caffe-ssd使用预训练模型做目标检测

首先参考https://www.jianshu.com/p/4eaedaeafcb4

这是一个傻瓜似的目标检测样例，目前还不清楚图片怎么转换，怎么验证，后续继续跟进

• 模型测试
  （1）图片数据集上测试

python examples/ssd/score_ssd_pascal.py

输出为

I0505 10:32:27.929069 16272 caffe.cpp:155] Finetuning from models/VGGNet/VOC0712/SSD_300x300/VGG_VOC0712_SSD_300x300_iter_120000.caffemodel
I0505 10:32:28.052016 16272 net.cpp:761] Ignoring source layer mbox_loss
I0505 10:32:28.053956 16272 caffe.cpp:251] Starting Optimization
I0505 10:32:28.053966 16272 solver.cpp:294] Solving VGG_VOC0712_SSD_300x300_train
I0505 10:32:28.053969 16272 solver.cpp:295] Learning Rate Policy: multistep
I0505 10:32:28.197612 16272 solver.cpp:332] Iteration 0, loss = 1.45893
I0505 10:32:28.197657 16272 solver.cpp:433] Iteration 0, Testing net (#0)
I0505 10:32:28.213793 16272 net.cpp:693] Ignoring source layer mbox_loss
I0505 10:42:04.390517 16272 solver.cpp:546]     Test net output #0: detection_eval = 0.570833
I0505 10:42:04.414819 16272 solver.cpp:337] Optimization Done.
I0505 10:42:04.414847 16272 caffe.cpp:254] Optimization Done.

作者：Ericzhang922
链接：https://www.jianshu.com/p/4eaedaeafcb4
來源：简书
简书著作权归作者所有，任何形式的转载都请联系作者获得授权并注明出处。

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