(img_dim, nb_classes, model_name="FCN")
| 23 | |
| 24 | |
| 25 | def FCN(img_dim, nb_classes, model_name="FCN"): |
| 26 | |
| 27 | x_input = Input(shape=img_dim, name="input") |
| 28 | |
| 29 | x = Flatten()(x_input) |
| 30 | |
| 31 | for i in range(20): |
| 32 | x = Dense(50, activation="relu")(x) |
| 33 | |
| 34 | x = Dense(nb_classes, activation="softmax")(x) |
| 35 | |
| 36 | FCN = Model(inputs=[x_input], outputs=[x]) |
| 37 | FCN.name = model_name |
| 38 | |
| 39 | return FCN |
| 40 | |
| 41 | |
| 42 | def CNN(img_dim, nb_classes, model_name="CNN"): |