基于matlab的自动人脸识别系统GUI设计

   之前做的一个课设项目半成品，一边网上找资料一边自己瞎捣鼓，完成了GUI界面的设计，实时视频中的人脸检测和追踪，PCA算法训练，单张人脸识别。但是识别率比较低，多人人脸识别和识别准确率统计这些部分还没有完成，等之后有空闲时再进行完善，然后将整个项目的具体过程给大家分享。下面是代码（省事，整个代码贴上来了，需要的话自己再处理一下吧，也欢迎各位大佬指点一下小白）。PCA算法部分参考了GitHub开源项目-face_recognize-master人脸检测部分参考了https://www.ilovematlab.cn/thread-201626-8-1.html

function varargout = charutupian(varargin)
% CHARUTUPIAN MATLAB code for charutupian.fig
%      CHARUTUPIAN, by itself, creates a new CHARUTUPIAN or raises the existing
%      singleton*.
%
%      H = CHARUTUPIAN returns the handle to a new CHARUTUPIAN or the handle to
%      the existing singleton*.
%
%      CHARUTUPIAN('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in CHARUTUPIAN.M with the given input arguments.
%
%      CHARUTUPIAN('Property','Value',...) creates a new CHARUTUPIAN or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before charutupian_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to charutupian_OpeningFcn via varargin.
%
%      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
%      instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES% Edit the above text to modify the response to help charutupian% Last Modified by GUIDE v2.5 23-Jun-2020 22:26:13% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...'gui_Singleton',  gui_Singleton, ...'gui_OpeningFcn', @charutupian_OpeningFcn, ...'gui_OutputFcn',  @charutupian_OutputFcn, ...'gui_LayoutFcn',  [] , ...'gui_Callback',   []);
if nargin && ischar(varargin{1})gui_State.gui_Callback = str2func(varargin{1});
endif nargout[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
elsegui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT% --- Executes just before charutupian is made visible.
function charutupian_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% varargin   command line arguments to charutupian (see VARARGIN)% Choose default command line output for charutupian
handles.output = hObject;% Update handles structure
guidata(hObject, handles);% UIWAIT makes charutupian wait for user response (see UIRESUME)
% uiwait(handles.figure1);% --- Outputs from this function are returned to the command line.
function varargout = charutupian_OutputFcn(hObject, eventdata, handles)
% varargout  cell array for returning output args (see VARARGOUT);
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)% Get default command line output from handles structure
varargout{1} = handles.output;% --- Executes on button press in pushbutton1.
function pushbutton1_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)% --- Executes on button press in pushbutton2.
function pushbutton2_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton2 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% varargout{1} = handles.output;% --- Executes on button press in pushbutton3.
function pushbutton3_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton3 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
%拍照% Create a cascade detector object.global vidDeviceglobal imim = step(vidDevice);axes(handles.axes2);imshow(im);% --- Executes on button press in pushbutton4.
function pushbutton4_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton4 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)global vidDevice
vidDevice = imaq.VideoDevice('winvideo',1,'MJPG_1280x720') ;
hVideoIn = vision.VideoPlayer;
hVideoIn.Name  = 'Input Video';
hVideoOut = vision.VideoPlayer;
hVideoOut.Name  = 'Output Video';
faceDetector = vision.CascadeObjectDetector();
pointTracker = vision.PointTracker('MaxBidirectionalError', 2);
numPts = 0;
n = 0;
while(n<200)videoFrame = step(vidDevice);videoFrameOutput = videoFrame;videoFrameGray = rgb2gray(videoFrame);if numPts < 10% Detection mode.bbox = faceDetector.step(videoFrameGray);if ~isempty(bbox)% Find corner points inside the detected region.points = detectMinEigenFeatures(videoFrameGray, 'ROI', bbox(1, :));% Re-initialize the point tracker.xyPoints = points.Location;numPts = size(xyPoints,1);release(pointTracker);initialize(pointTracker, xyPoints, videoFrameGray);% Save a copy of the points.oldPoints = xyPoints;% Convert the rectangle represented as [x, y, w, h] into an% M-by-2 matrix of [x,y] coordinates of the four corners. This% is needed to be able to transform the bounding box to display% the orientation of the face.bboxPoints = bbox2points(bbox(1, :));% Convert the box corners into the [x1 y1 x2 y2 x3 y3 x4 y4]% format required by insertShape.bboxPolygon = reshape(bboxPoints', 1, []);% Display a bounding box around the detected face.videoFrameOutput = insertShape(videoFrameOutput, 'Polygon', bboxPolygon, 'LineWidth', 3);% Display detected corners.videoFrameOutput = insertMarker(videoFrameOutput, xyPoints, '+', 'Color', 'white');endelse% Tracking mode.[xyPoints, isFound] = step(pointTracker, videoFrameGray);visiblePoints = xyPoints(isFound, :);oldInliers = oldPoints(isFound, :);numPts = size(visiblePoints, 1);if numPts >= 10% Estimate the geometric transformation between the old points% and the new points.[xform, oldInliers, visiblePoints] = estimateGeometricTransform(...oldInliers, visiblePoints, 'similarity', 'MaxDistance', 4);% Apply the transformation to the bounding box.bboxPoints = transformPointsForward(xform, bboxPoints);% Convert the box corners into the [x1 y1 x2 y2 x3 y3 x4 y4]% format required by insertShape.bboxPolygon = reshape(bboxPoints', 1, []);% Display a bounding box around the face being tracked.videoFrameOutput = insertShape(videoFrameOutput, 'Polygon', bboxPolygon, 'LineWidth', 3);% Display tracked points.videoFrameOutput = insertMarker(videoFrameOutput, visiblePoints, '+', 'Color', 'white');% Reset the points.oldPoints = visiblePoints;setPoints(pointTracker, oldPoints);endend% Display video.step(hVideoIn, videoFrame);step(hVideoOut, videoFrameOutput);n = n+1;
end
release(vidDevice);
release(hVideoOut);
release(hVideoIn);% --- Executes on button press in pushbutton5.
function pushbutton5_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton5 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
global im                   %待识别图片
global reference
global W
global imgmean              %行均值向量
global col_of_data          %列数
global pathname
global img_path_list% 预处理新数据
im = double(im(:));
objectone = W'*(im - imgmean);
distance = 100000000;% 最小距离法，寻找和待识别图片最为接近的训练图片
for k = 1:col_of_data     %遍历每张图片temp = norm(objectone - reference(:,k));  %if(distance>temp)aimone = k;distance = temp;aimpath = strcat(pathname, '/', img_path_list(aimone).name);axes( handles.axes3 )imshow(aimpath)disp('识别成功')elsedisp('识别不成功')end
end
disp('完成')% --- Executes on button press in pushbutton6.
function pushbutton6_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton6 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
%训练机器
global reference
global W
global imgmean
global col_of_data
global pathname
global img_path_list% 批量读取指定文件夹下的图片
pathname = uigetdir;
img_path_list = dir(strcat(pathname,'\*.jpg'));
img_num = length(img_path_list);
imagedata = [];
if img_num >0for j = 1:img_numimg_name = img_path_list(j).name;temp = imread(strcat(pathname, '/', img_name));   %读取照片temp = double(temp(:));imagedata = [imagedata, temp];end
end
col_of_data = size(imagedata,2);   %返回列数% 中心化 & 计算协方差矩阵
imgmean = mean(imagedata,2);             %返回行均值向量
for i = 1:col_of_dataimagedata(:,i) = imagedata(:,i) - imgmean;
end
covMat = imagedata'*imagedata;
[COEFF, latent, explained] = pcacov(covMat);% 选择构成95%能量的特征值
i = 1;
proportion = 0;
while(proportion < 95)proportion = proportion + explained(i);i = i+1;
end
p = i - 1;   % 特征脸
W = imagedata*COEFF;    % N*M阶
W = W(:,1:p);           % N*p阶，选出最大的P个构成变换矩阵（1280X720）*P% 训练样本在新座标基下的表达矩阵 p*M
reference = W'*imagedata;
p
img_path_list
disp('训练好了')% --- Executes on button press in pushbutton7.
function pushbutton7_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton7 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
global W
global reference
col_of_data = 60;pathname = uigetdir;
img_path_list = dir(strcat(pathname,'\*.bmp'));
img_num = length(img_path_list);
testdata = [];
if img_num >0for j = 1:img_numimg_name = img_path_list(j).name;temp = imread(strcat(pathname, '/', img_name));temp = double(temp(:));testdata = [testdata, temp];end
end
col_of_test = size(testdata,2);
testdata = center( testdata );
object = W'* testdata;% 最小距离法，寻找和待识别图片最为接近的训练图片
% 计算分类器准确率
num = 0;
for j = 1:col_of_test;distance = 1000000000000;for k = 1:col_of_data;temp = norm(object(:,j) - reference(:,k));if(distance>temp)aimone = k;distance = temp;endendif ceil(j/3)==ceil(aimone/4)num = num + 1;end
end
accuracy = num/col_of_test;
msgbox(['分类器准确率:                   ',num2str(accuracy)],'accuracy')% --- Executes on button press in pushbutton8.
function pushbutton8_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton8 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
global im;
[filename, pathname] = uigetfile({'*.jpg'},'choose photo');
p = [pathname, filename];
im = imread(p);
axes( handles.axes2);
imshow(im);function edit1_Callback(hObject, eventdata, handles)
% hObject    handle to edit1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)% Hints: get(hObject,'String') returns contents of edit1 as text
%        str2double(get(hObject,'String')) returns contents of edit1 as a double% --- Executes during object creation, after setting all properties.
function edit1_CreateFcn(hObject, eventdata, handles)
% hObject    handle to edit1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))set(hObject,'BackgroundColor','white');
end

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