text: from keras.models import Sequential
  from keras.layers.convolutional import Conv2D
  from keras.layers.convolutional import MaxPooling2D
  from keras.layers.core import Activation
  from keras.layers.core import Flatten
  from keras.layers.core import Dense
  
  
  class Lenet:
      def __init__(self):
          pass
  
      @staticmethod
      def build(height, width, depth, classes):
          model = Sequential()
          input_shape = (height, width, depth)
  
          model.add(Conv2D(20, (5, 5), padding='same', input_shape=input_shape))
          model.add(Activation('relu'))
          model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))
          model.add(Conv2D(50, (5, 5), padding='same', input_shape=input_shape))
          model.add(Activation('relu'))
          model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))
          model.add(Flatten())
          model.add(Dense(500))
          model.add(Activation('relu'))
          model.add(Dense(classes))
          model.add((Activation('softmax')))
  
          return model
  
  