DSen2 Model¶
ResBlock
¶
Bases: Module
A standard residual block with two convolutional layers.
__init__(channels, kernel_size=3, scale=0.1)
¶
Initializes the ResBlock.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
channels
|
int
|
The number of input and output channels. |
required |
kernel_size
|
int
|
The size of the convolutional kernel. Defaults to 3. |
3
|
scale
|
float
|
A scaling factor applied to the residual branch before addition. Defaults to 0.1. |
0.1
|
forward(x: torch.Tensor) -> torch.Tensor
¶
Defines the forward pass for the residual block.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
x
|
Tensor
|
The input tensor. |
required |
Returns:
| Type | Description |
|---|---|
Tensor
|
torch.Tensor: The output tensor after applying the residual connection. |
DSen2
¶
Bases: Model
Implementation of the DSen2 model for Sentinel-2 super-resolution.
This model is designed to super-resolve 20m and 60m Sentinel-2 bands to 10m resolution, using the 10m bands as a reference.
Reference
Lanaras, C., Bioucas-Dias, J., Baltsavias, E., & Schindler, K. (2018). Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network. ISPRS Journal of Photogrammetry and Remote Sensing.
__init__(num_layers=32, feature_size=256, input_channels=12, return_10m_bands=True)
¶
Initializes the DSen2 model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
num_layers
|
int
|
The number of residual blocks in the main body of the network. Defaults to 32. |
32
|
feature_size
|
int
|
The number of channels in the intermediate feature maps. Defaults to 256. |
256
|
input_channels
|
int
|
The total number of input channels from all concatenated Sentinel-2 bands. Defaults to 12. |
12
|
return_10m_bands
|
bool
|
If True, the output dictionary will also include the original, untouched 10m bands. Defaults to True. |
True
|