Create README.md

README.md

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+Checkpoints of models in CanadaWildFireDaily benchmark.
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+Standard UNet(architecture: 'unet'): The baseline spatial U-Net model.
+Age-Encoding UNet(architecture: 'unet_age'): A U-Net that explicitly encodes the satellite age (the time gap in days between the fire event and the satellite acquisition).
+Spatiotemporal UNet(architecture: 'unet_convlstm'): A U-Net featuring aConvLSTMbottleneck for recurrent time-series processing (e.g., 3-day sliding window forecasting).
+Attention UNet(architecture: 'unet_attention'): A U-Net utilizing attention gates in the skip connections to help the model focus on the most critical spatial features and suppress irrelevant background noise.
+UNet-SegFormer(architecture: 'unet_segformer'): A hybrid vision-transformer architecture that replaces the standard CNN encoder with SegFormer's Mix Vision Transformer (MiT), paired with a standard U-Net decoder for heavy pixel-level accuracy.
+UT-AE(architecture: 'utae'): A temporal attention encoder-decoder baseline adapted from the ICCV 2021 U-TAE model for satellite image time series. This baseline uses the time-series offline samples fromTimeseries_Samples/, and the generator now stores sequence positions for the temporal attention encoder when you regenerate those samples.