how to get PointNet network (no pointnet++) Layers?

Hi everybody

I train pointnet network in this matlab example:

https://de.mathworks.com/help/vision/ug/point-cloud-classification-using-pointnet-deep-learning.html

But I can't use this network in my work.

I need a MATLAB net (series network or DAG network) to be used in "DeepLearning HDL ToolBox Support Package For Xilinx FPGA And SoC Device".

Or a version of PointNet open with "DeepNetworksDesigner".

Note: Only PointNet is required, it is not possible to use PointNetPlusPlus.

Answer 1

[Venu]

Hi @mohammad,

I can suggest you a series network based on https://de.mathworks.com/help/vision/ug/point-cloud-classification-using-pointnet-deep-learning.html this documentation. But this is just a simplified example and should be adjusted to match your specific PointNet architecture.

% Define the layers for the PointNet model
inputLayer = imageInputLayer([3, 1, 1], 'Name', 'input', 'Normalization', 'none');
convLayer1 = convolution2dLayer(64, 1, 'Name', 'conv1', 'Padding', 'same');
convLayer2 = convolution2dLayer(64, 1, 'Name', 'conv2', 'Padding', 'same');
maxPoolLayer = maxPooling2dLayer([3, 1], 'Stride', [2, 1], 'Name', 'maxpool');
fullyConnectedLayer1 = fullyConnectedLayer(128, 'Name', 'fc1');
fullyConnectedLayer2 = fullyConnectedLayer(10, 'Name', 'fc2');
softmaxLayer = softmaxLayer('Name', 'softmax');
classificationLayer = classificationLayer('Name', 'classoutput');

% Assemble the layers into a Layer Graph
lgraph = layerGraph([inputLayer, convLayer1, reluLayer, convLayer2, reluLayer, maxPoolLayer, fullyConnectedLayer1, reluLayer, fullyConnectedLayer2, softmaxLayer, classificationLayer]);

% Convert the Layer Graph to a Series Network
net = assembleNetwork(lgraph);