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Support for Segmentation #23
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@digital-idiot Hi, sorry for the late reply, if you want a semantic segmentation, then the model output size should same as input size. Semantic segmentation has its own model design, because we usually need deconvolution/resize the features that been convolution from input, like textbook U-net, So the classification model cant directly used for Semantic segmentation. But can be directly used as backbone for object detection, instance segmentation, etc. |
For this case specific, if i want to change it to semantic segmentation, the simple way is modified like u-net. just deconvolution it. following is just a general ideal. usual convolution way start deconvolution (can try use similar bock style from convolution) |
It seems that semantic segmentation is not supported, only image classification is supported. When I build a model with
input_shape = [256, 256,3]
andn_classes = 6
, it creates a model with output shape[None,6]
. The verbose output is:The text was updated successfully, but these errors were encountered: