I have a problem with my detector , i get [bbox, score, label] empty.

7 vues (au cours des 30 derniers jours)
abdullah al-dulaimi
abdullah al-dulaimi le 17 Juil 2022
%% detection
pp=alexnet;
pp1=pp.Layers;
pp=pp.Layers(1:19);
ppp=[pp
fullyConnectedLayer(2)
softmaxLayer()
classificationLayer()];
options = trainingOptions('sgdm', ...
'MiniBatchSize', 10, ...
'InitialLearnRate', 1e-3, ...
'MaxEpochs', 1, ...
'CheckpointPath', tempdir);
train1 =trainFastRCNNObjectDetector(gTruth, ppp, options, ...
'NegativeOverlapRange', [0 0.1], ...
'PositiveOverlapRange', [0.5 1], ...
'SmallestImageDimension', 300);
img = imread('image (825).JPG');
[bbox, score, label] = detect(train1, img);
imshow(insertObjectAnnotation(img, 'rectangle', bbox, label));

Réponses (1)

Shuba Nandini
Shuba Nandini le 1 Sep 2023
Hello, 
It is my understanding that you want to train the trainFastRCNNObjectDetector” with ‘alexnet’ as the backbone network.
As per the documentation, “trainFastRCNNObjectDetector” function offers a functionality to automatically transform the backbone classification network, into a Fast R-CNN network by adding an ROI max pooling layer, classification layer and regression layer.
The above functionality can be achieved, by specifying the required classification network name for the “network” argument. 
Please refer to the following link, for further information, 
Hope this helps!
Regards,
Shuba Nandini

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