olojuwin / facerecognize-for-mobile-phone Goto Github PK
View Code? Open in Web Editor NEW适用于移动端的人脸识别模型,计算量与mobilefacenet相同,但megaface上提升了2%+
适用于移动端的人脸识别模型,计算量与mobilefacenet相同,但megaface上提升了2%+
如题,请问下,如何集成在tensflows框架中,或者说下如何集成在android 项目中,谢谢
如题,谢谢!
我想复测一下模型在Megaface上的表现,我发现run.sh里面的run_experiment.py没找到,您可以告诉我怎么获取或者分享给我一下吗
训练方法后续会有公开吗?学习一下,我训练这个模型最好效果将近达到作者公布的数据。
您好,训练代码能否分享,谢谢。
caffe模型转换为openvino,同样两张照片,相似度从55.34%掉到45%左右,不知道你是不是有相同的情况
如题目所示,还请不吝赐教!感激不尽
作者你好,我测试了你训练的mobilefacenet模型(mxnet),lfw,cfp-fp,agedb-30,上的指标非常高,基本与你的说明相同,但是我测试了自己的数据集(静态配合式人脸数据),发现与我自己训练的模型性比,性能差的较多。说明下,我训练的是 (mobilefacenet 128维,就是insightface中的模型,没有做什么修改,用的数据集也是glint 公开数据集,我训练的LFW, cfp-fp,agedb-30的指标都比较低,大概式99.2%,89.1%和 94.2%左右),我很疑惑,为什么你在验证集上的指标比我高了很多,为什么在我的数据集上性能却有较大差距呐?希望可以和你探讨下这个问题?不知道你有没有在自己的数据集上测试过。
模型的人脸对齐是同insightface的吗?
zwface的有相关的论文吗?方便的话给我发个链接,我想了解一下思路
你好,看了下模型大小,你的好像比mobilefacenet的大很多。
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