How to apply Matlab CNN code on an input image with 6 channels
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Chandrama Sarker
el 25 de Jul. de 2017
Comentada: Walter Roberson
el 15 de Mzo. de 2019
I have currently applied the Matbal CNN function to train my research data. Unlike, the Matlab 'lettersTrainSet'with a size of 28x28x1x1500 (4-D array), the input train data of my experiment have a size of 7x7x6x30,000. The problem I have encountered is that while running the 'trainNetwork' function, Matlab shows me an error: *Error using trainNetwork>iAssertValidImageArray (line 575) X must be a 4-D array of images.
Error in trainNetwork>iParseInput (line 329) iAssertValidImageArray( X );
Error in trainNetwork (line 68) [layers, opts, X, Y] = iParseInput(varargin{:});*
However, the same training data with 3 channels or 1 channels I can run the CNN code without any error message. It will be a great help if anyone can suggest how to use image data with more than 3 channels in Matlab for CNN classification.
1 comentario
Armin Eskandari
el 27 de Oct. de 2017
Hi, all I have the same problem, Please remove this limitation
Respuesta aceptada
Kristen Amaddio
el 27 de Jul. de 2017
Currently, CNN exclusively supports single and RGB channel imagery. Due to this limitation, the ability to use CNNs with image data with more than 3 channels is not available at this time.
I work at MathWorks, so I have forwarded this feedback to the relevant development team.
7 comentarios
$
el 15 de Mzo. de 2019
I have currently applied the Matbal CNN function to train my research data. Unlike, the Matlab 'lettersTrainSet'with a size of 28x28x1x1500 (4-D array), the input train data of my experiment have a size of 7x7x2500. The problem I have encountered is that while running the 'trainNetwork' function, Matlab shows me an error: *Error using trainNetwork>iAssertValidImageArray (line 575) X must be a 4-D array of images.
Error in trainNetwork>iParseInput (line 329) iAssertValidImageArray( X );
Error in trainNetwork (line 68) [layers, opts, X, Y] = iParseInput(varargin{:});*
please help me in this regard
Más respuestas (4)
jim peyton
el 1 de Nov. de 2017
Editada: jim peyton
el 1 de Nov. de 2017
If the development team is prioritizing by market need, this is a deal-breaker for a few of our applications too:
Using XYZRGB (6ch), or XYZ+Gray(4ch), or XYZ+normals+gray(7ch), or two stereo channels with multiple exposures/textures each (up to 24ch)...
Carole
el 21 de Feb. de 2018
This is the same for me. I wanted to implement a deconvolutional neural network and thus meed to have an input layer with more than 3 channels (to input the feature map and also to modify them as all needed layers for this are not yet implemented). Is there any workaround, or will this fixed in the next release? I will have to switch to Python otherwise. Is it in the plans of the development team? Cheers.
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Hang-Rai Kim
el 17 de Abr. de 2018
I want to apply CNN in 3D images (MRI data). I am planning to use 3D images as 2D x z stacks thus need to work in 2D CNN with multi channels. Please let me know what should i do.. Thank you.
9 comentarios
Áron Görög
el 23 de Abr. de 2018
Hang-Rai Kim, this might be useful for you:
https://www.mathworks.com/matlabcentral/fileexchange/58447-hagaygarty-mdcnn
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