code: def loadModel(
      url="https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5",
  ) -> Model:
      myInput = Input(shape=(55, 47, 3))
  
      x = Conv2D(
          20,
          (4, 4),
          name="Conv1",
          activation="relu",
          input_shape=(55, 47, 3),
      )(myInput)
      x = MaxPooling2D(pool_size=2, strides=2, name="Pool1")(x)
      x = Dropout(rate=0.99, name="D1")(x)
  
      x = Conv2D(40, (3, 3), name="Conv2", activation="relu")(x)
      x = MaxPooling2D(pool_size=2, strides=2, name="Pool2")(x)
      x = Dropout(rate=0.99, name="D2")(x)
  
      x = Conv2D(60, (3, 3), name="Conv3", activation="relu")(x)
      x = MaxPooling2D(pool_size=2, strides=2, name="Pool3")(x)
      x = Dropout(rate=0.99, name="D3")(x)
  
      x1 = Flatten()(x)
      fc11 = Dense(160, name="fc11")(x1)
  
      x2 = Conv2D(80, (2, 2), name="Conv4", activation="relu")(x)
      x2 = Flatten()(x2)
      fc12 = Dense(160, name="fc12")(x2)
  
      y = Add()([fc11, fc12])
      y = Activation("relu", name="deepid")(y)
  
      model = Model(inputs=[myInput], outputs=y)
  
      # ---------------------------------
  
      home = functions.get_deepface_home()
  
      if (
          os.path.isfile(
              home + "/.deepface/weights/deepid_keras_weights.h5"
          )
          != True
      ):
          logger.info("deepid_keras_weights.h5 will be downloaded...")
  
          output = home + "/.deepface/weights/deepid_keras_weights.h5"
          gdown.download(url, output, quiet=False)
  
      model.load_weights(
          home + "/.deepface/weights/deepid_keras_weights.h5"
      )
  
      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: loadModel(url) and returns: model