www.gusucode.com > IPCV_Eval_Kit_R2019a_0ce6858工具箱matlab程序源码 > IPCV_Eval_Kit_R2019a_0ce6858/code/demo_files/I5_04_3_myHOGDigitClassification_discr_R2015a.m
%% HOG (Histogram of Oriented Gradient) 摿挜検 偲 % 敾暿暘椶婍丗Discriminant analysis classifier 傪巊偭偨丄庤彂偒悢帤偺幆暿 clear;clc;close all;imtool close all % 僩儗乕僯儞僌夋憸乮101枃x10暥帤庬乯偲僥僗僩夋憸乮12枃x10暥帤庬乯傊偺愨懳僷僗傪愝掕 pathData = [toolboxdir('vision'), '\visiondata\digits'] trainSet = imageSet([pathData,'\synthetic' ], 'recursive'); testSet = imageSet([pathData,'\handwritten'], 'recursive'); %% 慡僩儗乕僯儞僌梡夋憸椺偺昞帵 figure;montage([trainSet.ImageLocation], 'Size', [26 40]); %% 慡僥僗僩夋憸傪儌儞僞乕僕儏昞帵 (12枃 x 10暥帤庬丗奺庤彂偒悢帤傪擣幆) figure;montage([testSet(:).ImageLocation], 'Size', [10,12]); %% 4x4偺僙儖僒僀僘傪巊梡 (324師尦儀僋僩儖) cellSize = [4 4]; hogFeatureSize = 324; % length(hog_4x4) %% [KNN暘椶婍偺峔抸]丗fitcknn傪巊梡 % 10暥帤暘偺trainingFeatures 傪奿擺偡傞攝楍傪偁傜偐偠傔嶌惢 trainingFeatures = zeros(10*101,hogFeatureSize, 'single'); trainingLabels = zeros(10*101,1); % HOG摿挜検傪拪弌 for digit = 0:9 % 暥帤'0'乣'9' for i = 1:101 % 奺悢帤偛偲偵101枃偺僩儗乕僯儞僌梡夋憸 img = read(trainSet(digit+1), i); %僩儗乕僯儞僌夋憸偺撉崬傒 trainSet()偼丄1偐傜巒傑傞偺偱丄+1 img = im2bw(img,graythresh(img)); % 擇抣壔 trainingFeatures((digit)*101+i,:) = extractHOGFeatures(img,'CellSize',cellSize); trainingLabels((digit)*101+i) = digit; end end % 暘椶婍偺妛廗: 0偺暘嶶偑偁傞偨傔丄'pseudoLinear'偲'pseudoQuadratic' 傪巊梡 discrModelL = fitcdiscr(trainingFeatures, trainingLabels, 'DiscrimType','pseudoLinear') %媈帡慄宍敾暿暘椶婍 discrModelQ = fitcdiscr(trainingFeatures, trainingLabels, 'DiscrimType','pseudoQuadratic'); %媈帡擇師敾暿暘椶婍 %% [幆暿] 嶌惉偟偨暘椶婍偱庤彂偒悢帤(120枃)傪幆暿\帵丗predict() => 偙偺僨乕僞偵懳偟偰偼偆傑偔偄偐偢 Ir = zeros([16,16,3,120], 'uint8'); % 寢壥傪奿擺偡傞攝楍 for digit = 0:9 % for i = 1:12 % 奺悢帤偛偲偵12枃偺庤彂偒暥帤 img = read(testSet(digit+1), i); % testSet()偼丄1偐傜巒傑傞偺偱丄+1 BW = im2bw(img,graythresh(img)); % 2抣壔 testFeatures = extractHOGFeatures(BW,'CellSize',cellSize); predictedNum = predict(discrModelL, testFeatures); % testFeature 傪攝楍偵偟偰丄偁偲偱傑偲傔偰敾掕傕壜 if predictedNum == digit %惓偟偄幆暿偼惵怓丄岆擣幆偼愒怓 Ir(:,:,:,digit*12+i) = insertText(img,[6 4],num2str(predictedNum),'FontSize',9,'TextColor','blue','BoxOpacity',0.4); else Ir(:,:,:,digit*12+i) = insertText(img,[6 4],num2str(predictedNum),'FontSize',9,'TextColor','red','BoxOpacity',0.4); end end end % 寢壥偺昞帵 figure;montage(Ir, 'Size', [10,12]); %% [幆暿] 嶌惉偟偨暘椶婍偱庤彂偒悢帤(120枃)傪幆暿\帵丗predict() => 偙偺僨乕僞偵懳偟偰偼偆傑偔偄偐偢 Ir = zeros([16,16,3,120], 'uint8'); % 寢壥傪奿擺偡傞攝楍 for digit = 0:9 % for i = 1:12 % 奺悢帤偛偲偵12枃偺庤彂偒暥帤 img = read(testSet(digit+1), i); % testSet()偼丄1偐傜巒傑傞偺偱丄+1 BW = im2bw(img,graythresh(img)); % 2抣壔 testFeatures = extractHOGFeatures(BW,'CellSize',cellSize); predictedNum = predict(discrModelQ, testFeatures); % testFeature 傪攝楍偵偟偰丄偁偲偱傑偲傔偰敾掕傕壜 if predictedNum == digit %惓偟偄幆暿偼惵怓丄岆擣幆偼愒怓 Ir(:,:,:,digit*12+i) = insertText(img,[6 4],num2str(predictedNum),'FontSize',9,'TextColor','blue','BoxOpacity',0.4); else Ir(:,:,:,digit*12+i) = insertText(img,[6 4],num2str(predictedNum),'FontSize',9,'TextColor','red','BoxOpacity',0.4); end end end % 寢壥偺昞帵 figure;montage(Ir, 'Size', [10,12]); %% %% Copyright 2013-2014 The MathWorks, Inc. % 夋憸僨乕僞僙僢僩 % 僩儗乕僯儞僌夋憸丗insertText娭悢偱帺摦嶌惉 (廃埻偵暿偺悢帤桳傝) % 僥僗僩夋憸丗庤彂偒偺夋憸傪巊梡