code: def baseModel() -> Sequential:
      model = Sequential()
      model.add(ZeroPadding2D((1, 1), input_shape=(224, 224, 3)))
      model.add(Convolution2D(64, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(64, (3, 3), activation="relu"))
      model.add(MaxPooling2D((2, 2), strides=(2, 2)))
  
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(128, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(128, (3, 3), activation="relu"))
      model.add(MaxPooling2D((2, 2), strides=(2, 2)))
  
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(256, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(256, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(256, (3, 3), activation="relu"))
      model.add(MaxPooling2D((2, 2), strides=(2, 2)))
  
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(512, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(512, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(512, (3, 3), activation="relu"))
      model.add(MaxPooling2D((2, 2), strides=(2, 2)))
  
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(512, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(512, (3, 3), activation="relu"))
      model.add(ZeroPadding2D((1, 1)))
      model.add(Convolution2D(512, (3, 3), activation="relu"))
      model.add(MaxPooling2D((2, 2), strides=(2, 2)))
  
      model.add(Convolution2D(4096, (7, 7), activation="relu"))
      model.add(Dropout(0.5))
      model.add(Convolution2D(4096, (1, 1), activation="relu"))
      model.add(Dropout(0.5))
      model.add(Convolution2D(2622, (1, 1)))
      model.add(Flatten())
      model.add(Activation("softmax"))
  
      return model
  
imports: import os
  import gdown
  import tensorflow
  from deepface.commons import functions
  from deepface.commons.logger import Logger
label_desc: Use image node_id 1 for calling a global function with example usage: baseModel() and returns: model