Error using reshape
Number of elements must not change. Use [] as one of the size inputs to automatically calculate the appropriate size for that dimension.

Error in trainYOLOv4ObjectDetector>iGetMaxIOUPredictedWithGroundTruth (line 565)
iou(:,:,:,batchSize) = reshape(maxOverlap,h,w,c);

Error in trainYOLOv4ObjectDetector>iGenerateTargets (line 418)
iou = iGetMaxIOUPredictedWithGroundTruth(bx,by,bw,bh,groundTruth,isRotatedBox);

Error in trainYOLOv4ObjectDetector>calculateLoss (line 302)
[boxTarget, objectnessTarget, classTarget, objectMaskTarget, boxErrorScale] = iGenerateTargets(gatheredPredictions, YTrain, params.InputSize, params.AnchorBoxes, penaltyThreshold, isRotatedBox);

Error in trainYOLOv4ObjectDetector>@(varargin)calculateLoss(lossParams,isRotatedBox,varargin) (line 226)
lossFcn = @(varargin) calculateLoss(lossParams,isRotatedBox,varargin);

Error in images.dltrain.internal.SerialTrainer>modelGradients (line 140)
loss = lossFcn(networkOutputs{:},targets{:});

Error in deep.internal.dlfeval (line 17)
[varargout{1:nargout}] = fun(x{:});

Error in deep.internal.dlfevalWithNestingCheck (line 19)
[varargout{1:nargout}] = deep.internal.dlfeval(fun,varargin{:});

Error in dlfeval (line 31)
[varargout{1:nargout}] = deep.internal.dlfevalWithNestingCheck(fun,varargin{:});

Error in images.dltrain.internal.SerialTrainer/fit (line 76)
[loss,grad,state,networkOutputs,lossData] = dlfeval(@modelGradients,self.Network,self.LossFcn,…

Error in images.dltrain.internal.dltrain (line 114)
net = fit(networkTrainer);

Error in trainYOLOv4ObjectDetector (line 245)
[trainedDetector,infoTrain] = images.dltrain.internal.dltrain(mbq,detector,options,lossFcn,metrics,validationPatienceMetric,’ExperimentMonitor’,params.ExperimentMonitor);

I have single class dataset withy class name person and this is error i am facing a time of training, i have gpu compute capacity 5.2 with gpu Nvidia M400

what could be issue here , i am cofuse that is it with preprocessing or compute capacityError using reshape
Number of elements must not change. Use [] as one of the size inputs to automatically calculate the appropriate size for that dimension.

Error in trainYOLOv4ObjectDetector>iGetMaxIOUPredictedWithGroundTruth (line 565)
iou(:,:,:,batchSize) = reshape(maxOverlap,h,w,c);

Error in trainYOLOv4ObjectDetector>iGenerateTargets (line 418)
iou = iGetMaxIOUPredictedWithGroundTruth(bx,by,bw,bh,groundTruth,isRotatedBox);

Error in trainYOLOv4ObjectDetector>calculateLoss (line 302)
[boxTarget, objectnessTarget, classTarget, objectMaskTarget, boxErrorScale] = iGenerateTargets(gatheredPredictions, YTrain, params.InputSize, params.AnchorBoxes, penaltyThreshold, isRotatedBox);

Error in trainYOLOv4ObjectDetector>@(varargin)calculateLoss(lossParams,isRotatedBox,varargin) (line 226)
lossFcn = @(varargin) calculateLoss(lossParams,isRotatedBox,varargin);

Error in images.dltrain.internal.SerialTrainer>modelGradients (line 140)
loss = lossFcn(networkOutputs{:},targets{:});

Error in deep.internal.dlfeval (line 17)
[varargout{1:nargout}] = fun(x{:});

Error in deep.internal.dlfevalWithNestingCheck (line 19)
[varargout{1:nargout}] = deep.internal.dlfeval(fun,varargin{:});

Error in dlfeval (line 31)
[varargout{1:nargout}] = deep.internal.dlfevalWithNestingCheck(fun,varargin{:});

Error in images.dltrain.internal.SerialTrainer/fit (line 76)
[loss,grad,state,networkOutputs,lossData] = dlfeval(@modelGradients,self.Network,self.LossFcn,…

Error in images.dltrain.internal.dltrain (line 114)
net = fit(networkTrainer);

Error in trainYOLOv4ObjectDetector (line 245)
[trainedDetector,infoTrain] = images.dltrain.internal.dltrain(mbq,detector,options,lossFcn,metrics,validationPatienceMetric,’ExperimentMonitor’,params.ExperimentMonitor);

I have single class dataset withy class name person and this is error i am facing a time of training, i have gpu compute capacity 5.2 with gpu Nvidia M400

what could be issue here , i am cofuse that is it with preprocessing or compute capacity Error using reshape
Number of elements must not change. Use [] as one of the size inputs to automatically calculate the appropriate size for that dimension.

Error in trainYOLOv4ObjectDetector>iGetMaxIOUPredictedWithGroundTruth (line 565)
iou(:,:,:,batchSize) = reshape(maxOverlap,h,w,c);

Error in trainYOLOv4ObjectDetector>iGenerateTargets (line 418)
iou = iGetMaxIOUPredictedWithGroundTruth(bx,by,bw,bh,groundTruth,isRotatedBox);

Error in trainYOLOv4ObjectDetector>calculateLoss (line 302)
[boxTarget, objectnessTarget, classTarget, objectMaskTarget, boxErrorScale] = iGenerateTargets(gatheredPredictions, YTrain, params.InputSize, params.AnchorBoxes, penaltyThreshold, isRotatedBox);

Error in trainYOLOv4ObjectDetector>@(varargin)calculateLoss(lossParams,isRotatedBox,varargin) (line 226)
lossFcn = @(varargin) calculateLoss(lossParams,isRotatedBox,varargin);

Error in images.dltrain.internal.SerialTrainer>modelGradients (line 140)
loss = lossFcn(networkOutputs{:},targets{:});

Error in deep.internal.dlfeval (line 17)
[varargout{1:nargout}] = fun(x{:});

Error in deep.internal.dlfevalWithNestingCheck (line 19)
[varargout{1:nargout}] = deep.internal.dlfeval(fun,varargin{:});

Error in dlfeval (line 31)
[varargout{1:nargout}] = deep.internal.dlfevalWithNestingCheck(fun,varargin{:});

Error in images.dltrain.internal.SerialTrainer/fit (line 76)
[loss,grad,state,networkOutputs,lossData] = dlfeval(@modelGradients,self.Network,self.LossFcn,…

Error in images.dltrain.internal.dltrain (line 114)
net = fit(networkTrainer);

Error in trainYOLOv4ObjectDetector (line 245)
[trainedDetector,infoTrain] = images.dltrain.internal.dltrain(mbq,detector,options,lossFcn,metrics,validationPatienceMetric,’ExperimentMonitor’,params.ExperimentMonitor);

I have single class dataset withy class name person and this is error i am facing a time of training, i have gpu compute capacity 5.2 with gpu Nvidia M400

what could be issue here , i am cofuse that is it with preprocessing or compute capacity preprocessing, computer vision MATLAB Answers — New Questions

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