Models: UTKFace

class model.AgeModel
Description:
The model is a CNN with 6 convolutional layers and 1 linear layer. The images has been transformed to gray before feeding them to the network,
Model:
Conv 1:
Conv layer

in_channels = 1, out_channels =10, kernel_size= 3, Stride= 1, Padding= 1

BatchNorm2d

num_features= 10

ReLU

a non linear function.

MaxPool2d

kernel_size=2

Conv 2:
Conv layer

in_channels = 10, out_channels =20, kernel_size= 3, Stride= 1, Padding= 1

BatchNorm2d

num_features= 20

ReLU

a non linear function.

MaxPool2d

kernel_size=2, stride =2

Conv 3:
Conv layer

in_channels = 20, out_channels =32, kernel_size= 3, Stride= 1, Padding= 1

BatchNorm2d

num_features= 32

ReLU

a non linear function.

MaxPool2d

kernel_size=2, stride =2

Conv 4:
Conv layer

in_channels = 32, out_channels =64, kernel_size= 3, Stride= 1, Padding= 1

BatchNorm2d

num_features= 64

ReLU

a non linear function.

MaxPool2d

kernel_size=2, stride =2

Conv 5:
Conv layer

in_channels = 64, out_channels =128, kernel_size= 3, Stride= 1, Padding= 1

BatchNorm2d

num_features= 128

ReLU

a non linear function.

MaxPool2d

kernel_size=2, stride =2

Conv 6:
Conv layer

in_channels = 128, out_channels =256, kernel_size= 3, Stride= 1, Padding= 1

BatchNorm2d

num_features= 256

ReLU

a non linear function.

MaxPool2d

kernel_size=2, stride =2

Linear:

in_features = 256*3*3 , out_features = 1

forward(x)
Description:
Predict an age using an image.
Return:
Batch of labels (ages)
Return Type:
Tensor
Args:
x (tensor):Batch of images.