www.gusucode.com > Adaboost算法训练人脸图像和非人脸图像，通过迭代得到由多个弱分类器组合而成的强分类器，实现图片里的人脸检测。 > Adaboost算法训练人脸图像和非人脸图像，通过迭代得到由多个弱分类器组合而成的强分类器，实现图片里的人脸检测。/myfacedet02/myadaboost_te.m

    function class=myadaboost_te(adaboost_model,myte_func_handle,myFeature)
% function [L,hits,class]=adaboost_te(adaboost_model,te_func_handle,test_set,...
%                               true_labels)
%测试函数
hypothesis_n=length(adaboost_model.weights);
%sample_n=size(test_set,1);
%class_n=length(unique(true_labels));
temp_L=zeros(1,2,hypothesis_n);

for i=1:hypothesis_n
    temp_L(:,:,i)=myte_func_handle(adaboost_model.parameters{i},myFeature);
%     [temp_L(:,:,i),hits,error_rate]=te_func_handle(adaboost_model.parameters{i},...
%                                                     test_set,ones(sample_n,1),true_labels);
    temp_L(:,:,i)=temp_L(:,:,i)*adaboost_model.weights(i);
%   temp_L(:,:,i)=temp_L(:,:,i)*adaboost_model.weights(i);
end 
L=sum(temp_L,3);
%hits=sum(likelihood2class(L)==true_labels);
%zhe ge di fang gai le yi xie nei rong
%ye jiu shi ba zhe ge han shu chai kai le
class=likelihood2class(L);