Comments (7)
考虑到自身添加数据后 需要人为判别其类别属性 成本高且不好判断(人为误差)去除了类别属性权重
from pfld_68points_pytorch.
好的,谢谢
from pfld_68points_pytorch.
好的,谢谢
客气 留赞ok? 哈
from pfld_68points_pytorch.
请问mobilenet-v2-0.25实测的效果好吗,我这边训练的飘的比较厉害,很不稳定
from pfld_68points_pytorch.
请问mobilenet-v2-0.25实测的效果好吗,我这边训练的飘的比较厉害,很不稳定
可以将飘的比较厉害的图片打印出来 然后查看一下 确认是角度很大的人脸还是正常人脸?
from pfld_68points_pytorch.
我是在线测试的,正对着测试也飘的比较厉害
from pfld_68points_pytorch.
我是在线测试的,正对着测试也飘的比较厉害
喔喔 可能输出特征点的网络较浅 而辅助网络(输出三个角度)的模型较强 极有可能都学到角度大的人脸去了 裁剪一下辅助网络或者干脆不要 再训练一下 试试看
from pfld_68points_pytorch.
Related Issues (20)
- 有没有使用PFLD做头部姿态估计的代码,而不是使用dlib
- train_model.py中的一点疑问 HOT 2
- 请问你这边提供的预训练模型是使用的什么数据集训练的? HOT 1
- 读取数据出错
- 训练多少个epoch后loss能正常收敛 HOT 8
- 关于使用300W数据集进行训练的问题 HOT 3
- 有关3D人脸坐标的问题 HOT 1
- 还想没有300W的困难数据的txt文件(ibug的130多张图的)
- test代码的算error分母好像不对 HOT 1
- 脸离摄像头较近关键点出现较大偏移 HOT 1
- Loss saturate after 80 Epoch HOT 1
- Does model also provides each landmark confidence score HOT 3
- 关于coco里的关键点 HOT 3
- 没有依赖包版本文件 HOT 2
- 欧拉角这部分怎么理解的呢 HOT 1
- 关于用自己制作的人脸数据集应该如何预处理的问题?
- 好像给dataloader设置num_worker就会出bug?
- 关于损失函数的问题 HOT 1
- 98 点 转 68 点的眼睛的关键点没对应上
- LICENSE
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from pfld_68points_pytorch.