Error Caused by: Layer 'cnn|concatenate': Input size mismatch. Size of input to this layer is different from the expected

Hi everyone,

I am trying to train a pointpiller network using code and functions from this example:

https://ww2.mathworks.cn/help/deeplearning/ug/lidar-object-detection-using-pointpillars-deep-learning.html

However, at the final stage,

[detector,info] = trainPointPillarsObjectDetector(cdsAugmented,detector,options);

I am receiving following error,

Processing data in minibatchqueue....

*************************************************************************
Data processing complete.

Error using dlnetwork/initialize
Invalid network.

Error in trainPointPillarsObjectDetector (line 182)
    dlnet = initialize(dlnet);

Error in TrainingPointPiller (line 231)
    [detector,info] = trainPointPillarsObjectDetector(cdsAugmented,detector,options);

Caused by:
    Layer 'cnn|concatenate': Input size mismatch. Size of input to this layer is different from the expected
    input size.
    Inputs to this layer:
        from layer 'cnn|up1|bn' (size 289(S) × 248(S) × 128(C) × 1(B))
        from layer 'cnn|up2|bn' (size 290(S) × 248(S) × 128(C) × 1(B))
        from layer 'cnn|up3|bn' (size 292(S) × 248(S) × 128(C) × 1(B))

Could you please point me to where I am making a mistake?

P.S. The above example was to train a point piller on two class (car and Truck), however, I modiefied the code and training it on just one class i.e. Car.

Thank you very much for your time :)

[Sebastiaan Hofstee]

Have you by any chance solved this issue? If so, how did you solve it? I am currently experiencing the exact same issue namely. Thank you in advance!

[Sarang Jokhio]

Hi @Sebastiaan Hofstee. Unfortunatly not, I gave up.

[Dmitry Rogachev]

Try these values as in the example

xMin = 0.0; % Minimum value along X-axis.

yMin = -39.68; % Minimum value along Y-axis.

zMin = -5.0; % Minimum value along Z-axis.

xMax = 69.12; % Maximum value along X-axis.

yMax = 39.68; % Maximum value along Y-axis.

zMax = 5.0; % Maximum value along Z-axis.