Cfrgtkky

I am doing scene classification but , I didn't get the correct image classification ,please help me how to do scene classification
I am create a dictionary like this

  label_dict={'0':'buildings', 



'1':'forest',



'2':'glacier',



'3':'mountain',



'4':'sea' ,



'5':'street' }

But how to classifly the image didn't understandard , I am bulid a model

model = Sequential()

model.add(Conv2D(32, kernel_size=(3, 3),

                 strides=2,

                 activation='relu',

                 input_shape=(32, 32, 3)))

model.add(Dropout(0.5))

model.add(Conv2D(32, kernel_size=(3, 3), strides=2, activation='relu'))

model.add(Dropout(0.5))

model.add(Flatten())

model.add(Dense(128, activation='relu'))

model.add(Dense(10, activation='softmax'))



model.compile(loss=keras.losses.categorical_crossentropy,

              optimizer='adam',

              metrics=['accuracy'])



model.summary(

I got errors are:

ValueError                                Traceback (most recent call last)

<ipython-input-16-4f5a963b4f20> in <module>

      1 model.fit(x_train, y_train,

      2           batch_size=128,

----> 3           epochs=5 ,validation_data=(x_test, y_test))



~/anaconda3/lib/python3.7/site-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)

    950             sample_weight=sample_weight,

    951             class_weight=class_weight,

--> 952             batch_size=batch_size)

    953         # Prepare validation data.

    954         do_validation = False



~/anaconda3/lib/python3.7/site-packages/keras/engine/training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, check_array_lengths, batch_size)

    787                 feed_output_shapes,

    788                 check_batch_axis=False,  # Don't enforce the batch size.

--> 789                 exception_prefix='target')

    790 

    791             # Generate sample-wise weight values given the `sample_weight` and



~/anaconda3/lib/python3.7/site-packages/keras/engine/training_utils.py in standardize_input_data(data, names, shapes, check_batch_axis, exception_prefix)

    136                             ': expected ' + names[i] + ' to have shape ' +

    137                             str(shape) + ' but got array with shape ' +

--> 138                             str(data_shape))

    139     return data

    140 



ValueError: Error when checking target: expected dense_2 to have shape (10,) but got array with shape (6,)

This is my JupyterNotebook like:
http://localhost:8888/notebooks/intel%20image%20classification.ipynb