Error while training SSD object detector

12 views (last 30 days)
i am using MATLAB 2020a to train SSD object detetctor for my database.I receive error which i am unable to troubleshoot. please help me out.
here is the code:
vehicleDataset1=vehicleDataset1.wbc;
rng(0);
shuffledIndices1 = randperm(height(vehicleDataset1));
idx1 = floor(0.6 * length(shuffledIndices1) );
trainingData1 = vehicleDataset1(shuffledIndices1(1:idx1),:);
testData1 = vehicleDataset1(shuffledIndices1(idx1+1:end),:);
imdsTrain1 = imageDatastore(trainingData1{:,'filename'});
bldsTrain1 = boxLabelDatastore(trainingData1(:,'wbc'));
imdsTest1 = imageDatastore(testData1{:,'filename'});
bldsTest1 = boxLabelDatastore(testData1(:,'wbc'));
trainingData1 = combine(imdsTrain1,bldsTrain1);
testData1 = combine(imdsTest1, bldsTest1);
data1 = read(trainingData1);
I1 = data1{1};
bbox1 = data1{2};
annotatedImage1 = insertShape(I1,'Rectangle',bbox1);
annotatedImage1 = imresize(annotatedImage1,2);
figure
imshow(annotatedImage1)
inputSize1 = [300 300 3];
numClasses1 = width(vehicleDataset1)-1;
lgraph1 = ssdLayers(inputSize1, numClasses1, 'resnet50');
augmentedTrainingData1 = transform(trainingData1,@augmentData);
augmentedData1 = cell(4,1);
for k = 1:4
data1 = read(augmentedTrainingData1);
augmentedData1{k} = insertShape(data1{1},'Rectangle',data1{2});
reset(augmentedTrainingData1);
end
figure
montage(augmentedData1,'BorderSize',10)
preprocessedTrainingData1 = transform(augmentedTrainingData1,@(data)preprocessData(data,inputSize1));
data1 = read(preprocessedTrainingData1);
I1 = data1{1};
bbox1 = data1{2};
annotatedImage1 = insertShape(I1,'Rectangle',bbox1);
annotatedImage1 = imresize(annotatedImage1,2);
figure
imshow(annotatedImage1)
options = trainingOptions('sgdm',...
'InitialLearnRate',5e-5,...
'MiniBatchSize',16,...
'Verbose',true,...
'MaxEpochs',50,...
'Shuffle','every-epoch',...
'VerboseFrequency',10,...
'CheckpointPath',tempdir);
[detector1,info1] = trainSSDObjectDetector(preprocessedTrainingData1,lgraph1,options);
data1 = read(testData1);
I1 = data1{1,1};
I1 = imresize(I1,inputSize1(1:2));
[bboxes1,scores1] = detect(detector1,I1, 'Threshold', 0.4);
I1 = insertObjectAnnotation(I1,'rectangle',bboxes1,scores1);
figure
imshow(I1)
here is error:
Invalid transform function defined on datastore.
The cause of the error was:
Error using bboxwarp>iParseInputs (line 324)
The value of 'bboxA' is invalid. Expected input number 1, bboxA, to be integer-valued.
Error in bboxwarp (line 81)
params = iParseInputs(bboxA,tform,ref,varargin{:});
Error in augmentData (line 23)
[B{2},indices] = bboxwarp(A{2},tform,rout,'OverlapThreshold',0.25);
Error in matlab.io.datastore.TransformedDatastore/applyTransforms (line 489)
data = ds.Transforms{ii}(data);
Error in matlab.io.datastore.TransformedDatastore/read (line 162)
[data, info] = ds.applyTransforms(data, info);
Error in nnet.internal.cnn.DataLoader/manageReadQueue (line 161)
data = read(self.Datastore);
Error in nnet.internal.cnn.DataLoader/readAhead (line 192)
manageReadQueue(self);
Error in nnet.internal.cnn.DataLoader (line 80)
readAhead(self);
Error in nnet.internal.cnn.GeneralDatastoreDispatcher (line 272)
this.DataLoader = nnet.internal.cnn.DataLoader(ds,...
Error in nnet.internal.cnn.DataDispatcherFactory.createDataDispatcherMIMO (line 170)
nnet.internal.cnn.GeneralDatastoreDispatcher( ...
Error in vision.internal.cnn.trainNetwork>iCreateTrainingDataDispatcher (line 190)
dispatcher = nnet.internal.cnn.DataDispatcherFactory.createDataDispatcherMIMO( ...
Error in vision.internal.cnn.trainNetwork (line 40)
trainingDispatcher = iCreateTrainingDataDispatcher(ds, mapping, trainedNet,...
Error in trainSSDObjectDetector (line 233)
[network, info] = vision.internal.cnn.trainNetwork(...
Error in wbc_detetctor_traininga (line 61)
[detector1,info1] = trainSSDObjectDetector(preprocessedTrainingData1,lgraph1,options);

Accepted Answer

Divya Gaddipati
Divya Gaddipati on 16 Jun 2020
Make sure your groundtruths are valid and non-empty i.e., the values of the bounding boxes are finite, positive, non-fractional, non-NaN and should be within the image boundary with a positive height and width. You should either discard or fix the samples with invalid bounding boxes.
  2 Comments
Huma Hafeez
Huma Hafeez on 24 May 2021
Thanks for your reply. You are right, there was a problem with ground truth

Sign in to comment.

More Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by