Update yolov8Transform.m

Author: viakkala

+helper/yolov8Transform.m

@@ -7,29 +7,29 @@
 stride = [8,16,32];
 batch = 1;
 
-% Extract feature maps from Matlab model
-% Apply this if dlarray output
-predictions = cellfun(@extractdata,predictions,'UniformOutput',false);
-predictions = cellfun(@gather,predictions,'UniformOutput',false);
+pred = cell(3,1);
+predPermute = cell(3,1);
+predAll = cell(3,1);
 
-% Compute anchor grid and stride
-[anchorGrid, stride] = helper.make_anchors(predictions, stride);
-% anchor grid and stride transposed
-anchorGrid = anchorGrid';
-stride = stride';
-
-% Reshape predictions from model output
-pred = cellfun(@(p){permute(p,[2,1,3,4])}, predictions, 'UniformOutput',true);
-pred = cellfun(@(p){reshape(p,[],outputsPerAnchor, batch)}, pred, 'UniformOutput',true);
-pred = cellfun(@(p){permute(p,[2,1,3,4])}, pred, 'UniformOutput',true);
+for i = 1:size(predictions,1)
+    pred{i,1} = permute(predictions{i,1},[2,1,3,4]);
+    predPermute{i,1} = reshape(pred{i,1},[],outputsPerAnchor,batch);
+    predAll{i,1} = permute(predPermute{i,1},[2,1,3,4]);
+end
 
 % Concat all Predictions
-predCat = cat(2,pred{:});
+predCat = cat(2,predAll{:});
 
 % Split classes and boxes
 box = predCat(1:64,:,:);
 cls = predCat(65:end,:,:);
 
+% Compute anchor grid and stride
+[anchorGrid, stride] = helper.make_anchors(predictions, stride);
+% anchor grid and stride transposed
+anchorGrid = anchorGrid';
+stride = stride';
+
 box = helper.distributionFocalLoss(box);
 % Converting boxes to xywh format here
 box = helper.dist2bbox(box,anchorGrid);