_________________________________________________________________
Layer (type)                 Output Shape              Param #
=================================================================
input_1 (InputLayer)         (None, 28, 28, 28, 1)     0
_________________________________________________________________
conv3d_1 (Conv3D)            (None, 28, 28, 28, 16)    448
_________________________________________________________________
batch_normalization_1 (Batch (None, 28, 28, 28, 16)    64
_________________________________________________________________
activation_1 (Activation)    (None, 28, 28, 28, 16)    0
_________________________________________________________________
conv3d_2 (Conv3D)            (None, 28, 28, 28, 16)    6928
_________________________________________________________________
batch_normalization_2 (Batch (None, 28, 28, 28, 16)    64
_________________________________________________________________
activation_2 (Activation)    (None, 28, 28, 28, 16)    0
_________________________________________________________________
max_pooling3d_1 (MaxPooling3 (None, 14, 14, 14, 16)    0
_________________________________________________________________
conv3d_3 (Conv3D)            (None, 14, 14, 14, 32)    13856
_________________________________________________________________
batch_normalization_3 (Batch (None, 14, 14, 14, 32)    128
_________________________________________________________________
activation_3 (Activation)    (None, 14, 14, 14, 32)    0
_________________________________________________________________
conv3d_4 (Conv3D)            (None, 14, 14, 14, 32)    27680
_________________________________________________________________
batch_normalization_4 (Batch (None, 14, 14, 14, 32)    128
_________________________________________________________________
activation_4 (Activation)    (None, 14, 14, 14, 32)    0
_________________________________________________________________
max_pooling3d_2 (MaxPooling3 (None, 7, 7, 7, 32)       0
_________________________________________________________________
conv3d_5 (Conv3D)            (None, 7, 7, 7, 64)       55360
_________________________________________________________________
batch_normalization_5 (Batch (None, 7, 7, 7, 64)       256
_________________________________________________________________
activation_5 (Activation)    (None, 7, 7, 7, 64)       0
_________________________________________________________________
conv3d_6 (Conv3D)            (None, 7, 7, 7, 64)       110656
_________________________________________________________________
batch_normalization_6 (Batch (None, 7, 7, 7, 64)       256
_________________________________________________________________
activation_6 (Activation)    (None, 7, 7, 7, 64)       0
_________________________________________________________________
global_average_pooling3d_1 ( (None, 64)                0
=================================================================
Total params: 215,824
Trainable params: 215,376
Non-trainable params: 448

sgd = optimizers.SGD(lr=0.001, decay=0, momentum=0.9, nesterov=True)
with open(model) as f:
    model = model_from_json(f.read())

model.load_weights(weights)
model.layers.pop()

model2 = Model(inputs=model.layers[0].input, outputs=model.layers[-1].output)
model2.compile(optimizer=sgd,metrics=['accuracy'])

ct = self.load_full_ct(dcm_path)
vec = self.nn_model.predict(box.reshape(-1,28,28,28,1))