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‎AnchorMask.mat

957 Bytes
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‎COVID19_LabelMaskAutomation.mlx

977 KB
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‎COVID19_LiveWebcamMask.mlx

5.03 KB
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‎COVID19_Mask_SSD.mat

42.5 MB
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‎COVID19_Mask_yolo.mat

97.6 MB
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‎COVID19_TestStillImage.mlx

758 KB
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‎COVID19_TrainMaskDetection.mlx

10.7 KB
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‎COVID19_VideoRunning.mlx

4.19 KB
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‎FaceMaskDetection.m

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classdef FaceMaskDetection < vision.labeler.AutomationAlgorithm
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properties(Constant)
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Name = 'Face Mask Detection';
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Description = 'This is a automatic Mask labeling algorithm.';
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UserDirections = {...
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['Automation algorithms are a way to automate manual labeling ' ...
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'tasks. This AutomationAlgorithm is a template for creating ' ...
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'user-defined automation algorithms. Below are typical steps' ...
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'involved in running an automation algorithm.'], ...
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['Run: Press RUN to run the automation algorithm. '], ...
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['Review and Modify: Review automated labels over the interval ', ...
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'using playback controls. Modify/delete/add ROIs that were not ' ...
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'satisfactorily automated at this stage. If the results are ' ...
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'satisfactory, click Accept to accept the automated labels.'], ...
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['Change Settings and Rerun: If automated results are not ' ...
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'satisfactory, you can try to re-run the algorithm with ' ...
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'different settings. In order to do so, click Undo Run to undo ' ...
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'current automation run, click Settings and make changes to ' ...
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'Settings, and press Run again.'], ...
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['Accept/Cancel: If results of automation are satisfactory, ' ...
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'click Accept to accept all automated labels and return to ' ...
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'manual labeling. If results of automation are not ' ...
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'satisfactory, click Cancel to return to manual labeling ' ...
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'without saving automated labels.']};
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end
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properties
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AllCategories = {'background'};
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FireName
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count
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end
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methods
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function isValid = checkLabelDefinition(algObj, labelDef)
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disp(['Executing checkLabelDefinition on label definition "' labelDef.Name '"'])
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if (strcmpi(labelDef.Name, 'Mask') && labelDef.Type == labelType.Rectangle)
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isValid = true;
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algObj.FireName = labelDef.Name;
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algObj.AllCategories{end+1} = labelDef.Name;
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end
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end
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function isReady = checkSetup(algObj)
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isReady = ~isempty(algObj);
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end
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function settingsDialog(algObj)
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disp('Executing settingsDialog')
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end
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end
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methods
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function initialize(algObj, I)
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disp('Executing initialize on the first image frame')
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end
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function autoLabels = run(algObj, I)
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disp('Executing run on image frame')
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[labelCord, label] = MaskLabel(I, algObj);
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autoLabels.Name = char(label);
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autoLabels.Type = labelType('Rectangle');
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autoLabels.Position = labelCord;
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algObj.count = algObj.count+1;
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end
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function terminate(algObj)
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disp('Executing terminate')
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end
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end
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end
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% Copyright 2020 The MathWorks, Inc.

‎GitSubmission.prj

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<?xml version="1.0" encoding="UTF-8"?>
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<MATLABProject xmlns="http://www.mathworks.com/MATLABProjectFile" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="1.0"/>

‎LICENSE

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Copyright (c) 2020, The MathWorks, Inc.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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3. In all cases, the software is, and all modifications and derivatives of the software shall be, licensed to you solely for use in conjunction with MathWorks products and service offerings.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

‎MaskLabel.m

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function [labelCord, label] = MaskLabel(I, ~)
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ori_sz = size(I, [1 2]);
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re_sz = [448 448];
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img = imresize(I, re_sz);
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scale = ori_sz./re_sz;
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bbox = predictFace(img, 'net_face_yolo.mat');
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bbox(:,4) = bbox(:,4)./2+20;
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bbox(:,2) = bbox(:,2)+bbox(:,4)-20;
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bbox(:,3) = bbox(:,3)+10;
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labelCord = bboxresize(round(bbox),scale);
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label = 'Mask';
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% Copyright 2020 The MathWorks, Inc.
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‎README.md

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‎SampleMaskData/a01.jpg

1.63 MB

‎SampleMaskData/a02.jpg

1.53 MB

‎SampleMaskData/a03.jpg

1.73 MB

‎SampleMaskData/mw_wanbin2.jpg

479 KB

‎SampleMaskData/mw_wanbin3.jpg

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‎SampleMaskData/mw_wanbin7.jpg

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‎SampleMaskData/mw_wanbin9.jpg

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‎SampleMaskData/zz.jpg

1.37 MB

‎images/.gitkeep

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‎images/image1.png

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‎images/image2.png

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‎images/image3.png

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‎images/image4.png

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‎predictFace.m

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function selectedBbox = predictFace(img_rz, matfile)
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%#codegen
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% This function detects the traffic signs in the image using Detection Network
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% (modified version of Yolo) and recognizes(classifies) using Recognition Network
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%
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% Inputs :
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%
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% im : Input test image
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%
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% Outputs :
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%
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% selectedBbox : Detected bounding boxes
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% idx : Corresponding classes
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% Copyright 2017-2018 The MathWorks, Inc.
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coder.gpu.kernelfun;
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% Converting into BGR format
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img_rz = img_rz(:,:,3:-1:1);
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img_rz = im2single(img_rz);
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%% TSD
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persistent detectionnet;
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if isempty(detectionnet)
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detectionnet = coder.loadDeepLearningNetwork(matfile,'Detection');
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end
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predictions = detectionnet.predict(img_rz);%, 'executionenvironment', 'cpu');
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%% Convert predictions to bounding box attributes
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classes = 1;
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num = 2;
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side = 11;
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thresh = 0.2;
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[h,w,~] = size(img_rz);
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boxes = single(zeros(0,4));
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probs = single(zeros(0,1));
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for i = 0:(side*side)-1
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for n = 0:num-1
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p_index = side*side*classes + i*num + n + 1;
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scale = predictions(p_index);
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prob = zeros(1,classes+1);
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for j = 0:classes
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class_index = i*classes + 1;
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tempProb = scale*predictions(class_index+j);
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if tempProb > thresh
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row = floor(i / side);
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col = mod(i,side);
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box_index = side*side*(classes + num) + (i*num + n)*4 + 1;
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bxX = (predictions(box_index + 0) + col) / side;
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bxY = (predictions(box_index + 1) + row) / side;
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bxW = (predictions(box_index + 2)^2);
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bxH = (predictions(box_index + 3)^2);
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prob(j+1) = tempProb;
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probs = [probs;tempProb];
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boxX = (bxX-bxW/2)*w+1;
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boxY = (bxY-bxH/2)*h+1;
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boxW = bxW*w;
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boxH = bxH*h;
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boxes = [boxes; boxX,boxY,boxW,boxH];
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end
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end
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end
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end
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%% Run Non-Maximal Suppression on the detected bounding boxess
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coder.varsize('selectedBbox',[98, 4],[1 0]);
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[selectedBbox,~] = selectStrongestBbox(round(boxes),probs);
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% Copyright 2020 The MathWorks, Inc.

‎resources/project/Project.xml

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<?xml version='1.0' encoding='UTF-8'?>
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<Info MetadataType="distributed" />

‎resources/project/ProjectData.type.Info.xml

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<?xml version='1.0' encoding='UTF-8'?>
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<Info Name="gitSubmission" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category.xml

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<Info ReadOnly="1" SingleValued="1" DataType="None" Name="분류" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/artifact.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="아티팩트" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/convenience.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="편의" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/derived.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="파생" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/design.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="설계" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/none.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="없음" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/other.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="기타" />

‎resources/project/Root.type.Categories/FileClassCategory.type.Category/test.type.Label.xml

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<Info ReadOnly="READ_ONLY" Name="테스트" />

‎resources/project/Root.type.Files/AnchorMask.mat.type.File.xml

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<Category UUID="FileClassCategory">
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<Label UUID="design" />
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</Category>
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</Info>

‎resources/project/Root.type.Files/COVID19_LabelMaskAutomation.mlx.type.File.xml

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</Info>

‎resources/project/Root.type.Files/COVID19_LiveWebcamMask.mlx.type.File.xml

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‎resources/project/Root.type.Files/COVID19_Mask_SSD.mat.type.File.xml

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‎resources/project/Root.type.Files/COVID19_Mask_yolo.mat.type.File.xml

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‎resources/project/Root.type.Files/COVID19_TestStillImage.mlx.type.File.xml

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‎resources/project/Root.type.Files/COVID19_TrainMaskDetection.mlx.type.File.xml

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‎resources/project/Root.type.Files/COVID19_VideoRunning.mlx.type.File.xml

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