Comments (2)
Yes, you are right. These are two different network structures. The difference is how many layers these two tasks are shared. The latter network structure will cost more feed forward time.
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qiexing 你好,你提供的model是使用 train/train_val.prototxt训练的吗?如果是,那使用 train/train_val.prototx训练的模型可以在使用model/deploy.prototxt做预测吗?
from face-landmark-localization.
Related Issues (20)
- 训练loss停止下降问题 HOT 4
- Running the "python landmarkPredict.py predictImage testList.txt" error! HOT 2
- error :RuntimeError: data array has wrong number of channels HOT 1
- 请问训练数据大概有多少? HOT 1
- 直接运行.py报了这个错 HOT 2
- Missing parentheses in call to 'print' HOT 5
- Face Landmark HOT 1
- 想请教一下 yaw roll pitch 这个角度是怎么算出来的?
- Landmark to head-pose
- 制作HDF5数据请教 HOT 5
- 哈喽,请问但看特征点的loss,你最终可以训到多少呢?
- 数据扩增中旋转角度的代码方便发一份吗
- 测试集输出结果全部是一样的 HOT 7
- error: reference to ‘list’ is ambiguous
- 有关训练数据制作
- 这个网络结构是VGG吗?我怎么看着很像是AlexNet? HOT 1
- Request train dataset HOT 2
- 请问如何查看模型是怎么样的/
- How to make training prediction on one's own data set?
- landmark for video
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