Using Contrast Limited Adaptive Histograph Equalization for data augmentation
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MirPooya Salehi Moharer
on 23 May 2021
Commented: MirPooya Salehi Moharer
on 26 May 2021
Dear community
I'm trying to apply transfer learning in Yolov3 pretrained model for my custom data. I wanted to add CLAHE feature beside traditional Yolov3 data augmentation. Here is the code:
rng(0);
shuffledIndices = randperm(height(vehicleDataset));
idx = floor(0.6 * length(shuffledIndices));
trainingDataTbl = vehicleDataset(shuffledIndices(1:idx), :);
testDataTbl = vehicleDataset(shuffledIndices(idx+1:end), :);
imdsTrain = imageDatastore(trainingDataTbl.imageFilename);
imdsTest = imageDatastore(testDataTbl.imageFilename);
bldsTrain = boxLabelDatastore(trainingDataTbl(:, 2:end));
bldsTest = boxLabelDatastore(testDataTbl(:, 2:end));
trainingData = combine(imdsTrain, bldsTrain);
testData = combine(imdsTest, bldsTest);
augmentedTrainingData = transform(trainingData, @augmentData);
function data = augmentData(A)
data = cell(size(A));
for ii = 1:size(A,1)
I = A{ii,1};
bboxes = A{ii,2};
labels = A{ii,3};
sz = size(I);
if numel(sz) == 3 && sz(3) == 3
I = jitterColorHSV(I,...
'Contrast',0.0,...
'Hue',0.1,...
'Saturation',0.2,...
'Brightness',0.2);
end
% Randomly flip image.
tform = randomAffine2d('XReflection',true,'Scale',[1 1.1]);
rout = affineOutputView(sz,tform,'BoundsStyle','centerOutput');
I = imwarp(I,tform,'OutputView',rout);
% Apply same transform to boxes.
[bboxes,indices] = bboxwarp(bboxes,tform,rout,'OverlapThreshold',0.25);
labels = labels(indices);
% Return original data only when all boxes are removed by warping.
if isempty(indices)
data(ii,:) = A(ii,:);
else
data(ii,:) = {I, bboxes, labels};
end
end
end
function data = preprocessData(data, targetSize)
% Resize the images and scale the pixels to between 0 and 1. Also scale the
% corresponding bounding boxes.
for ii = 1:size(data,1)
I = data{ii,1};
imgSize = size(I);
% Convert an input image with single channel to 3 channels.
if numel(imgSize) < 3
I = repmat(I,1,1,3);
end
bboxes = data{ii,2};
I = im2single(imresize(I,targetSize(1:2)));
scale = targetSize(1:2)./imgSize(1:2);
bboxes = bboxresize(bboxes,scale);
data(ii, 1:2) = {I, bboxes};
end
end
I wanted to add the CLAHE (https://www.mathworks.com/help/images/ref/adapthisteq.html) to this perticular section but I'm keeping get error. Can anyone help me through?
Best regards.
3 Comments
DGM
on 26 May 2021
You didn't answer either question. If you tried to use it somewhere, I can't guess how you did. I can't guess what error you got. All I know is that you did something and it didn't work.
If for some reason you're trying to use it on RGB or multipage/multiframe images, then you'll need to do it one channel/page/frame at a time.
Accepted Answer
Shashank Gupta
on 26 May 2021
Edited: Shashank Gupta
on 26 May 2021
Hi,
I see you want to use CLAHE as one of the data augmentation technique, you can simply add the adapthisteq function in the augmentData function as descibed in one of the comment by @DGM. Below is a reference code for you.
% Everything inside the augmentData remain same, just add CLAHE.
function data = augmentData(A)
data = cell(size(A));
for ii = 1:size(A,1)
I = A{ii,1};
bboxes = A{ii,2};
labels = A{ii,3};
J = adapthisteq(I);
if isempty(indices)
data(ii,:) = A(ii,:);
else
data(ii,:) = {I, bboxes, labels};
end
end
end
I hope this helps.
Cheers.
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