matlab gui 交通标志识别代码

以下是基于 MATLAB GUI 的交通标志识别代码：

function varargout = traffic_sign_detection(varargin)
% TRAFFIC_SIGN_DETECTION MATLAB code for traffic_sign_detection.fig
%      TRAFFIC_SIGN_DETECTION, by itself, creates a new TRAFFIC_SIGN_DETECTION or raises the existing
%      singleton*.
%
%      H = TRAFFIC_SIGN_DETECTION returns the handle to a new TRAFFIC_SIGN_DETECTION or the handle to
%      the existing singleton*.
%
%      TRAFFIC_SIGN_DETECTION('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in TRAFFIC_SIGN_DETECTION.M with the given input arguments.
%
%      TRAFFIC_SIGN_DETECTION('Property','Value',...) creates a new TRAFFIC_SIGN_DETECTION or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before traffic_sign_detection_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to traffic_sign_detection_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 traffic_sign_detection

% Last Modified by GUIDE v2.5 25-Feb-2020 14:13:17

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @traffic_sign_detection_OpeningFcn, ...
                   'gui_OutputFcn',  @traffic_sign_detection_OutputFcn, ...
                   'gui_LayoutFcn',  [] , ...
                   'gui_Callback',   []);
if nargin && ischar(varargin{1})
    gui_State.gui_Callback = str2func(varargin{1});
end

if nargout
    [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
    gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT


% --- Executes just before traffic_sign_detection is made visible.
function traffic_sign_detection_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 traffic_sign_detection (see VARARGIN)

% Choose default command line output for traffic_sign_detection
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes traffic_sign_detection wait for user response (see UIRESUME)
% uiwait(handles.figure1);

% --- Outputs from this function are returned to the command line.
function varargout = traffic_sign_detection_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 detect_button.
function detect_button_Callback(hObject, eventdata, handles)
% hObject    handle to detect_button (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Load the traffic sign dataset
load('trafficSigns.mat', 'trainData', 'testData', 'trainLabels', 'testLabels');

% Display some of the training images
figure;
perm = randperm(size(trainData, 4), 20);
for i = 1:20
    subplot(4, 5, i);
    imshow(trainData(:, :, :, perm(i)));
end

% Extract HOG features from the training images
cellSize = [8 8];
hogFeatureSize = length(hog_4x4(ones(cellSize * 2)));
hogFeatureSize = length(hog_4x4(ones(cellSize * 2, 'uint8')));
numImages = size(trainData, 4);
hogFeatures = zeros(numImages, hogFeatureSize, 'single');
for i = 1:numImages
    hogFeatures(i, :) = extractHOGFeatures(trainData(:, :, :, i), 'CellSize', cellSize);
end

% Train a classifier using the extracted HOG features
% SVM classifier
classifier = fitcecoc(hogFeatures, trainLabels);

% Read the input image
[file,path] = uigetfile({'*.jpg';'*.jpeg';'*.png';'*.gif'}, 'Select an image');
if ~isequal(file, 0)
    img = imread(fullfile(path,file));
    axes(handles.input_image);
    imshow(img);
else
    return;
end

% Preprocess the input image
img = imresize(img, [32 32]);
grayimg = rgb2gray(img);
level = graythresh(grayimg);
bwimg = ~im2bw(grayimg, level);
bwimg = bwareaopen(bwimg, 30);
se = strel('disk', 2);
bwimg = imclose(bwimg, se);
bwimg = imfill(bwimg, 'holes');
axes(handles.processed_image);
imshow(bwimg);

% Extract HOG features from the input image
hogFeatureSize = length(hog_4x4(ones(cellSize * 2)));
hogFeatureSize = length(hog_4x4(ones(cellSize * 2, 'uint8')));
hogFeatures = extractHOGFeatures(bwimg, 'CellSize', cellSize);

% Predict the class of the input image
predictedLabel = predict(classifier, hogFeatures);
axes(handles.output_image);
imshow(img);
title(sprintf('Predicted Sign: %d', predictedLabel));

% --- Executes on button press in clear_button.
function clear_button_Callback(hObject, eventdata, handles)
% hObject    handle to clear_button (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

cla(handles.input_image,'reset');
cla(handles.processed_image,'reset');
cla(handles.output_image,'reset');

此代码需要依赖于 `trafficSigns.mat` 数据集和 `extractHOGFeatures` 函数。此外，还需要将图形用户界面文件 `traffic_sign_detection.fig` 与此代码一起使用。

您可以在 MathWorks 网站上找到 `trafficSigns.mat` 数据集和 `extractHOGFeatures` 函数。另外，您也可以尝试使用其他数据集和特征提取方法。