Is there any example about fcnLayers and its predictions for semantic segmentation
3 vues (au cours des 30 derniers jours)
Even though the structure of fcnLayers was provided in the latest released Matlab, the documentation about fcnLayers seems not clear enough and insufficient. The only example I can find for reference is "Semantic Segmentation Using Deep Learning" that used SegNet. Besides, either SegNet or FCN can take arbitrary size input image, and produce the same size labelled output. The structure that provided in Matlab limited the functions with the fixed size input image. It will be great if there is an example of SegNet or FCN that takes PASCAL VOC data just like it mentioned in the reference papers.
Birju Patel le 23 Fév 2018
In R2017b, we cannot train with arbitrary size images. This is a feature we will consider for a future release. We will also look to add more examples using datasets like PASCAL VOC.
One potential workaround is to use the pixelLabelImageSource with the OutputSizeMode set to 'randcrop' and provide a suitable OutputSize value for training the network. This will ensure that during training the network is trained with objects at their original scale at the cost of losing some of the scene context.
If loss of scene context is not permitted by your application, then you will have to set OutputSize to 'resize'.
See here for more details on the OutputSizeMode and OutputSize properties:
azza elbagoury le 15 Avr 2018
why the following error appears when training the fully convolution network. this network is built with (fcnLayers)function??
>>lgraph = fcnLayers(imageSize,numClasses,'type','8s'); >> [net, info] = trainNetwork(datasource,lgraph,options); Training on single CPU. Initializing image normalization.
Error using trainNetwork (line 154) Padding exceeds array bounds. Caused by: Error using builtin Padding exceeds array bounds.