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import tensorflow as tf
from tensorflow.keras import layers, models
from tensorflow.keras.applications import InceptionV3
def create_model():
base_model = InceptionV3(weights='imagenet', include_top=False, input_shape=(150, 150, 3))
base_model.trainable = False # Freezing the base model layers
model = models.Sequential([
base_model,
layers.GlobalAveragePooling2D(),
layers.Dense(512, activation='relu'),
layers.Dropout(0.5),
layers.Dense(1, activation='sigmoid')
])
model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.0001),
loss='binary_crossentropy',
metrics=['accuracy'])
return model
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