If I want to use anti_spoofing.h5 separately, what image dimension should I pass to the model?
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d (Conv2D) (None, 112, 112, 18) 504
activation (Activation) (None, 112, 112, 18) 0
batch_normalization (BatchN (None, 112, 112, 18) 72
ormalization)
conv2d_1 (Conv2D) (None, 112, 112, 18) 2934
activation_1 (Activation) (None, 112, 112, 18) 0
max_pooling2d (MaxPooling2D (None, 56, 56, 18) 0
)
batch_normalization_1 (Batc (None, 56, 56, 18) 72
hNormalization)
conv2d_2 (Conv2D) (None, 56, 56, 36) 5868
activation_2 (Activation) (None, 56, 56, 36) 0
batch_normalization_2 (Batc (None, 56, 56, 36) 144
hNormalization)
conv2d_3 (Conv2D) (None, 56, 56, 36) 11700
activation_3 (Activation) (None, 56, 56, 36) 0
max_pooling2d_1 (MaxPooling (None, 28, 28, 36) 0
2D)
batch_normalization_3 (Batc (None, 28, 28, 36) 144
hNormalization)
flatten (Flatten) (None, 28224) 0
dense (Dense) (None, 128) 3612800
activation_4 (Activation) (None, 128) 0
dropout (Dropout) (None, 128) 0
dense_1 (Dense) (None, 2) 258
activation_5 (Activation) (None, 2) 0
=================================================================
Total params: 3,634,496
Trainable params: 3,634,280
Non-trainable params: 216
_________________________________________________________________