Datasets:
Update README.md
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README.md
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@@ -203,23 +203,32 @@ dataset = build_terramesh_dataset(
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If you only use a single modality, you
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### Returning metadata
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You can pass `return_metadata=True` to `build_terramesh_dataset()` to load center longitude and latitude, timestamps, and the S2 cloud mask as additional metadata.
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The resulting batch keys include: `["__key__", "__url__", "S2L2A", "S1RTC", ..., "center_lon", "center_lat", "cloud_mask", "time_S2L2A", "time_S1RTC", ...]
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Therefore, you need to update the
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```
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...
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additional_targets={m: "image" for m in modalities + ["cloud_mask"]}
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),
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non_image_modalities=["__key__", "__url__", "center_lon", "center_lat"] + ["time_" + m for m in modalities]
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```
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The cloud mask provides the classes land (0), water (1), snow (2), thin cloud (3), thick cloud (4), and cloud shadow (5), and no data (6).
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DEM does not return a time value while LULC uses the S2 timestamp because of the augmentation usign the S2 cloud and ice mask. Time values are returned as integer values but can be converted back to datetime with
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```python
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)
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```
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If you only use a single modality, you don't need to specify `additional_targets`.
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### Returning metadata
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You can pass `return_metadata=True` to `build_terramesh_dataset()` to load center longitude and latitude, timestamps, and the S2 cloud mask as additional metadata.
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The resulting batch keys include: `["__key__", "__url__", "S2L2A", "S1RTC", ..., "center_lon", "center_lat", "cloud_mask", "time_S2L2A", "time_S1RTC", ...]`.
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Therefore, you need to update the `transform` if you use one:
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```python
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...
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additional_targets={m: "image" for m in modalities + ["cloud_mask"]}
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),
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non_image_modalities=["__key__", "__url__", "center_lon", "center_lat"] + ["time_" + m for m in modalities]
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```
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For a single modality dataset, "time" does not have a suffix and the following changes for the `transform` are required:
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```python
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...
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additional_targets={"cloud_mask": "image"}
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),
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non_image_modalities=["__key__", "__url__", "center_lon", "center_lat", "time"]
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```
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Note that center points are not updated when random crop is used.
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The cloud mask provides the classes land (0), water (1), snow (2), thin cloud (3), thick cloud (4), and cloud shadow (5), and no data (6).
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DEM does not return a time value while LULC uses the S2 timestamp because of the augmentation usign the S2 cloud and ice mask. Time values are returned as integer values but can be converted back to datetime with
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```python
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