss_cls: 0.011721 loss_box: 0.010993
speed: 14.338s / iter iter: 3992 / 4000, total loss: 0.048566
rpn_loss_cls: 0.001235 rpn_loss_box: 0.001046 loss_cls: 0.033571 loss_box: 0.012713
speed: 14.337s / iter iter: 3993 / 4000, total loss: 0.053452
rpn_loss_cls: 0.001681 rpn_loss_box: 0.001608 loss_cls: 0.035508 loss_box: 0.014654
speed: 14.336s / iter iter: 3994 / 4000, total loss: 0.070646
rpn_loss_cls: 0.000058 rpn_loss_box: 0.000423 loss_cls: 0.046126 loss_box: 0.024039
speed: 14.336s / iter iter: 3995 / 4000, total loss: 0.036924
rpn_loss_cls: 0.000836 rpn_loss_box: 0.001194 loss_cls: 0.018513 loss_box: 0.016380
speed: 14.335s / iter iter: 3996 / 4000, total loss: 0.085609
rpn_loss_cls: 0.001739 rpn_loss_box: 0.000387 loss_cls: 0.047054 loss_box: 0.036428
speed: 14.334s / iter iter: 3997 / 4000, total loss: 0.029429
rpn_loss_cls: 0.000159 rpn_loss_box: 0.000223 loss_cls: 0.020920 loss_box: 0.008128
speed: 14.333s / iter iter: 3998 / 4000, total loss: 0.053948
rpn_loss_cls: 0.002857 rpn_loss_box: 0.000448 loss_cls: 0.023264 loss_box: 0.027379
speed: 14.332s / iter iter: 3999 / 4000, total loss: 0.079444
rpn_loss_cls: 0.000330 rpn_loss_box: 0.000551 loss_cls: 0.047870 loss_box: 0.030693
speed: 14.332s / iter iter: 4000 / 4000, total loss: 0.123056
rpn_loss_cls: 0.002037 rpn_loss_box: 0.001161 loss_cls: 0.081516 loss_box: 0.038342
speed: 14.331s / iter iter: 4001 / 4000, total loss: 0.073527
rpn_loss_cls: 0.000512 rpn_loss_box: 0.001229 loss_cls: 0.038448 loss_box: 0.033339
speed: 14.330s / iter
(py35-cpu) E:\Faster-RCNN-TensorFlow-Python3-2c52d601cae09fba0d9e445cd95d5af95d80d6c9>
The output model is saved in default folder
default
There is no output model after the training,The final result is as follows(train.py):
speed: 14.338s / iter iter: 3991 / 4000, total loss: 0.024490
speed: 14.338s / iter iter: 3992 / 4000, total loss: 0.048566
speed: 14.337s / iter iter: 3993 / 4000, total loss: 0.053452
speed: 14.336s / iter iter: 3994 / 4000, total loss: 0.070646
speed: 14.336s / iter iter: 3995 / 4000, total loss: 0.036924
speed: 14.335s / iter iter: 3996 / 4000, total loss: 0.085609
speed: 14.334s / iter iter: 3997 / 4000, total loss: 0.029429
speed: 14.333s / iter iter: 3998 / 4000, total loss: 0.053948
speed: 14.332s / iter iter: 3999 / 4000, total loss: 0.079444
speed: 14.332s / iter iter: 4000 / 4000, total loss: 0.123056
speed: 14.331s / iter iter: 4001 / 4000, total loss: 0.073527
speed: 14.330s / iter
(py35-cpu) E:\Faster-RCNN-TensorFlow-Python3-2c52d601cae09fba0d9e445cd95d5af95d80d6c9>