Example #1
0
def get_model_by_type(model_type, cfg):
    '''
    given the string model_type and the configuration settings in cfg
    create a Keras model and return it.
    '''
    from donkeycar.parts.keras import KerasRNN_LSTM, KerasBehavioral, KerasCategorical, KerasIMU, KerasLinear, Keras3D_CNN, KerasLocalizer, KerasLatent
    from donkeycar.parts.tflite import TFLitePilot

    if model_type is None:
        model_type = cfg.DEFAULT_MODEL_TYPE
    print("\"get_model_by_type\" model Type is: {}".format(model_type))

    input_shape = (cfg.IMAGE_H, cfg.IMAGE_W, cfg.IMAGE_DEPTH)
    roi_crop = (cfg.ROI_CROP_TOP, cfg.ROI_CROP_BOTTOM)

    if model_type == "tflite_linear":
        kl = TFLitePilot()
    elif model_type == "localizer" or cfg.TRAIN_LOCALIZER:
        kl = KerasLocalizer(num_outputs=2,
                            num_behavior_inputs=len(cfg.BEHAVIOR_LIST),
                            num_locations=cfg.NUM_LOCATIONS,
                            input_shape=input_shape)
    elif model_type == "behavior" or cfg.TRAIN_BEHAVIORS:
        kl = KerasBehavioral(num_outputs=2,
                             num_behavior_inputs=len(cfg.BEHAVIOR_LIST),
                             input_shape=input_shape)
    elif model_type == "imu":
        kl = KerasIMU(num_outputs=2, num_imu_inputs=6, input_shape=input_shape)
    elif model_type == "linear":
        kl = KerasLinear(input_shape=input_shape, roi_crop=roi_crop)
    elif model_type == "tensorrt_linear":
        # Aggressively lazy load this. This module imports pycuda.autoinit which causes a lot of unexpected things
        # to happen when using TF-GPU for training.
        from donkeycar.parts.tensorrt import TensorRTLinear
        kl = TensorRTLinear(cfg=cfg)
    elif model_type == "3d":
        kl = Keras3D_CNN(image_w=cfg.IMAGE_W,
                         image_h=cfg.IMAGE_H,
                         image_d=cfg.IMAGE_DEPTH,
                         seq_length=cfg.SEQUENCE_LENGTH)
    elif model_type == "rnn":
        kl = KerasRNN_LSTM(image_w=cfg.IMAGE_W,
                           image_h=cfg.IMAGE_H,
                           image_d=cfg.IMAGE_DEPTH,
                           seq_length=cfg.SEQUENCE_LENGTH)
    elif model_type == "categorical":
        kl = KerasCategorical(
            input_shape=input_shape,
            throttle_range=cfg.MODEL_CATEGORICAL_MAX_THROTTLE_RANGE,
            roi_crop=roi_crop)
    elif model_type == "latent":
        kl = KerasLatent(input_shape=input_shape)
    else:
        raise Exception("unknown model type: %s" % model_type)

    return kl
Example #2
0
def get_model_by_type(model_type: str, cfg: 'Config') -> 'KerasPilot':
    '''
    given the string model_type and the configuration settings in cfg
    create a Keras model and return it.
    '''
    from donkeycar.parts.keras import KerasPilot, KerasCategorical, \
        KerasLinear, KerasInferred
    from donkeycar.parts.tflite import TFLitePilot

    if model_type is None:
        model_type = cfg.DEFAULT_MODEL_TYPE
    print("\"get_model_by_type\" model Type is: {}".format(model_type))

    input_shape = (cfg.IMAGE_H, cfg.IMAGE_W, cfg.IMAGE_DEPTH)
    kl: KerasPilot
    if model_type == "linear":
        kl = KerasLinear(input_shape=input_shape)
    elif model_type == "categorical":
        kl = KerasCategorical(
            input_shape=input_shape,
            throttle_range=cfg.MODEL_CATEGORICAL_MAX_THROTTLE_RANGE)
    elif model_type == 'inferred':
        kl = KerasInferred(input_shape=input_shape)
    elif model_type == "tflite_linear":
        kl = TFLitePilot()
    elif model_type == "tensorrt_linear":
        # Aggressively lazy load this. This module imports pycuda.autoinit
        # which causes a lot of unexpected things to happen when using TF-GPU
        # for training.
        from donkeycar.parts.tensorrt import TensorRTLinear
        kl = TensorRTLinear(cfg=cfg)
    else:
        raise Exception("Unknown model type {:}, supported types are "
                        "linear, categorical, inferred, tflite_linear, "
                        "tensorrt_linear".format(model_type))

    return kl