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Home Page: https://github.com/Tencent/ncnn
基于ncnn的face-landmark
Home Page: https://github.com/Tencent/ncnn
这个example在Linux系统上,用g++编译,运行时出现段错误,请问什么原因
基于原生ncnn只移植substract_mean_normalize
只移植一个函数。substract_mean_normalize
发现无法获得任何 人脸landmark。
代码一样,请问为啥?
代码没有改变,在ubuntu环境编译可执行文件运行后,显示的关键点有点乱
貌似只有自带的人脸有效,用其他的人脸图片或者摄像头抓的图片就对不上
我看到网络激活函数是用的tanh+absval,请问这有什么出处么?是不是说做回归任务这样激活效果会好?
你好,多谢你的分享,我这边在安卓端跑成功了。但是每次需要计算一次图像的均值与方差,这个比较耗时。模型训练的时候没有指定固定的均值与方差吗?还有一个问题需要请教下:
1、原始的人脸区域图像作为ncnn输入,计算mean和vars,在进行ncnn的from_pixels_resize
2、原始的人脸区域resize为60*60 ,计算均值与方差,在进行ncnn的from_pixels,两种方式是不是第二种方式更符合训练流程?
我用新版本的ncnn在android上读取提供的landmark model遇到问题,似乎提供的文件还是用的旧的caffe格式。
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