How to increase network input size for 'Tiny-yolov3-coco'?

Question

Fahmi Akmal Dzulkifli ，2022-10-29

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https://ww2.mathworks.cn/matlabcentral/answers/1838638-how-to-increase-network-input-size-for-tiny-yolov3-coco

评论： Khushboo ，2022-10-31

Greetings,

I want to use 'tiny-yolov3-coco' for detecting the cells. As shown in the Figure, I used a network input size of 416x416. However, the total loss is still high. Therefore I want to increase the network input size to 832x832. The code that I used as follows:

networkInputSize = [832 832 3];

baseNetwork = 'tiny-yolov3-coco';

detector = yolov3ObjectDetector(baseNetwork);

net = detector.Network;

lgraph = layerGraph(net);

imgLayer = imageInputLayer(networkInputSize,"Name","input","Normalization","none");

lgraph = replaceLayer(lgraph,"input",imgLayer);

newbaseNetwork = assembleNetwork(lgraph);

However, I got the error as follows:

Error in trainyolov3 (line 61)

newbaseNetwork = assembleNetwork(lgraph);

Caused by:

Network: Missing output layer. The network must have at least one output layer.

Layer 'conv2d_10': Unconnected output. Each layer output must be connected to the input of another layer.

Layer 'conv2d_13': Unconnected output. Each layer output must be connected to the input of another layer.

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Answer 1

Khushboo 2022-10-31

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https://ww2.mathworks.cn/matlabcentral/answers/1838638-how-to-increase-network-input-size-for-tiny-yolov3-coco#answer_1087743

Hello,

The network that you are using is a dlnetwork (which does not have output layers) and not a DAG network. The assembleNetwork function returns a DAG network ready for prediction. If using a dlnetwork works for your usecase, you can do the following:

networkInputSize = [832 832 3];
baseNetwork = 'tiny-yolov3-coco';
detector = yolov3ObjectDetector(baseNetwork);
net = detector.Network;
lgraph = layerGraph(net);
imgLayer = imageInputLayer(networkInputSize,"Name","input","Normalization","none");
lgraph = replaceLayer(lgraph,"input",imgLayer);
newbaseNetwork = dlnetwork(lgraph);

Hope this answers your question!

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Khushboo 2022-10-31

Hello,

I am not able to understand what this code does. But from what I assume, the error is related to the number of dimensions defined for the last convolution layer. As you are changing the input size, I think the rest of the dimensions will have to be changes correspondingly. Kindly make sure you have done that.

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