Generative Adversarial Networks Projects

Upsampling Blocks

Upsampling blocks contain layers that increase the spatial resolution of images and generate a high-resolution image of dimensions 256x256x3.

Let's write the code for the upsampling blocks:

1. Firstly, add an upsampling block that contains a 2D upsampling layer, a 2D convolutional layer, a batch normalization, and an activation function. The different parameters that are used in the block are the following:
   • Upsampling size: (2, 2)
   • Filters: 512
   • Kernel size: 3
   • Padding: "same"
   • Strides: 1
   • Batch normalization: Yes
   • Activation: ReLU

x = UpSampling2D(size=(2, 2))(x)x = Conv2D(512, kernel_size=3, padding="same", strides=1, use_bias=False)(x)x = BatchNormalization()(x)x = ReLU()(x)

2. Next, add three more upsampling blocks. The hyperparameters ...