model.py

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