Closed deerdodo closed 3 years ago
It seems that the shape of X_data
is (2892,128,128,3)
, that is
(the number of samples, height, width, number of channels)
.
So in the first layer, you should type input_shape = (None, 128, 128,3)
.
If you want to keep input_shape = (1,128, 128,3)
, equivalently, input=(None, 1,128,128,3)
, that means the number one 1 has some meaning, you have to change the shape of X_data
.
That is my opinion.
I'm setting up a keras model with Conv2D and LSTM layers and i try the following code .. i am trying not to reshape the LSTM layer but it also gives me an error that the index is out of range. I have searched a lot but i couldn't figure out where is the problem or how to fix it The images which are the input to the CNN model are 128*128
This is what i have tried
but it gives me the following error
This is the model summary