after training a denoising network from dnCNNLayers, how to use it in denoisingNetwork and denoiseImage?
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Ming-Jer Tsai
on 31 Aug 2020
Commented: Ming-Jer Tsai
on 16 Sep 2020
I name my denoising network as dncnn_xfer, which is trained starting from dnCNNLayers. Since denoiseNetwork('dncnn') only accepts 'dncnn' I rename dncnn_xfer as dncnn, dncnn=dncnn_xfer. But net=denoiseNetwork ('dncnn') seems to always pick up the pretrained DnCNN existing in MATLIB instead of dncnn_fer.
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Accepted Answer
Madhav Thakker
on 16 Sep 2020
Hi Ming-Jer,
I understand that you want to use your custom denoising network. I assume you have trained the network sucessfully using the procedure. After training the network using trainnetwork, it returns a trained network in the output argument. There is no need to initialize a network using denoisingNetwork. denoiseImage can accepts as input the trained network and returns a denoised image.
Hope this helps.
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