Created
February 18, 2021 02:32
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Conv2D, Flatten, Dense
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import tensorflow as tf | |
model = tf.keras.models.Sequential([ | |
tf.keras.layers.Conv2D(16, (3,3), activation='relu', input_shape=(300, 300, 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(64, (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.Flatten(), | |
tf.keras.layers.Dense(512, activation='relu'), | |
tf.keras.layers.Dense(1, activation='sigmoid') | |
]) | |
model.summary() |
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