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@@ -27,13 +27,40 @@ The dataset is designed to do binary semantic segmentation of burned vs unburned
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  ## Dataset Structure
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  ### Data Instances
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- [More Information Needed]
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  ### Data Fields
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Data Splits
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  ## Dataset Structure
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+ ### Dataset opening
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+
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+ Dataset was compressed using `h5py` and BZip2 from `hdf5plugin`. **WARNING: `hdf5plugin` is necessary to extract data**
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  ### Data Instances
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+ Each matrix has a shape of 5490x5490xC, where C is 12 for pre-fire and post-fire images, while it is 0 for binary masks.
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  ### Data Fields
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+ In each HDF5 file, you can find post-fire, pre-fire images and binary masks. The file is structured in this way:
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+ ```bash
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+ β”œβ”€β”€ foldn
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+ β”‚ β”œβ”€β”€ uid0
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+ β”‚ β”‚ β”œβ”€β”€ pre_fire
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+ β”‚ β”‚ β”œβ”€β”€ post_fire
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+ β”‚ β”‚ β”œβ”€β”€ mask
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+ β”‚ β”œβ”€β”€ uid1
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+ β”‚ β”œβ”€β”€ post_fire
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+ β”‚ β”œβ”€β”€ mask
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+ β”‚
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+ β”œβ”€β”€ foldm
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+ β”œβ”€β”€ uid2
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+ β”‚ β”œβ”€β”€ post_fire
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+ β”‚ β”œβ”€β”€ mask
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+ β”œβ”€β”€ uid3
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+ β”œβ”€β”€ pre_fire
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+ β”œβ”€β”€ post_fire
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+ β”œβ”€β”€ mask
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+ ...
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+ ```
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+
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+ where `foldn` and `foldm` are fold names and `uidn` is a unique identifier for the wilfire.
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  ### Data Splits
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