Couche convolutionnelle de l'architecture du modèle Pass Input_shape
classifier = tf.keras.Sequential([
tf.keras.layers.Conv2D(16,(3,3),activation='relu',input_shape=(IMG_SHAPE, IMG_SHAPE, 3)),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Conv2D(32,(3,3),activation='relu'),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Conv2D(64,(3,3),activation='relu'),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Conv2D(128,(3,3),activation='relu'),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Dropout(0.32),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(1024,activation= 'relu'),
tf.keras.layers.Dense(3, activation = "softmax")
])
Akshay R