(time_len=1)
| 22 | |
| 23 | |
| 24 | def get_model(time_len=1): |
| 25 | ch, row, col = 3, 160, 320 # camera format |
| 26 | |
| 27 | model = Sequential() |
| 28 | model.add(Lambda(lambda x: x/127.5 - 1., |
| 29 | input_shape=(ch, row, col), |
| 30 | output_shape=(ch, row, col))) |
| 31 | model.add(Convolution2D(16, 8, 8, subsample=(4, 4), border_mode="same")) |
| 32 | model.add(ELU()) |
| 33 | model.add(Convolution2D(32, 5, 5, subsample=(2, 2), border_mode="same")) |
| 34 | model.add(ELU()) |
| 35 | model.add(Convolution2D(64, 5, 5, subsample=(2, 2), border_mode="same")) |
| 36 | model.add(Flatten()) |
| 37 | model.add(Dropout(.2)) |
| 38 | model.add(ELU()) |
| 39 | model.add(Dense(512)) |
| 40 | model.add(Dropout(.5)) |
| 41 | model.add(ELU()) |
| 42 | model.add(Dense(1)) |
| 43 | |
| 44 | model.compile(optimizer="adam", loss="mse") |
| 45 | |
| 46 | return model |
| 47 | |
| 48 | |
| 49 | if __name__ == "__main__": |
no outgoing calls
no test coverage detected