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询问下ArcFace的代码,谢谢
你好,请问Arcface::normalize()函数是做什么用的?为什么要对输出的特征值做这步处理?ArcFace官方的python代码好像没这步处理?
还有ArcFace的特征输出长度为512,你这为什么是128?
请问您用的是什么版本的ncnn?使用我自行编译的ncnn,链接运行之后显示段错误
关于arcface.cpp中preprocess输入的图像问题
非常感谢您的开源工作。
关于preprocess(ncnn::Mat img, sst_face info)的第一个参数是通过mtcnn截取的脸部图像还是原始图像呢?
preprocess函数内部在做脸部对齐的时候直接传入了img,是不是应该传入mtcnn截取的脸部图像?
warpAffineMatrix(img, out, M, image_w, image_h)
不知道是不是我哪里理解错了,期待您的解答,谢谢!
Bbox value normalization
@KangKangLoveCat
This is how I got the bbox value "results1[0].regreCoord" obtained as a result of the detection model, but the drawn rectangle is drawn in different positions.
How can normalization be done?
Could you support mxnet model link corresponding to this ncnn mobilefacenet model
Hi,KangKangLoveCat
Thanks you so much for your open source work.I want to validate the accuracy using mxnet.Thanks again.
models对应的图像格式是BGR还是RGB的顺序?
您好,我运行了您的代码,效果很好。 我看到main函数中读入图像是按照BGR的格式读入的: ncnn::Mat ncnn_img1 = ncnn::Mat::from_pixels(img1.data, ncnn::Mat::PIXEL_BGR, img1.cols, img1.rows); 我疑惑的是,MTCNN和insightface在训练的时候是按照RGB的图像格式来训练的。 有的ncnn版本的MTCNN代码中使用的是ncnn::Mat::PIXEL_BGR2RGB的通道顺序。
我把输入图像换成RGB的格式,该代码也可以工作。
所以想确认下,MTCNN和insightface的模型对应的是哪一种,您是否在转换成ncnn模型的时候,就把对应的数据顺序从RGB转成了BGR?
非常感谢。
大神,我使用官方提供的LResNet100E-IR模型转化为ncnn模型后测试精度很低?
insightface Model Zoo LResNet100E-IR,ArcFace@ms1m-refine-v2 model-r100-ii 转换为ncnn模型加载测试 Similarity: 0.0810913,哪里的问题呢?
How to install and run program?
mergebn needed?
Do you need mergebn before converting caffemodel to ncnnmodel?
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