Home/ Questions/Q 410
Next
Answered
Kenil Vasani
Kenil Vasani

Kenil Vasani

View Profile
  • 3
Asked: 2020-12-11T20:35:40+00:00 In:

Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5

  • 3

I have checked all the solutions, but still, I am facing the same error. My training images shape is (26721, 32, 32, 1), which I believe it is 4 dimension, but I don’t know why error shows it is 5 dimension. 

 model = Sequential()

 model.add(Convolution2D(16, 5, 5, border_mode='same', input_shape= input_shape ))

So this is how I am defining model.fit_generator 

model.fit_generator(train_dataset, train_labels, nb_epoch=epochs, verbose=1,validation_data=(valid_dataset, valid_labels), nb_val_samples=valid_dataset.shape[0],callbacks=model_callbacks)
conv-neural-networkdeep-learningkeraspythontensorflow
Share

    1 Answer

    1. Rohit Patel

      Rohit Patel

      View Profile
      Best Answer

      The problem is input_shape.

      It should actually contain 3 dimensions only. And internally keras will add the batch dimension making it 4.

      Since you probably used input_shape with 4 dimensions (batch included), keras is adding the 5th.

      You should use input_shape=(32,32,1).

      • 1

    You must login to add an answer.