Training the RCNN Detector with multivariable from groundtruth

Question

Abdussalam Elhanashi 2019-9-5

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/479046-training-the-rcnn-detector-with-multivariable-from-groundtruth

回答： Kritika Bansal 2019-9-13

采纳的回答： Kritika Bansal

在 MATLAB Online 中打开

Hi guys

Hope you are doing well

I have one code which is for Traning the RCNN object detector for detecting the smoke

i made dataset for labelling set of images which have many variable such as sky cars people smoke however i want in my code that to train the detector to detect smoke and not to detect the other variables which are labelled

currently in my code i can only make selecetlabels for smoke and traning the detector with smoke but i want to know how to select other variables and train the detector not to detect or select other variables

herein my code

load('gTruth.mat')
smokedetection = selectLabels(gTruth,'smoke');
if isfolder(fullfile('TrainingData'))
    cd TrainingData
else
    mkdir TrainingData
end 
addpath('TrainingData');
options = trainingOptions('sgdm', ...
  'MiniBatchSize', 32, ...
  'InitialLearnRate', 1e-6, ...
  'MaxEpochs', 10);
layers = [
    imageInputLayer([32 32 3],"Name","imageinput")
    convolution2dLayer([5 5],32,"Name","conv","BiasLearnRateFactor",2,"Padding",[2 2 2 2],"WeightsInitializer","narrow-normal")
    maxPooling2dLayer([3 3],"Name","maxpool","Stride",[2 2])
    reluLayer("Name","relu")
    averagePooling2dLayer([3 3],"Name","avgpool","Stride",[2 2])
    fullyConnectedLayer(2,"Name","fc_rcnn","BiasL2Factor",1,"BiasLearnRateFactor",10,"WeightLearnRateFactor",20,"WeightsInitializer","narrow-normal")
    softmaxLayer("Name","softmax")
    classificationLayer("Name","classoutput")];
trainingData = objectDetectorTrainingData(smokedetection,'SamplingFactor',1,...
'WriteLocation','TrainingData');
detector = trainRCNNObjectDetector(trainingData, layers, options,  ...
        'NegativeOverlapRange', [0 0.3]);
save('Detector.mat','detector');