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README.md
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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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### Data Fields
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### Data Splits
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## Dataset Structure
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### Dataset opening
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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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├── foldn
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│ ├── uid0
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│ │ ├── pre_fire
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│ │ ├── post_fire
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│ │ ├── mask
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│ ├── uid1
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│ ├── post_fire
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│ ├── mask
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│
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├── foldm
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├── uid2
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│ ├── post_fire
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│ ├── mask
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├── uid3
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├── pre_fire
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├── post_fire
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├── mask
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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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