Description
看Owner是中国人就用中文了(小声BB...)
我直接用caffe.exe训练了 resnet101 (models/FRCNN/res101/solver.proto VOC2007)
我一开始训练了10000步发现推理结果为0 (使用test_frcnn.exe, 直接用训练集当做测试集)
于是我继续训练到20000发现推理结果还是为0
详细调试后发现score肥肠肥肠低都是0.00x,最高的我看到也就0.05...
我浏览了其他问题, 你说可以不用convert_model.py 于是我就直接训练完的模型直接test_frcnn也不行.输出结果如下
I0828 13:00:15.272047 19684 FRCNNtest.cpp:210] Handle 97 th image : 000193.jpg, with image_thresh : 0, 0 -> 0 boxes
I0828 13:00:15.367131 19684 FRCNNtest.cpp:210] Handle 98 th image : 000194.jpg, with image_thresh : 0, 0 -> 0 boxes
I0828 13:00:15.479229 19684 FRCNNtest.cpp:210] Handle 99 th image : 000198.jpg, with image_thresh : 0, 0 -> 0 boxes
I0828 13:00:15.584322 19684 FRCNNtest.cpp:210] Handle 100 th image : 000200.jpg, with image_thresh : 0, 0 -> 0 boxes
I0828 13:00:15.687412 19684 FRCNNtest.cpp:210] Handle 101 th image : 000203.jpg, with image_thresh : 0, 0 -> 0 boxes
I0828 13:00:15.791504 19684 FRCNNtest.cpp:210] Handle 102 th image : 000207.jpg, with image_thresh : 0, 0 -> 0 boxes
I0828 13:00:15.887589 19684 FRCNNtest.cpp:210] Handle 103 th image : 000208.jpg, with image_thresh : 0, 0 -> 0 boxes
我现在不知道怎么修改了...下面是训练时一部分....我认为正常
I0828 11:53:16.375608 19192 solver.cpp:218] Iteration 19920 (2.24295 iter/s, 8.91684s/20 iters), loss = 1.99799
I0828 11:53:16.375608 19192 solver.cpp:237] Train net output #0: bbox_accuracy = 0.75
I0828 11:53:16.376610 19192 solver.cpp:237] Train net output #1: loss_bbox = 0.430361 (* 1 = 0.430361 loss)
I0828 11:53:16.376610 19192 solver.cpp:237] Train net output #2: loss_cls = 1.27145 (* 1 = 1.27145 loss)
I0828 11:53:16.376610 19192 solver.cpp:237] Train net output #3: rpn_cls_loss = 0.898545 (* 1 = 0.898545 loss)
I0828 11:53:16.376610 19192 solver.cpp:237] Train net output #4: rpn_loss_bbox = 0.391415 (* 1 = 0.391415 loss)
I0828 11:53:16.376610 19192 sgd_solver.cpp:105] Iteration 19920, lr = 0.001
I0828 11:53:25.249524 19192 solver.cpp:218] Iteration 19940 (2.25401 iter/s, 8.87307s/20 iters), loss = 1.99201
I0828 11:53:25.249524 19192 solver.cpp:237] Train net output #0: bbox_accuracy = 0.75
I0828 11:53:25.250700 19192 solver.cpp:237] Train net output #1: loss_bbox = 0.644284 (* 1 = 0.644284 loss)
I0828 11:53:25.250700 19192 solver.cpp:237] Train net output #2: loss_cls = 0.905329 (* 1 = 0.905329 loss)
I0828 11:53:25.250700 19192 solver.cpp:237] Train net output #3: rpn_cls_loss = 0.0850422 (* 1 = 0.0850422 loss)
I0828 11:53:25.250700 19192 solver.cpp:237] Train net output #4: rpn_loss_bbox = 0.0457095 (* 1 = 0.0457095 loss)
I0828 11:53:25.251526 19192 sgd_solver.cpp:105] Iteration 19940, lr = 0.001
I0828 11:53:34.160838 19192 solver.cpp:218] Iteration 19960 (2.24479 iter/s, 8.90953s/20 iters), loss = 2.00955
I0828 11:53:34.160838 19192 solver.cpp:237] Train net output #0: bbox_accuracy = 0.75
I0828 11:53:34.161839 19192 solver.cpp:237] Train net output #1: loss_bbox = 0.721698 (* 1 = 0.721698 loss)
I0828 11:53:34.161839 19192 solver.cpp:237] Train net output #2: loss_cls = 1.35276 (* 1 = 1.35276 loss)
I0828 11:53:34.161839 19192 solver.cpp:237] Train net output #3: rpn_cls_loss = 0.107642 (* 1 = 0.107642 loss)
I0828 11:53:34.161839 19192 solver.cpp:237] Train net output #4: rpn_loss_bbox = 0.0488492 (* 1 = 0.0488492 loss)
I0828 11:53:34.161839 19192 sgd_solver.cpp:105] Iteration 19960, lr = 0.001
I0828 11:53:43.032603 19192 solver.cpp:218] Iteration 19980 (2.25453 iter/s, 8.87101s/20 iters), loss = 1.98453
I0828 11:53:43.032603 19192 solver.cpp:237] Train net output #0: bbox_accuracy = 0.96875
I0828 11:53:43.033603 19192 solver.cpp:237] Train net output #1: loss_bbox = 0.000514256 (* 1 = 0.000514256 loss)
I0828 11:53:43.033603 19192 solver.cpp:237] Train net output #2: loss_cls = 0.411482 (* 1 = 0.411482 loss)
I0828 11:53:43.033603 19192 solver.cpp:237] Train net output #3: rpn_cls_loss = 0.192493 (* 1 = 0.192493 loss)
I0828 11:53:43.033603 19192 solver.cpp:237] Train net output #4: rpn_loss_bbox = 0.0110174 (* 1 = 0.0110174 loss)
I0828 11:53:43.033603 19192 sgd_solver.cpp:105] Iteration 19980, lr = 0.001
请问如何修改使其能跑锕....救救我...