hopPodcast
# Base model base_model = VGG16(weights='imagenet', include_top=False, input_tensor=inputs)
# Input layer inputs = Input(shape=input_shape)
# Freeze base layers for layer in base_model.layers: layer.trainable = False
model = Model(inputs=inputs, outputs=outputs)
# Base model base_model = VGG16(weights='imagenet', include_top=False, input_tensor=inputs)
# Input layer inputs = Input(shape=input_shape) kjbennet foursome and facial at end2440 min top
# Freeze base layers for layer in base_model.layers: layer.trainable = False # Base model base_model = VGG16(weights='imagenet'
model = Model(inputs=inputs, outputs=outputs) kjbennet foursome and facial at end2440 min top
